A review of quantitative methods for movement data
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paper_title: Moving Objects Databases

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Introduction Spatio-Temporal Databases in the Past Modeling and Querying Current Movement Modeling and Querying History of Movement Data Structures and Algorithms for Moving Objects Types The Constraint Database Approach Spatio-Temporal Indexing.
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paper_title: SECONDO: A Platform for Moving Objects Database Research and for Publishing and Integrating Research Implementations

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Databases supporting time dependent and continuously changing geometries, called ::: moving ob- ::: jects databases ::: , have been studied for about 15 years. The field has been flourishing and there exist ::: many hundreds, more likely thousands, of publications. However, very few of these results have ::: made it into systems (research prototypes or commercial) and are available for practical use today. ::: It is not that the publications are purely theoretical. In most cases data structures and algorithms ::: have been proposed, implemented, and experimentally evaluated. However, whereas there exists a ::: well established infrastructure for publishing research papers through journals and conferences, no ::: such facilities exist for the publication of the related prototypical implementations. Hence imple- ::: mentations are just done for experiments in the paper and then usually abandoned. This is highly ::: unfortunate even for research, as future proposals of improved algorithms most often have to reim- ::: plement the previous techniques they need to compare to. ::: In this paper we describe an infrastructure for research in moving objects databases that addresses ::: some of these problems. Essentially it allows researchers to implement their new techniques within ::: a system context and to make them available for practical use to all readers of their papers and ::: users of the system. The infrastructure consists of ::: S ::: ECONDO ::: , an extensible database system into ::: which a lot of moving object technology has been built already. It offers BerlinMOD, a benchmark ::: to generate large sets of realistic moving object trajectories together with a comprehensive set of ::: queries. Finally, it offers ::: S ::: ECONDO ::: Plugins as a facility to publish new research implementations ::: that anyone can merge with a standard ::: S ::: ECONDO ::: distribution to have them run in a complete system ::: context.
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paper_title: Indoor - A New Data Management Frontier

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Much research has been conducted on the management of outdoor moving objects. In contrast, relatively little research has been conducted on indoor moving objects. The indoor setting differs from outdoor settings in important ways, including the following two. First, indoor spaces exhibit complex topologies. They are composed of entities that are unique to indoor settings, e.g., rooms and hallways that are connected by doors. As a result, conventional Euclidean distance and spatial network distance are inapplicable in indoor spaces. Second, accurate, GPS-like positioning is typically unavailable in indoor spaces. Rather, positioning is achieved through the use of technologies such as Bluetooth, Infrared, RFID, or Wi-Fi. This typically results in much less reliable and accurate positioning. This paper covers some preliminary research that explicitly targets an indoor setting. Specifically, we describe a graph-based model that enables the effective and efficient tracking of indoor objects using proximity-based positioning technologies like RFID and Bluetooth. Furthermore, we categorize objects according to their position-related states, present an on-line hash-based object indexing scheme, and conduct an uncertainty analysis for indoor objects. We end by identifying several interesting and important directions for future research.
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paper_title: What about time in urban planning & design in the ICT age?

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CORP 2005 & Geomultimedia05 Feb. 22-25 2005 www.corp.at Proceedings / Tagungsband; Ed. / Hg.: Manfred SCHRENK ISBN: 3-901673-12-1 (Hardcopy-Edition) ISBN: 3-901673-13-X (CD-Edition) 13 What about time in urban planning & design in the ICT age? Paul DREWE (Prof. Paul DREWE, Delft University of Technology, Design Studio ‘ The Network City’, Faculty of Architecture, Berlageweg 1, Delft, p.drewe@bk.tudelft.nl)
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paper_title: A movement ecology paradigm for unifying organismal movement research.

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Movement of individual organisms is fundamental to life, quilting our planet in a rich tapestry of phenomena with diverse implications for ecosystems and humans. Movement research is both plentiful and insightful, and recent methodological advances facilitate obtaining a detailed view of individual movement. Yet, we lack a general unifying paradigm, derived from first principles, which can place movement studies within a common context and advance the development of a mature scientific discipline. This introductory article to the Movement Ecology Special Feature proposes a paradigm that integrates conceptual, theoretical, methodological, and empirical frameworks for studying movement of all organisms, from microbes to trees to elephants. We introduce a conceptual framework depicting the interplay among four basic mechanistic components of organismal movement: the internal state (why move?), motion (how to move?), and navigation (when and where to move?) capacities of the individual and the external factors affecting movement. We demonstrate how the proposed framework aids the study of various taxa and movement types; promotes the formulation of hypotheses about movement; and complements existing biomechanical, cognitive, random, and optimality paradigms of movement. The proposed framework integrates eclectic research on movement into a structured paradigm and aims at providing a basis for hypothesis generation and a vehicle facilitating the understanding of the causes, mechanisms, and spatiotemporal patterns of movement and their role in various ecological and evolutionary processes. "Now we must consider in general the common reason for moving with any movement whatever." (Aristotle, De Motu Animalium, 4th century B.C.).
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paper_title: EDGIS: a dynamic GIS based on space time points

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Contemporary GIS can handle static spatial data for querying and visual representation, but the temporal dimension remains a challenge. This paper addresses the need for a dynamic GIS capable of managing complex data types. The design relies on a representation of the theoretical spatiotemporal primitive known as the 'geo-atom'. This paper proposes a novel and implemented data structure called the space time point (STP) built on this theory. With the STP representation, spatiotemporal data queries can be posed to return useful results about dynamic geographic phenomena and their interaction. Two key challenges addressed in this research are (1) data structures to represent hybrid (object and field) spatiotemporal phenomena and (2) the design of a dynamic GIS interface. These challenges are addressed by the implementation of the system, referred to as 'Extended Dynamic GIS (EDGIS)', that uses the proposed STPs. The EDGIS system is described from theory to its implementation in Java™ and a series of application examples are described followed by performance metrics. The paper concludes with a discussion of areas for further research such as integration of the system with geo-sensor networks, hazards, transportation, and location-based services (LBS).
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paper_title: W(h)ither spatial science and spatial analysis

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Abstract Spatial analysis, which emerged as the dominant geographical paradigm during the 1960s, was quickly eclipsed not simply through its inability to deal with deeper structures and processes but because of its inability to deal with questions of bounded space. In this paper, the limits that spatial analysis and its newer approaches through geographic information systems (GIS) pose are examined; and contemporary views of geographical space that build on localisation and globalisation, and on time-space compression, are considered.
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paper_title: Real-Time Missile Tracking with GPS

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This paper describes a system for real-time tracking of long-range missiles based on use of the Global Positioning System (GPS). When GPS is fully operational, an in-place reference system will exist for use in tracking moving vehicles such a missiles, aircraft, and ground vehicles. In order to obtain the maximum benefit of this capability, an economical means of tracking the test vehicles is necessary. This is particularly true in tracking expendable test vehicles such as missiles. ::: ::: ::: ::: The techniques presented in this paper represent an approach to economical tracking of expendable test missiles. In this concept, the tracked missile receives the GPS signals, translates a composite signal spectrum to a new S-band frequency, and then transmits the composite S-band spectrum to a ground-station receiver. The ground station receives and processes the translated GPS signals into normal pseudorange and range-rate measurements of the missile. A Kalman filter is used to obtain a position and velocity solution. In addition to its capability for standalone performance, the described system could be incorporated into existing tracking systems, resulting in improved tracking accuracy.
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paper_title: A Characteristic-Hull Based Method for Home Range Estimation

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Recent literature has reported inaccuracies associated with some popular home range estimators such as kernel density estimation, especially when applied to point patterns of complex shapes. This study explores the use of characteristic hull polygons (CHPs) as a new method of home range estimation. CHPs are special bounding polygons created in GIS that can have concave edges, be composed of disjoint regions, and contain areas of unoccupied space within their interiors. CHPs are created by constructing the Delaunay triangulation of a set of points and then removing a subset of the resulting triangles. Here, CHPs consisting of 95% of the smallest triangles, measured in terms of perimeter, are applied for home range estimation. First, CHPs are applied to simulated animal locational data conforming to five point pattern shapes at three sample sizes. Then, the method is applied to black-footed albatross (Phoebastria nigripes) locational data for illustration and comparison to other methods. For the simulated data, 95% CHPs produced unbiased home range estimates in terms of size for linear and disjoint point patterns and slight underestimates (8–20%) for perforated, concave, and convex ones. The estimated and known home ranges intersected one another by 72–96%, depending on shape and sample size, suggesting that the method has potential as a home range estimator. Additionally, the CHPs applied to estimate albatross home ranges illustrate how the method produces reasonable estimates for bird species that intensively forage in disjoint habitat patches.
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paper_title: Designing visual analytics methods for massive collections of movement data

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Exploration and analysis of large data sets cannot be carried out using purely visual means but require the involvement of database technologies, computerized data processing, and computational analysis methods. An appropriate combination of these technologies and methods with visualization may facilitate synergetic work of computer and human whereby the unique capabilities of each “partner” can be utilized. We suggest a systematic approach to defining what methods and techniques, and what ways of linking them, can appropriately support such a work. The main idea is that software tools prepare and visualize the data so that the human analyst can detect various types of patterns by looking at the visual displays. To facilitate the detection of patterns, we must understand what types of patterns may exist in the data (or, more exactly, in the underlying phenomenon). This study focuses on data describing movements of multiple discrete entities that change their positions in space while preserving their integrity and identity. We define the possible types of patterns in such movement data on the basis of an abstract model of the data as a mathematical function that maps entities and times onto spatial positions. Then, we look for data transformations, computations, and visualization techniques that can facilitate the detection of these types of patterns and are suitable for very large data sets – possibly too large for a computer's memory. Under such constraints, visualization is applied to data that have previously been aggregated and generalized by means of database operations and/or computational techniques.
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paper_title: Special issue on data management for mobile services

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Small, GPS-enabled and wireless networked mobile devices such as mobile phones, personal digital assistants, or car navigation systems have become powerful, affordable, and wide-spread.Not only do these devices interactwith the environment such as local services and facilities, searching for useful information, but they are also capable of collecting and transmitting position data. There is a need for addressing both aspects, of supporting online services by managing the locations of large sets of currently moving users, and of analyzing enormous volumes of captured trajectory data. The latter may in particular be useful for improving mobile services. This special issue focuses on managing information about movingobjects in space and time, both for online applications and for analysis of ‘historical’ trajectory data. The complex form of trajectory data obtained from objects (typically moving in road networks) calls for specializedmethods for indexing, in order to meet the demands of online query evaluation. In addition, the limited resources of the mobile devices that sense and transmit the locations of themoving objects call for techniques that minimize the communication cost of location updates, without sacrificing too much accuracy. Specialized data analysts and common users need effective and efficient tools for querying and mining the large volume of the mobile data that are collected. These include systems that allow the identification of complex forms of data patterns, support aggregate queries, proximity, and direction queries and
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paper_title: Time-geographic density estimation for moving point objects

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This research presents a time-geographic method of density estimation for moving point objects. The approach integrates traditional kernel density estimation (KDE) with techniques of time geography to generate a continuous intensity surface that characterises the spatial distribution of a moving object over a fixed time frame. This task is accomplished by computing density estimates as a function of a geo-ellipse generated for each consecutive pair of control points in the object's space-time path and summing those values at each location in a manner similar to KDE. The main advantages of this approach are: (1) that positive intensities are only assigned to locations within a moving object's potential path area and (2) that it avoids arbitrary parameter selection as the amount of smoothing is controlled by the object's maximum potential velocity. The time-geographic density estimation technique is illustrated with a sample dataset, and a discussion of limitations and future work is provided.
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paper_title: Illuminating the Path: The Research and Development Agenda for Visual Analytics

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This is the book form of the Research and Development Agenda for Visual Analytics to be published by IEEE in 2005.
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paper_title: Space-Time and Integral Measures of Individual Accessibility: A Comparative Analysis Using a Point-based Framework

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Conventional integral measures of accessibility, although valuable as indicators of place accessibility, have several limitations when used to evaluate individual accessibility. Two alternatives for overcoming some of the difficulties involved are explored in this study. One is to adapt these measures for evaluating individual accessibility using a disaggregate, nonzonal approach. The other is to develop different types of measures based on an alternative conceptual framework. To pursue the former alternative, this study specifies and examines eighteen gravity-type and cumulative-opportunity accessibility measures using a point-based spatial framework. For the latter option, twelve space-time accessibility measures are developed based on the construct of a prism-constrained feasible opportunity set. This paper compares the relationships and spatial patterns of these thirty measures using network-based GIS procedures. Travel diary data collected in Columbus, Ohio, and a digital data set of 10,727 selected land parcels are used for all computation. Results of this study indicate that space-time and integral indices are distinctive types of accessibility measures which reflect different dimensions of the accessibility experience of individuals. Since space-time measures are more capable of capturing interpersonal differences, especially the effect of space-time constraints, they are more “gender sensitive” and helpful for unraveling gender/ethnic differences in accessibility. An important methodological implication is that whether accessibility is observed to be important or different between individuals depends heavily on whether the measure used is capable of revealing the kind of differences the analyst intends to observe.
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paper_title: Discovering relative motion patterns in groups of moving point objects

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Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been impleme...
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paper_title: Modelling accessibility using space-time prism concepts within geographical information systems.

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Abstract The space-time Of time geographical framework is a powerful perspective from which to analyse human behaviour. One of the central concepts in this framework is the space-time prism, which models individual accessibility to an environment. In this paper, the derivation and manipulation of space-time prism concepts within a geographical information system (GIS) are discussed. The required system inputs and desired outputs are identified and a generic GIS based procedure is presented Given these basic requirements, issues are discussed which can determine the feasibility of current GIS technology to handle the derivation of space-time prism concepts.
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paper_title: Geographical information science

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Abstract. Research papers at conferences such as EGIS and the International Symposia on Spatial Data Handling address a set of intellectual and scientific questions which go well beyond the limited technical capabilities of current technology in geographical information systems. This paper reviews the topics which might be included in a science of geographical information. Research on these fundamental issues is a better prospect for long-term survival and acceptance in the academy than the development of technical capabilities. This paper reviews the current state of research in a series of key areas and speculates on why progress has been so uneven. The final section of the paper looks to the future and to new areas of significant potential in this area of research.
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paper_title: Timing Space and Spacing Time

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A plea is made for a chronosophical approach to the selection of dimensions of time which might be relevant to the description and explanation of urban processes. Following the definition of some basic terms and concepts which might be used in the future development of a notational schema, the paper considers some possibilities which are inherent in the idea of timing space. This is followed by similar consideration of the idea of spacing time. These themes are compounded in a simple example which suggests that fundamental ongoing processes in daily urban behaviour are usefully summarised by what we call the accordion effect. The final section proposes that new insights into the problem of evaluating the quality of life of urban residents are obtained when such an approach is taken.
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paper_title: WHAT ABOUT PEOPLE IN REGIONAL SCIENCE?

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The described locking mechanism permits two or more rods to be quickly fitted together and adjusted to a fixed, predetermined length. The locking mechanism is of a type such that the rotation of the rods by approximately 45 DEG -90 DEG automatically fixes the rods in place.
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paper_title: Algorithms for constrained k-nearest neighbor queries over moving object trajectories

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An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (CkNN) queries and historical continuous CkNN (HCCkNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a CkNN query over trajectories retrieves from D within T, the k (? 1) trajectories that lie closest to q and intersect (or are enclosed by) CR; and (ii) an HCCkNN query on trajectories retrieves the constrained k nearest neighbors (CkNNs) of q at any time instance of T. We propose a suite of algorithms for processing CkNN queries and HCCkNN queries respectively, with different properties and advantages. In particular, we thoroughly investigate two types of CkNN queries, i.e., CkNNP and CkNNT, which are defined with respect to stationary query points and moving query trajectories, respectively; and two types of HCCkNN queries, namely, HCCkNNP and HCCkNNT, which are continuous counterparts of CkNNP and CkNNT, respectively. Our methods utilize an existing data-partitioning index for trajectory data (i.e., TB-tree) to achieve low I/O and CPU cost. Extensive experiments with both real and synthetic datasets demonstrate the performance of the proposed algorithms in terms of efficiency and scalability.
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paper_title: Modeling Moving Objects over Multiple Granularities

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This paper introduces a framework for modeling the movement of objects or individuals over multiple granularities. i>Granularity refers to selecting the appropriate level of detail for a task. At fine granularities, spatio-temporal information is revealed that was not previously known, such as additional locations that an individual visited or multiple visits to the same location. Conversely, moving to a coarser granularity or simpler view generalizes spatial and temporal aspects of movement allowing for an improved understanding of movement. Movement is modeled as i>geospatial lifelines, time-stamped records of the locations that an individual has occupied over a period of time. Depending on the desired granularity, lifelines are modeled as lifeline beads, necklaces, or more general approximations of these structures and this paper examines how different aspects of lifelines become relevant at refined or coarse granularities.
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paper_title: Time-space constraints and the formation of trip chains

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Abstract This study is concerned with a worker's decision to chain trips when a non-work, out-of-home activity is pursued together with obligatory work activities. Using a simple model, factors related to the likelihood of combining activities into a multi-sojourn trip chain are examined. The analysis indicates that the likelihood depends on whether marginal benefit of the time spent for in-home activities diminishes or not. It is shown that if marginal benefit diminishes, a longer activity duration, larger distance between the home and non-work activity locations, larger distance between the home and work location, and slower speed of the travel mode used, tend to favor a multi-sojourn trip chain. When the marginal benefit does not diminish, the relation is in general reversed. Tabulation of origin-destination survey results in general supports the notion of non-diminishing marginal benefit of in-home activity time. Estimation of constrained discrete-choice models also offers results that are consistent with non-diminishing benefit of in-home time. It is also indicated that trip chaining behavior is less sensitive to the sojourn duration and travel mode in the evening period than in the morning.
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paper_title: WHAT ABOUT PEOPLE IN REGIONAL SCIENCE?

paper_content:

The described locking mechanism permits two or more rods to be quickly fitted together and adjusted to a fixed, predetermined length. The locking mechanism is of a type such that the rotation of the rods by approximately 45 DEG -90 DEG automatically fixes the rods in place.
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paper_title: Moving Objects Databases

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Introduction Spatio-Temporal Databases in the Past Modeling and Querying Current Movement Modeling and Querying History of Movement Data Structures and Algorithms for Moving Objects Types The Constraint Database Approach Spatio-Temporal Indexing.
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paper_title: Modeling Moving Objects over Multiple Granularities

paper_content:

This paper introduces a framework for modeling the movement of objects or individuals over multiple granularities. i>Granularity refers to selecting the appropriate level of detail for a task. At fine granularities, spatio-temporal information is revealed that was not previously known, such as additional locations that an individual visited or multiple visits to the same location. Conversely, moving to a coarser granularity or simpler view generalizes spatial and temporal aspects of movement allowing for an improved understanding of movement. Movement is modeled as i>geospatial lifelines, time-stamped records of the locations that an individual has occupied over a period of time. Depending on the desired granularity, lifelines are modeled as lifeline beads, necklaces, or more general approximations of these structures and this paper examines how different aspects of lifelines become relevant at refined or coarse granularities.
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paper_title: The concept of animals' trajectories from a data analysis perspective

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Abstract The Global Positioning System (GPS) has been increasingly used during the past decade to monitor the movements of free-ranging animals. This technology allows to automatically relocate fitted animals, which often results into a high-frequency sampling of their trajectory during the study period. However, depending on the objective of trajectory analysis, this study may quickly become difficult, due to the lack of well designed computer programs. For example, the trajectory may be built by several “parts” corresponding to different behaviours of the animal, and the aim of the analysis could be to identify the different parts, and thereby the different activities, based on the properties of the trajectory. This complex task needs to be performed into a flexible computing environment, to facilitate exploratory analysis of its properties. In this paper, we present a new class of object of the R software, the class “ltraj” included in the package adehabitat, allowing the analysis of animals' trajectories. We developed this class of data after an extensive review of the literature on the analysis of animal movements. This class of data facilitates the computation of descriptive parameters of the trajectory (such as the relative angles between successive moves, distance between successive relocations, etc.), graphical exploration of these parameters, as well a numerous tests and analyses developed in the literature (first passage time, trajectory partitioning, etc.). Finally, this package also contains numerous examples of animal trajectories, and a working example illustrating the use of the package.
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paper_title: Modeling Moving Geospatial Objects from an Event-based Perspective

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In this paper, the dynamic happenings or occurrents experienced by entities in a geospatial domain, are modeled as events and from an analysis of these events, we show how meaningful information about the movement of objects can be abstracted. The semantics of moving objects are captured based on different events, for example, specialized events, such as departure, arrival, or unexpected destination events. The paper presents an approach for abstracting patterns of movement from event sequences based on key attributes: object identity, event description, and event location. A set of eight possible event pattern types are distinguished and discussed in the paper. From these patterns, three notable patterns of events are presented, i.e. identifiable trends of movement that are worthy of further attention or perhaps intervention. Two of these patterns, repeating and collocating, capture particular kinds of movement within a traversal or transit of a domain by a single moving object, such as a zigzag movement or reversal of direction, while a reiterating pattern of events corresponds to a movement pattern associated with multiple objects and describes, for example, convergence in a region. The inclusion of events in the data model provides a foundation for distinguishing particular semantics of movement based on patterns of events, providing a basis for querying different kinds of events as well as providing a foundation for developing automated event notification systems.
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paper_title: A Conceptual View on Trajectories ⋆

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Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an object). This paper explores how conceptual modeling could provide applications with direct support of trajectories (i.e. movement data that is structured into countable semantic units) as a first class concept. A specific concern is to allow enriching trajectories with semantic annotations allowing users to attach semantic data to specific parts of the trajectory. Building on a preliminary requirement analysis and an application example, the paper proposes two modeling approaches, one based on a design pattern, the other based on dedicated data types, and illustrates their differences in terms of implementation in an extended-relational context.
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paper_title: Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants

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Why study movement? data for measuring movement modelling movement building behaviourally based models analysis of movement paths mass mark-recapture individual mark-recapture. Appendix A: diffusion for ecologists.
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paper_title: A Field-Based Theory for Time Geography

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Classic time geography is powerful but rigid, admitting only uniform travel velocities. Computational time geographic methods that resolve the uniform velocity assumption through transportation networks or isochrones only partially address this weakness and do not have a rigorous theoretical foundation. This article develops an analytical time geographic theory for the case where travel velocities vary continuously across space. Using the continuous transportation or “urban fields” tradition in quantitative geography and regional science, this article formulates analytical definitions of the space–time path and prism for the case where unobserved components are characterized by minimum cost curves through an inverse velocity field rather than straight line segments through a uniform velocity plane. This provides a geometrically and visually oriented approach to capturing complex velocities that complements existing methods. Time geographic fields also generalize time geography as the classic and isochrone...
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paper_title: The space - time cube revisited from a geovisualization perspective

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At the end of the sixties Hagerstrand introduced a space-time model which included features such as a Space-TimePath, and a Space-Time-Prism. His model is often seen as the start of the time-geography studies. Throughout the years his model has been applied and improved to understand our movements through space. Problems studied can be found in different fields of geography, and range from those on an individual movement to whole theories to optimize transportation. From a visualization perspective the Space-Time-Cube was the most prominent element in Hagerstrand’s approach. In its basic appearance these images consist of a cube with on its base a representation of geography (along the x- and y-axis), while the cube’s height represents time (z-axis). A typical Space-Time-Cube could contain the space time-paths of for instance individuals or bus routes. However, when the concept was introduced the options to create the graphics were limited to manual methods and the user could only experience the single view created by the draftsperson. An alternative view on the cube would mean to go through a laborious drawing exercise. Today’s software has options to automatically create the cube and its contents from a database. Data acquisition of space-time paths for both individuals and groups is also made easier using GPS. Today, the user’s viewing environment is, by default, interactive and allows one to view the cube from any direction. In this paper an extended interactive and dynamic visualization environment is proposed, and demonstrated, in which the user has full flexibility to view, manipulate and query the data in a Space-Time-Cube. Included are options to move slider planes along each of the axes to for instance select, or highlight a period in time or location in space. Examples will be discussed in which the time axis is manipulated by for instance changing world time for event time (time cartograms). Creativity should not stop here since it has been shown that especially an alternative perspective on the data will sparkle the mind with new ideas. The user should be allowed to for instance let the x- and/or y-axis be represented by other variables of the theme studied. Since the cube is seen as an integral part of a geovisualization environment the option to link other views with other graphic representation does exist.
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paper_title: Time-geography – at the end of its beginning

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Let me start by presenting a short 'definition' of the main subject of this essay. Time-geography constitutes a foundation for a general geographical perspective. It represents a new structure of thought under development, which attempts to consolidate the spatial and temporal perspectives of different disciplines on a more solid basis than has thus far taken place. Time-geography is not a subject area per se, or a theory in its narrow sense, but rather an attempt to construct a broad structure of thought which may form a framework capable of fulfilling two tasks. The first is to receive and bring into contact knowledge from highly distinct scientific areas and from everyday praxis. The second is to reveal relations, the nature of which escape researchers as soon as the object of research is separated from its given milieu in order to study it in isolation, experimentally or in some other way distilled. This is a very unofficial and condensed version of the definition given by Torsten Hagerstrand many years ago. It is not very easy to grasp. But to me, it is an excellent and compact version of what time-geography really is. As a backdrop, I will use a 'map' as a frame of reference. I will use a straightforward metaphor life as a drama. Though simple, this is a rather useful starting point. Every drama has three elements namely actors, roles (expressed by behaviors, activities), and the scene. (In fact, life is a drama without any spectators: we are all taking part in the play and cannot analyze the course of events from the comfort of a seat in the audience.) I will not dwell on this metaphor but will move ahead to make some short (and perhaps obvious) remarks. The human actors without them, there will be no play can be observed physically and portrayed by a trajectory in a timegeographic notation as they move around saying and doing things. Their thoughts, their experiences, expectations, aims, etc., are not directly observable, however. What they are doing, their activities, derives from the various roles they try to play. Most of the social sciences are concerned with these roles and how they are created and developed. Roughly speaking, their development is a matter of common culture values, rules, institutional frameworks, power structures, etc. In short, roles express what is called the underlying structure (or structures). The scene is the sum of all physical objects like natural phenomena, lakes, mountains, minerals and all that human beings and societies make out of raw materials transforming them into buildings, roads, machines, tools, etc. To complete the scene, we must add the actors themselves, who are part of the physical scene. This is a brief and rough rendition of Popper and Eccles' division of our world into three parts: the physical world (the scene), our inner worlds (actors' images) and the cultural heritage (role-creating), which has been established in our physical world or perhaps just in our minds. (Actually, I prefer the drama metaphor, because it captures the dynamics in human lives and societies). The name of the game is integration. The point is to deal with all worlds together, because the triad is something that we have superimposed on reality to make it easier to tackle. Time-geography, as a foundation for a general (geographical) perspective, tries to bring all these worlds together into a common framework. Or to put it the other way around, time-geography tries to separate the three worlds as little as possible in the analytic process. In this essay, I will briefly characterize the main areas that time-geographic thought has penetrated over the years. I will use the metaphor 'life as a drama' and Popper's tripartite world as a frame to reference to describe the shifts in emphasis over time and how time-geography has been accepted or rejected. In the same vein, I will sketch the contours of the critique of the time-geographic approach. Finally, I will try to outline the prospects of current developments for the future.
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paper_title: Human Interaction Spaces Under Uncertainty

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Rigid activity schedules and pressure of time can strongly influence the determination of a meeting place and time. When several uncertain determinants need to be taken into account, joint activity planning becomes a complex issue. In this respect, a cross-pollination of Hagerstrand's time geography and Pawlak's rough set theory yields a fruitful foundation for analyzing multiple agents' travel spaces under uncertainty. This paper reports on an attempt to analyze the effects of uncertain spatiotemporal settings on the determination of interaction spaces. The aim is to provide a better understanding of the uncertainty component of constraints to support agents pointing out a feasible meeting place while respecting individuals' fixed activity programs. The concept of rough space-time prisms and their effect on current space-time accessibility measures is presented. The paper focuses on three types of uncertainty: temporal, spatial, and speed.
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paper_title: Time geography and wildlife home range delineation

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Funding for this work was provided by Canada’s Natural Science and Engineering Research Council (NSERC) and GEOIDE through the Government of Canada’s Networks of Centres of Excellence program.
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paper_title: Gis Software For Measuring Space-Time Accessibility In Transportation Planning And Analysis

paper_content:

Transportation systems exist to improve individual accessibility. However, emerging applications of GIS in transportation (GIS-T) and intelligent transportation system (ITS) focus on throughput (the amount of system flow) rather than accessibility. Throughput is related but not equivalent to accessibility. Sensitive transportation planning requires rigorous, realistic and tractable accessibility measures. This paper reports on the development of GIS software that implement space-time accessibility measures (STAMs). The STAMs reflect the benefits that individuals receive from the transportation system. They are easily interpreted, particularly with respect to changes in accessibility. The STAMs also consider the locations and travel velocities dictated by the transportation system as well as individuals’ daily activity schedules. Tractable computational procedures allow calculation of the STAMs for detailed, urban-scale transportation networks. A prototype ArcInfo^®-linked software system that runs on Windows NT^® or Sun Solaris^® platform implements the STAMs with user-friendly interfaces and project management tools.
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paper_title: Towards a probabilistic time geography

paper_content:

Time geography uses space-time volumes to represent the possible locations of a mobile agent over time in a x-y-t space. Space-time volumes are qualitative statements, enabling qualitative analysis. In this paper these statements will be quantified, modeling an agent's possible locations from a stochastic perspective. With such a model time geography can be improved in expressiveness as well as accuracy.
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paper_title: A measurement theory for time geography

paper_content:

Hagerstrand's time geography is a powerful conceptual framework for understanding constraints on human activity participation in space and time. However, rigorous, analytical definitions of basic time geography entities and relationships do not exist. This limits abilities to make statements about error and uncertainty in time geographic measurement and analysis. It also compromises comparison among different time geographic analyses and the development of standard time geographic computational tools. The time geographic measurement theory in this article consists of analytical formulations for basic time geography entities and relations, specifically, the space–time path, prism, composite path-prisms, stations, bundling, and intersections. The definitions have arbitrary spatial and temporal resolutions and are explicit with respect to informational assumptions: there are clear distinctions between measured and inferred components of each entity or relation. They are also general to n-dimensional space rather than the strict two-dimensional space of classical time geography. Algebraic solutions are available for one or two spatial dimensions, while numeric (but tractable) solutions are required for some entities and relations in higher dimensional space.
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paper_title: SPACE-TIME MODELING OF GRIZZLY BEARS*

paper_content:

ABSTRACT. An appropriate conceptual leap can be made from human geography to physical geography by applying space-time continuum modeling to zoogeomorphology--the alteration of the landscape by animals. Drawing on the work of Torsten Hagerstrand, we propose a space-time continuum model of grizzly bears, a geomorphic agent. Through both data-driven and conceptual applications, the model traces where and when grizzly bears are likely to wield a geomorphic impact. The model further demonstrates that geographers have much to gain by merging concepts from human and physical geography. Keywords: grizzly bears, time geography, zoogeomorphology. Many geographers assert that physical geography and human geography are deeply, inherently, and necessarily connected. Although their subject matter may appear different, an underlying rootedness in a geographical perspective remains true throughout the discipline. One way in which concepts from seemingly disparate ends of the discipline can and should be integrated is through the application of space-time continuum models. Space-time continuum modeling has proved useful in tracing people as they go through a day, a month, a year, or even a lifetime Hag 1967, 1982; Carlstein 1978). Ideally, everything that happens at particular moments in time, even the sound of a dog barking, can be introduced into a space-time continuum model (Hagerstrand 1982). Imagine taking the concept of space-time continuum modeling out of human geography and introducing it into physical geography--more specifically, into zoogeomorphology, or the alteration of the landscape by animals. Imagine studying the geomorphic impact of grizzly bears (Ursus arctos horribilis) by drawing on the work of Torsten Hagerstrand. Such an effort would integrate human and physical geography, and is the focus here. GRIZZLY BEARS Grizzly bears inhabit the mid-high latitudes of North America and Eurasia. Currently, fewer than 1,000 grizzlies live in the conterminous United States, existing in six ecosystems in the northwestern part of the country (Figure i). They are also found in Alaska and in ten ecosystems in Canada, four of which border on U.S. ecosystems. Before European contact grizzly bears occupied much larger tracts of land, including most of western and central North America, but their range diminished substantially as a result of Euro-American movement into the western United States and Canada (IGBC 1987). Adult grizzly bears weigh 160 kilograms or more and, when standing upright, are approximately 2 meters in height or taller (Butler 1992; McArthur n.d.) (Figure 2). Their massive size and potential for harming people pose a major safety concern for researchers and sightseers (Gunther and Hoekstra 1996). A large body of literature exists on the landscape ecology and habitat utilization of grizzly bears. However, the bulk of this work is in the framework of conservation biology and wildlife management rather than of physical geography (Servheen 1983; Butterfield and Key 1986; Hamer, Herrero, and Brady 1991; Mace and Waller 1998; Waller and Mace 1998; Mace and others 1999). Further contributions in geomorphology and biogeography can help strengthen the linkages between geography and other disciplines. In particular, research in zoogeomorphology builds on the human-land-interaction component of geography, a key ecological component of the discipline and one with firm links to conservation biology and environmental history. The zoogeomorphology of grizzly bears is significant because grizzlies can and do alter the landscape through activities such as denning, trampling, and digging for plants, insects, and animals (Butler 1992, 1995). Such activities occur at a variety of elevations, in different habitats, and during different seasons (Butterfield and Key 1986; Mace and Jonkel 1986). SEASONAL VARIATIONS IN GEOMORPHOLOGY During the early spring, after they have emerged from their winter dens, grizzlies dig for succulent tubers along riparian corridors, graze on grasses in low-altitude meadows, and search for carrion killed and deposited in valley bottoms by avalanches during the previous winter (Singer 1978; Mace and Bissell 1986; Butler 1995). …
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paper_title: Modelling accessibility using space-time prism concepts within geographical information systems.

paper_content:

Abstract The space-time Of time geographical framework is a powerful perspective from which to analyse human behaviour. One of the central concepts in this framework is the space-time prism, which models individual accessibility to an environment. In this paper, the derivation and manipulation of space-time prism concepts within a geographical information system (GIS) are discussed. The required system inputs and desired outputs are identified and a generic GIS based procedure is presented Given these basic requirements, issues are discussed which can determine the feasibility of current GIS technology to handle the derivation of space-time prism concepts.
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paper_title: Timing Space and Spacing Time

paper_content:

A plea is made for a chronosophical approach to the selection of dimensions of time which might be relevant to the description and explanation of urban processes. Following the definition of some basic terms and concepts which might be used in the future development of a notational schema, the paper considers some possibilities which are inherent in the idea of timing space. This is followed by similar consideration of the idea of spacing time. These themes are compounded in a simple example which suggests that fundamental ongoing processes in daily urban behaviour are usefully summarised by what we call the accordion effect. The final section proposes that new insights into the problem of evaluating the quality of life of urban residents are obtained when such an approach is taken.
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paper_title: WHAT ABOUT PEOPLE IN REGIONAL SCIENCE?

paper_content:

The described locking mechanism permits two or more rods to be quickly fitted together and adjusted to a fixed, predetermined length. The locking mechanism is of a type such that the rotation of the rods by approximately 45 DEG -90 DEG automatically fixes the rods in place.
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paper_title: Interpolating and Using Most Likely Trajectories in Moving-Objects Databases

paper_content:

In recent years, many emerging database applications deal with large sets of continuously moving data objects. Since no computer system can commit continuously occurring infinitesimal changes to the database, related data management techniques view a moving object's trajectory as a sequence of discretely reported spatiotemporal points. For each pair of consecutive committed trajectory points, a spatiotemporal uncertainty region representing all possible in-between trajectory points is defined. To support trajectory queries with a non-uniform probability distribution model, the query system needs to compute (interpolate) the most likely trajectories in the uncertainty regions to determine the peak points of the probability distributions. This paper proposes a generalized trajectory interpolation model using parametric trajectory representations. In addition, the paper expands and investigates three practical specializations of our proposed model using a moving object with momentum, i.e., a vehicle, as the exemplar.
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paper_title: How to reliably estimate the tortuosity of an animal's path: straightness, sinuosity, or fractal dimension?

paper_content:

The tortuosity of an animal's path is a key parameter in orientation and searching behaviours. The tortuosity of an oriented path is inversely related to the efficiency of the orientation mechanism involved, the best mechanism being assumed to allow the animal to reach its goal along a straight line movement. The tortuosity of a random search path controls the local searching intensity, allowing the animal to adjust its search effort to the local profitability of the environment. This paper shows that (1) the efficiency of an oriented path can be reliably estimated by a straightness index computed as the ratio between the distance from the starting point to the goal and the path length travelled to reach the goal, but such a simple index, ranging between 0 and 1, cannot be applied to random search paths; (2) the tortuosity of a random search path, ranging between straight line movement and Brownian motion, can be reliably estimated by a sinuosity index which combines the mean cosine of changes of direction with the mean step length; and (3) in the current state of the art, the fractal analysis of animals' paths, which may appear as an alternative and promising way to measure the tortuosity of a random search path as a fractal dimension ranging between 1 (straight line movement) and 2 (Brownian motion), is only liable to generate artifactual results. This paper also provides some help for distinguishing between oriented and random search paths, and depicts a general, comprehensive framework for analysing individual animals' paths in a two-dimensional space.
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paper_title: Analyzing insect movement as a correlated random walk

paper_content:

This paper develops a procedure for quantifying movement sequences in terms of move length and turning angle probability distributions. By assuming that movement is a correlated random walk, we derive a formula that relates expected square displacements to the number of consecutive moves. We show this displacement formula can be used to highlight the consequences of different searching behaviors (i.e. different probability distributions of turning angles or move lengths). Observations of Pieris rapae (cabbage white butterfly) flight and Battus philenor (pipe-vine swallowtail) crawling are analyzed as a correlated random walk. The formula that we derive aptly predicts that net displacements of ovipositing cabbage white butterflies. In other circumstances, however, net displacements are not well-described by our correlated random walk formula; in these examples movement must represent a more complicated process than a simple correlated random walk. We suggest that progress might be made by analyzing these more complicated cases in terms of higher order markov processes.
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paper_title: Lévy flight search patterns of wandering albatrosses

paper_content:

LeVY flights are a special class of random walks whose step lengths are not constant but rather are chosen from a probability distribution with a power-law tail. Realizations of Levy flights in physical phenomena are very diverse, examples including fluid dynamics, dynamical systems, and micelles1,2. This diversity raises the possibility that Levy flights may be found in biological systems. A decade ago, it was proposed that Levy flights may be observed in the behaviour of foraging ants3. Recently, it was argued that Drosophila might perform Levy flights4, but the hypothesis that foraging animals in natural environments perform Levy flights has not been tested. Here we study the foraging behaviour of the wandering albatross Diomedea exulans, and find a power-law distribution of flight-time intervals. We interpret our finding of temporal scale invariance in terms of a scale-invariant spatial distribution of food on the ocean surface. Finally, we examine the significance of our finding in relation to the basis of scale-invariant phenomena observed in biological systems.
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paper_title: Towards a taxonomy of movement patterns

paper_content:

Areview of research that has been carried out on data mining and visual analysis of movement patterns suggests that there is little agreement on the relevant types of movement patterns and only few, isolated definitions of these exist. Since the research interest in this area has recently started to soar. we believe that this is a good time to approach the definition of movement patterns in a more systematic and comprehensive way. This paper intends to contribute to the development of a toolbox of data mining algorithms and visual analytic techniques for movement analysis by developing firstly a conceptual framework for movement behavior of different moving objects and secondly a comprehensive classification and review of movement patterns. We argue that this is indispensable as a basis for the development of pattern recognition and information visualization algorithms that are required to be efficient (i.e. usable on massive data sets), effective (i.e. capable of accurately detecting patterns not artifacts), and as generic as possible (i.e. potentially applicable to different types of movement data). We demonstrate the utilization of our classification by answering the question as to what extent eye tracking data can be seen as a proxy of other types of movement data. We have set up a moderated discussion platform in order to facilitate the further evolution of our proposed classification towards a consolidated taxonomy in a consensus process.
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paper_title: Using fractal dimensions for characterizing tortuosity of animal trails

paper_content:

. The tortuosity of mite trails was characterized by their fractal dimension, which is the non-Euclidean dimension varying between 1 (completely straight) and 2 (so tortuous that the complete two-dimensional space is used). This index was shown to be a good, discriminative index for mite trails, which is a completely new use of the fractal dimension. The value of this index is compared with other tortuosity indices.
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paper_title: Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants

paper_content:

Why study movement? data for measuring movement modelling movement building behaviourally based models analysis of movement paths mass mark-recapture individual mark-recapture. Appendix A: diffusion for ecologists.
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paper_title: A modified Hausdorff distance based algorithm for 2-dimensional spatial trajectory matching

paper_content:

With the development of mobile technology, Internet and GIS, LBS plays an important role in various applications. As the basis of LBS, the research on acquisition, processing, storage, query of mobile object trajectories has been quite mature, but the analysis and the application of movement patterns contained in mobile object trajectories is relatively lagging behind. The calculation of trajectory similarity is the key area for mobile object trajectories data mining, and the similarity algorithm based on Hausdorff distance is one of the major algorithms. In this paper, we presents a modified Hausdorff distance (MHD) based algorithm for 2-dimensional trajectory matching in light of the problem of correlation algorithms which are based on Hausdorff distance. This algorithm uses interpolation algorithm to shield the impact to the distance between trajectories due to different position updating polices, sampling granularity, initial position and so on in Mobile Object Database (MOD). The experimental results show that the algorithm can better reflect the trajectory similarity between 2-dimensional mobile objects.
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paper_title: Comparison of Similarity Measures for Trajectory Clustering in Outdoor Surveillance Scenes

paper_content:

This paper compares different similarity measures used for trajectory clustering in outdoor surveillance scenes. Six similarity measures are presented and the performance is evaluated by Correct Clustering Rate (CCR) and Time Cost (TC). The experimental results demonstrate that in outdoor surveillance scenes, the simpler PCA+Euclidean distance is competent for the clustering task even in case of noise, as more complex similarity measures such as DTW, LCSS are not efficient due to their high computational cost .
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paper_title: Correlation Analysis of Discrete Motions

paper_content:

Points are dimensionless geometric elements often employed by geographic information systems to model a range of real-world objects such as people and vehicles. Many analytical tools have been developed for finding and validating certain patterns of static points such as clustering. In this paper, we present our preliminary efforts to develop statistical methods for analyzing patterns of moving points whose locations are tracked at equal intervals of time. Focus is placed on simple descriptive statistics—rather than more sophisticated inferential statistics—useful for detecting a tendency of two or more points to move in some coordinated fashion. A major implication of this paper is that statistical analysis complements spatial data query and modeling with respect to dynamics of sets of point-like objects in a way that potentially interrelated subsets are screened.
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paper_title: Learning Traffic Patterns at Intersections by Spectral Clustering of Motion Trajectories

paper_content:

We address the problem of automatically learning the layout of a traffic intersection from trajectories of vehicles obtained by a vision tracking system. We present a similarity measure which is suitable for use with spectral clustering in problems that emphasize spatial distinctions between vehicle trajectories. The robustness of the method to small perturbations and its sensitivity to the choice of parameters are evaluated using real-world data.
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paper_title: Comparing images using the hausdorff distance

paper_content:

The Hausdorff distance measures the extent to which each point of a model set lies near some point of an image set and vice versa. Thus, this distance can be used to determine the degree of resemblance between two objects that are superimposed on one another. Efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model are presented. The focus is primarily on the case in which the model is only allowed to translate with respect to the image. The techniques are extended to rigid motion. The Hausdorff distance computation differs from many other shape comparison methods in that no correspondence between the model and the image is derived. The method is quite tolerant of small position errors such as those that occur with edge detectors and other feature extraction methods. It is shown that the method extends naturally to the problem of comparing a portion of a model against an image. >
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paper_title: A Conceptual View on Trajectories ⋆

paper_content:

Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an object). This paper explores how conceptual modeling could provide applications with direct support of trajectories (i.e. movement data that is structured into countable semantic units) as a first class concept. A specific concern is to allow enriching trajectories with semantic annotations allowing users to attach semantic data to specific parts of the trajectory. Building on a preliminary requirement analysis and an application example, the paper proposes two modeling approaches, one based on a design pattern, the other based on dedicated data types, and illustrates their differences in terms of implementation in an extended-relational context.
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paper_title: Movement similarity assessment using symbolic representation of trajectories

paper_content:

This article describes a novel approach for finding similar trajectories, using trajectory segmentation based on movement parameters MPs such as speed, acceleration, or direction. First, a segmentation technique is applied to decompose trajectories into a set of segments with homogeneous characteristics with respect to a particular MP. Each segment is assigned to a movement parameter class MPC, representing the behavior of the MP. Accordingly, the segmentation procedure transforms a trajectory to a sequence of class labels, that is, a symbolic representation. A modified version of edit distance called normalized weighted edit distance NWED is introduced as a similarity measure between different sequences. As an application, we demonstrate how the method can be employed to cluster trajectories. The performance of the approach is assessed in two case studies using real movement datasets from two different application domains, namely, North Atlantic Hurricane trajectories and GPS tracks of couriers in London. Three different experiments have been conducted that respond to different facets of the proposed techniques and that compare our NWED measure to a related method.
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paper_title: Measuring similarity between geospatial lifelines in studies of environmental health

paper_content:

Many epidemiological studies involve analysis of clusters of diseases to infer locations of environmental hazards that could be responsible for the disease. This approach is however only suitable for sedentary populations or diseases with small latency periods. For migratory populations and diseases with long latency periods, people may change their residential location between time of exposure and onset of ill health. For such situations, clusters are diffused and diluted by in- and out-migration and may become very difficult to detect. One way to address the problem of diffused clusters is to include in analyses not only current residential locations, but all past locations at which cases might have been exposed to environmental hazardous. In this paper, we assume that a person’s residential history provides such information and represent it through a discrete geospatial lifeline data model. Clusters of similar geospatial lifelines represent individuals who have similar residential histories—and therefore represent people who are more likely to have had similar environmental exposure histories. We therefore introduce a lifeline distance (dissimilarity) measure to detect clusters of cases, providing a basis for revealing possible regions in space-time where environmental hazards might have existed in the past. The ability of the measure to distinguish cases from controls is tested using two sets of synthetically generated cases and controls. Results indicate that the measure is able to consistently distinguish between populations of cases and controls with statistically significant results. The lifeline distance measure consistently outperforms another measure which uses only the distance between subjects’ residences at time of diagnosis. However, the advantages of using the entire residential history are only partly realized, since the ability to distinguish between cases and controls is only moderately better for the lifeline distance function. Future work is needed to investigate modifications to the inter-lifeline distance measure in order to enhance the potential of this approach to detect locations of environmental hazards over the lifespan. Copyright Springer-Verlag Berlin Heidelberg 2005
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paper_title: Shape-Based Similarity Query for Trajectory of Mobile Objects

paper_content:

In this paper, we describe an efficient indexing method for a shape-based similarity search of the trajectory of dynamically changing locations of people and mobile objects. In order to manage trajectories in database systems, we define a data model of trajectories as directed lines in a space, and the similarity between trajectories is defined as the Euclidean distance between directed discrete lines. Our proposed similarity query can be used to find interested patterns embedded into the trajectories, for example, the trajectories of mobile cars in a city may include patterns for expecting traffic jams. Furthermore, we propose an efficient indexing method to retrieve similar trajectories for a query by combining a spatial indexing technique (R+-Tree) and a dimension reduction technique, which is called PAA (Piecewise Approximate Aggregate). The indexing method can efficiently retrieve trajectories whose shape in a space is similar to the shape of a candidate trajectory from the database.
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paper_title: Robust similarity measures for mobile object trajectories

paper_content:

We investigate techniques for similarity analysis of spatio-temporal trajectories for mobile objects. Such data may contain a large number of outliers, which degrade the performance of Euclidean and time warping distance. Therefore, we propose the use of non-metric distance functions based on the longest common subsequence (LCSS), in conjunction with a sigmoidal matching function. Finally, we compare these new methods to various L/sub p/ norms and also to time warping distance (for real and synthetic data) and present experimental results that validate the accuracy and efficiency of our approach, especially in the presence of noise.
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paper_title: Spatio-temporal similarity analysis between trajectories on road networks

paper_content:

In order to analyze the behavior of moving objects, a measure for determining the similarity of trajectories needs to be defined. Although research has been conducted that retrieved similar trajectories of moving objects in Euclidean space, very little research has been conducted on moving objects in the space defined by road networks. In terms of real applications, most moving objects are located in road network space rather than in Euclidean space. In this paper, we investigate the properties of similar trajectories in road network space. And we propose a method to retrieve similar trajectories based on this observation and similarity measure between trajectories on road network space. Experimental results show that this method provides not only a practical method for searching for similar trajectories but also a clustering method for trajectories.
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paper_title: Finding popular places

paper_content:

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. We investigate spatio-temporal movement patterns in large tracking data sets. Specifically we study so-called 'popular places', that is, regions that are visited by many entities. We present upper and lower bounds.
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paper_title: On discovering moving clusters in spatio-temporal data

paper_content:

A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars moving in a city, etc. We study the discovery of moving clusters in a database of object trajectories. The difference of this problem compared to clustering trajectories and mining movement patterns is that the identity of a moving cluster remains unchanged while its location and content may change over time. For example, while a group of animals are migrating, some animals may leave the group or new animals may enter it. We provide a formal definition for moving clusters and describe three algorithms for their automatic discovery: (i) a straight-forward method based on the definition, (ii) a more efficient method which avoids redundant checks and (iii) an approximate algorithm which trades accuracy for speed by borrowing ideas from the MPEG-2 video encoding. The experimental results demonstrate the efficiency of our techniques and their applicability to large spatio-temporal datasets.
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paper_title: Eigenbehaviors: identifying structure in routine

paper_content:

Longitudinal behavioral data generally contains a significant amount of structure. In this work, we identify the structure inherent in daily behavior with models that can accurately analyze, predict, and cluster multimodal data from individuals and communities within the social network of a population. We represent this behavioral structure by the principal components of the complete behavioral dataset, a set of characteristic vectors we have termed eigenbehaviors. In our model, an individual’s behavior over a specific day can be approximated by a weighted sum of his or her primary eigenbehaviors. When these weights are calculated halfway through a day, they can be used to predict the day’s remaining behaviors with 79% accuracy for our test subjects. Additionally, we demonstrate the potential for this dimensionality reduction technique to infer community affiliations within the subjects’ social network by clustering individuals into a “behavior space” spanned by a set of their aggregate eigenbehaviors. These behavior spaces make it possible to determine the behavioral similarity between both individuals and groups, enabling 96% classification accuracy of community affiliations within the population-level social network. Additionally, the distance between individuals in the behavior space can be used as an estimate for relational ties such as friendship, suggesting strong behavioral homophily amongst the subjects. This approach capitalizes on the large amount of rich data previously captured during the Reality Mining study from mobile phones continuously logging location, proximate phones, and communication of 100 subjects at MIT over the course of 9 months. As wearable sensors continue to generate these types of rich, longitudinal datasets, dimensionality reduction techniques such as eigenbehaviors will play an increasingly important role in behavioral research.
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paper_title: Modeling Moving Geospatial Objects from an Event-based Perspective

paper_content:

In this paper, the dynamic happenings or occurrents experienced by entities in a geospatial domain, are modeled as events and from an analysis of these events, we show how meaningful information about the movement of objects can be abstracted. The semantics of moving objects are captured based on different events, for example, specialized events, such as departure, arrival, or unexpected destination events. The paper presents an approach for abstracting patterns of movement from event sequences based on key attributes: object identity, event description, and event location. A set of eight possible event pattern types are distinguished and discussed in the paper. From these patterns, three notable patterns of events are presented, i.e. identifiable trends of movement that are worthy of further attention or perhaps intervention. Two of these patterns, repeating and collocating, capture particular kinds of movement within a traversal or transit of a domain by a single moving object, such as a zigzag movement or reversal of direction, while a reiterating pattern of events corresponds to a movement pattern associated with multiple objects and describes, for example, convergence in a region. The inclusion of events in the data model provides a foundation for distinguishing particular semantics of movement based on patterns of events, providing a basis for querying different kinds of events as well as providing a foundation for developing automated event notification systems.
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paper_title: Efficient k-nearest neighbor search on moving object trajectories

paper_content:

With the growing number of mobile applications, data analysis on large sets of historical moving objects trajectories becomes increasingly important. Nearest neighbor search is a fundamental problem in spatial and spatio-temporal databases. In this paper, we consider the following problem: Given a set of moving object trajectories D and a query trajectory mq, find the k nearest neighbors to mq within D for any instant of time within the lifetime of mq. We assume D is indexed in a 3D-R-tree and employ a filter-and-refine strategy. The filter step traverses the index and creates a stream of so-called units (linear pieces of a trajectory) as a superset of the units required to build the result of the query. The refinement step processes an ordered stream of units and determines the pieces of units forming the precise result. To support the filter step, for each node p of the index, in preprocessing a time-dependent coverage function C p (t) is computed which is the number of trajectories represented in p present at time t. Within the filter step, sophisticated data structures are used to keep track of the aggregated coverages of the nodes seen so far in the index traversal to enable pruning. Moreover, the R-tree index is built in a special way to obtain coverage functions that are effective for pruning. As a result, one obtains a highly efficient kNN algorithm for moving data and query points that outperforms the two competing algorithms by a wide margin. Implementations of the new algorithms and of the competing techniques are made available as well. Algorithms can be used in a system context including, for example, visualization and animation of results. Experiments of the paper can be easily checked or repeated, and new experiments be performed.
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paper_title: Trajectory pattern mining

paper_content:

The increasing pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) is leading to the collection of large spatio-temporal datasets and to the opportunity of discovering usable knowledge about movement behaviour, which fosters novel applications and services. In this paper, we move towards this direction and develop an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects. We introduce trajectory patterns as concise descriptions of frequent behaviours, in terms of both space (i.e., the regions of space visited during movements) and time (i.e., the duration of movements). In this setting, we provide a general formal statement of the novel mining problem and then study several different instantiations of different complexity. The various approaches are then empirically evaluated over real data and synthetic benchmarks, comparing their strengths and weaknesses.
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paper_title: Sequence Alignment as a Method for Human Activity Analysis in Space and Time

paper_content:

Abstract This article introduces the method of sequence alignment as a tool for analyzing the sequential aspects within the temporal and spatial dimensions of human activities. Sequence alignment was first developed during the 1980s and employed by biochemists to analyze DNA sequences. Toward the end of the 1990s it was adapted for use in the social sciences. However, unlike other social sciences practitioners, geographers have not, until now, exploited this method. In contrast to traditional quantitative methods, sequence alignment, as its name suggests, is directly concerned with the order (sequence) of events, and is therefore well suited for the pursuit of time-geographic research. To demonstrate the merits of sequence alignment for geographic research, a database composed of forty space-time sequences of visitors who had visited the Old City of Akko (Israel) was used. The sequences were obtained by means of GPS devices, which were distributed among the visitors tracked and which they operated for the...
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paper_title: A Conceptual View on Trajectories ⋆

paper_content:

Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an object). This paper explores how conceptual modeling could provide applications with direct support of trajectories (i.e. movement data that is structured into countable semantic units) as a first class concept. A specific concern is to allow enriching trajectories with semantic annotations allowing users to attach semantic data to specific parts of the trajectory. Building on a preliminary requirement analysis and an application example, the paper proposes two modeling approaches, one based on a design pattern, the other based on dedicated data types, and illustrates their differences in terms of implementation in an extended-relational context.
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paper_title: Mining spatio-temporal patterns in object mobility databases

paper_content:

With the increasing use of wireless communication devices and the ability to track people and objects cheaply and easily, the amount of spatio-temporal data is growing substantially. Many of these applications cannot easily locate the exact position of objects, but they can determine the region in which each object is contained. Furthermore, the regions are fixed and may vary greatly in size. Examples include mobile/cell phone networks, RFID tag readers and satellite tracking. This demands techniques to mine such data. These techniques must also correct for the bias produced by different sized regions. We provide a comprehensive definition of Spatio-Temporal Association Rules (STARs) that describe how objects move between regions over time. We also present other patterns that are useful for mobility data; stationary regions and high traffic regions. The latter consists of sources, sinks and thoroughfares. These patterns describe important temporal characteristics of regions and we show that they can be considered as special STARs. We define spatial support to effectively deal with the problem of different sized regions. We provide an efficient algorithm--STAR-Miner--to find these patterns by exploiting several pruning properties.
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paper_title: A foundation for representing and querying moving objects

paper_content:

Spatio-temporal databases deal with geometries changing over time. The goal of our work is to provide a DBMS data model and query language capable of handling such time-dependent geometries, including those changing continuously that describe moving objects . Two fundamental abstractions are moving point and moving region , describing objects for which only the time-dependent position, or position and extent, respectively, are of interest. We propose to present such time-dependent geometries as attribute data types with suitable operations, that is, to provide an abstract data type extension to a DBMS data model and query language. This paper presents a design of such a system of abstract data types. It turns out that besides the main types of interest, moving point and moving region, a relatively large number of auxiliary data types are needed. For example, one needs a line type to represent the projection of a moving point into the plane, or a “moving real” to represent the time-dependent distance of two points. It then becomes crucial to achieve (i) orthogonality in the design of the system, i.e., type constructors can be applied unifomly; (ii) genericity and consistency of operations, i.e., operations range over as many types as possible and behave consistently; and (iii) closure and consistency between structure and operations of nontemporal and related temporal types. Satisfying these goal leads to a simple and expressive system of abstract data types that may be integrated into a query language to yield a powerful language for querying spatio-temporal data, including moving objects. The paper formally defines the types and operations, offers detailed insight into the considerations that went into the design, and exemplifies the use of the abstract data types using SQL. The paper offers a precise and conceptually clean foundation for implementing a spatio-temporal DBMS extension.
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paper_title: Novel Approaches to the Indexing of Moving Object Trajectories

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The domain of spatiotemporal applications is a treasure trove of new types of data and queries. However, work in this area is guided by related research from the spatial and temporal domains, so far, with little attention towards the true nature of spatiotemporal phenomena. In this work, the focus is on a spatiotemporal sub-domain, namely the trajectories of moving point objects. We present new types of spatiotemporal queries, as well as algorithms to process those. Further, we introduce two access methods this kind of data, namely the Spatio-Temporal R-tree (STR-tree) and the Trajectory-Bundle tree (TB-tree). The former is an R-tree based access method that considers the trajectory identity in the index as well, while the latter is a hybrid structure, which preserves trajectories as well as allows for R-tree typical range search in the data. We present performance studies that compare the two indices with the R-tree (appropriately modified, for a fair comparison) under a varying set of spatiotemporal queries, and we provide guidelines for a successful choice among them.
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paper_title: Statistical Analysis Of Spatial Point Patterns

paper_content:

A spatial point pattern is a set of data consisting of a map of points. These points might represent, for example, cases of a disease in a human or animal population, or trees in a forest, or cells in a microscopic tissue section. This book provides an introduction to statistical methods for analysing data in the form of spatial point distributions. Theoretical results are described in intuitive terms and statistical methods are illustrated by many applications to real data drawn from the biological and biomedical sciences.
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paper_title: Evolution of clusters in dynamic point patterns: with a case study of Ants' simulation

paper_content:

Recent developments in sensing and tracking technologies have enabled large geographical databases to be established that represent spatial dynamics of 'behavioral entities'. Within this type of dynamics there are several levels and modes of organization that need to be revealed. Clusters are high-level groupings of entities, where change in their location and form, including split and merge events, represents self-organization and functioning patterns. Such information may contribute for better understanding spatially complex dynamic patterns. The main objective of this article is to develop an adaptable methodology that facilitates exploration of spatial order and processes in point pattern dynamics. The approach presented here utilizes data-clustering at each snapshot of the moving pattern, and then involves pairwise linking between the clusters identified at each snapshot and those identified in the following snapshot. Such linking is based on a new methodology that defines well globally optimized solutions for numerous possible linking combinations based on Linear Programming. A preliminary assessment of the approach was conducted with an existing Ants' simulation tool, capable of creating data sets covering in detail a substantial portion of the nest's life cycle.
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paper_title: A clustering-based approach for discovering interesting places in trajectories

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Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which the background geographic information is integrated to trajectory sample points. In this new concept, trajectories are observed as a set of stops and moves, where stops are the most important parts of the trajectory. Stops and moves have been computed by testing the intersections of trajectories with a set of geographic objects given by the user. In this paper we present an alternative solution with the capability of finding interesting places that are not expected by the user. The proposed solution is a spatio-temporal clustering method, based on speed, to work with single trajectories. We compare the two different approaches with experiments on real data and show that the computation of stops using the concept of speed can be interesting for several applications.
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paper_title: Time-focused clustering of trajectories of moving objects

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Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future, due to both technological and social/commercial reasons. From the data mining viewpoint, spatio-temporal trajectory data introduce new dimensions and, correspondingly, novel issues in performing the analysis tasks. In this paper, we consider the clustering problem applied to the trajectory data domain. In particular, we propose an adaptation of a density-based clustering algorithm to trajectory data based on a simple notion of distance between trajectories. Then, a set of experiments on synthesized data is performed in order to test the algorithm and to compare it with other standard clustering approaches. Finally, a new approach to the trajectory clustering problem, called temporal focussing, is sketched, having the aim of exploiting the intrinsic semantics of the temporal dimension to improve the quality of trajectory clustering.
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paper_title: Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases

paper_content:

As mobile devices proliferate and networks become more location-aware, the corresponding growth in spatio-temporal data will demand analysis techniques to mine patterns that take into account the semantics of such data. Association Rule Mining has been one of the more extensively studied data mining techniques, but it considers discrete transactional data (supermarket or sequential). Most attempts to apply this technique to spatial-temporal domains maps the data to transactions, thus losing the spatio-temporal characteristics. We provide a comprehensive definition of spatio-temporal association rules (STARs) that describe how objects move between regions over time. We define support in the spatio-temporal domain to effectively deal with the semantics of such data. We also introduce other patterns that are useful for mobility data; stationary regions and high traffic regions. The latter consists of sources, sinks and thoroughfares. These patterns describe important temporal characteristics of regions and we show that they can be considered as special STARs. We provide efficient algorithms to find these patterns by exploiting several pruning properties.
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paper_title: Algorithms for constrained k-nearest neighbor queries over moving object trajectories

paper_content:

An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (CkNN) queries and historical continuous CkNN (HCCkNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a CkNN query over trajectories retrieves from D within T, the k (? 1) trajectories that lie closest to q and intersect (or are enclosed by) CR; and (ii) an HCCkNN query on trajectories retrieves the constrained k nearest neighbors (CkNNs) of q at any time instance of T. We propose a suite of algorithms for processing CkNN queries and HCCkNN queries respectively, with different properties and advantages. In particular, we thoroughly investigate two types of CkNN queries, i.e., CkNNP and CkNNT, which are defined with respect to stationary query points and moving query trajectories, respectively; and two types of HCCkNN queries, namely, HCCkNNP and HCCkNNT, which are continuous counterparts of CkNNP and CkNNT, respectively. Our methods utilize an existing data-partitioning index for trajectory data (i.e., TB-tree) to achieve low I/O and CPU cost. Extensive experiments with both real and synthetic datasets demonstrate the performance of the proposed algorithms in terms of efficiency and scalability.
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paper_title: Seasonal tourism spaces in Estonia: Case study with mobile positioning data

paper_content:

Abstract The study analysed the seasonality of foreign tourists’ space consumption in Estonia using mobile positioning dataset with anonymous roaming data. The method which uses mobile phone positioning coordinates in space–time movement studies in Estonia is called the social positioning method. The dataset allowed analysis of the distribution of foreigners’ country of origin in Estonia with the precision of network cells of mobile operators. Privacy of mobile phone holders was guaranteed according to EU regulation. It was concluded that seasonality produces very different and sometimes even opposite tourists’ space consumption patterns in Estonia. Coastal areas are popular for summer tourism and not so popular in winter; continental inland areas were used more for winter tourism. The popular summer tourism areas along the Baltic Sea beaches are dominated by one nationality: the Finnish in western Estonia, and the Russians in eastern Estonia. Latvians made up a higher percentage in Saaremaa and Parnu during summer and in Otepaa and Lake Peipsi in winter. The mobile positioning data have great potential for tourism studies and monitoring, but is a sensitive issue due to the fear of surveillance.
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paper_title: Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases

paper_content:

Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as 3-D (2-D space+time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for spatial databases. The paper explains the approach and discusses several fundamental issues and questions related to it that need to be clarified before delving into specific designs of spatio- temporal algebras.
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paper_title: Efficient Detection of Patterns in 2D Trajectories of Moving Points

paper_content:

Moving point object data can be analyzed through the discovery of patterns in trajectories. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined by Laube et al., Finding REMO--detecting relative motion patterns in geospatial lifelines, 201---214, (2004). These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction, heading for the same location, and/or proximity. By the use of techniques from computational geometry, including approximation algorithms, we improve the running time bounds of existing algorithms to detect these patterns.
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paper_title: Interpolation of animal tracking data in a fluid environment

paper_content:

Interpolation of geolocation or Argos tracking data is a necessity for habitat use analyses of marine vertebrates. In a fluid marine environment, characterized by curvilinear structures, linearly interpolated track data are not realistic. Based on these two facts, we interpolated tracking data from albatrosses, penguins, boobies, sea lions, fur seals and elephant seals using six mathematical algorithms. Given their popularity in mathematical computing, we chose Bézier, hermite and cubic splines, in addition to a commonly used linear algorithm to interpolate data. Performance of interpolation methods was compared with different temporal resolutions representative of the less-precise geolocation and the more-precise Argos tracking techniques. Parameters from interpolated sub-sampled tracks were compared with those obtained from intact tracks. Average accuracy of the interpolated location was not affected by the interpolation method and was always within the precision of the tracking technique used. However, depending on the species tested, some curvilinear interpolation algorithms produced greater occurrences of more accurate locations, compared with the linear interpolation method. Total track lengths were consistently underestimated but were always more accurate using curvilinear interpolation than linear interpolation. Curvilinear algorithms are safe to use because accuracy, shape and length of the tracks are either not different or are slightly enhanced and because analyses always remain conservative. The choice of the curvilinear algorithm does not affect the resulting track dramatically so it should not preclude their use. We thus recommend using curvilinear interpolation techniques because of the more realistic fluid movements of animals. We also provide some guidelines for choosing an algorithm that is most likely to maximize track quality for different types of marine vertebrates.
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paper_title: Reporting flock patterns

paper_content:

Data representing moving objects is rapidly getting more available, especially in the area of wildlife GPS tracking. It is a central belief that information is hidden in large data sets in the form of interesting patterns, where a pattern can be any configuration of some moving objects in a certain area and/or during a certain time period. One of the most common spatio-temporal patterns sought after is flocks. A flock is a large enough subset of objects moving along paths close to each other for a certain pre-defined time. We give a new definition that we argue is more realistic than the previous ones, and by the use of techniques from computational geometry we present fast algorithms to detect and report flocks. The algorithms are analysed both theoretically and experimentally.
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paper_title: A Relative Representation of Trajectories in Geogaphical Spaces

paper_content:

The research presented in this paper introduces a relative representation of trajectories in space and time. The objective is to represent space the way it is perceived by a moving observer acting in the environment, and to provide a complementary view to the usual absolute vision of space. Trajectories are characterized from the perception of a moving observer where relative positions and relative velocities are the basic primitives. This allows for a formal identification of elementary trajectory configurations, and their relationships with the regions that compose the environment. The properties of the model are studied, including transitions and composition tables. These properties characterize trajectory transitions by the underlying processes that semantically qualify them. The approach provides a representation that might help the understanding of trajectory patterns in space and time.
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paper_title: Constrained free space diagrams: a tool for trajectory analysis

paper_content:

Time plays an important role in the analysis of moving object data. For many applications it is not sufficient to only compare objects at exactly the same times, or to consider only the geometry of their trajectories. We show how to leverage between these two approaches by extending a tool from curve analysis, namely the free space diagram. Our approach also allows us to take further attributes of the objects like speed or direction into account. We demonstrate the usefulness of the new tool by applying it to the problem of detecting single file movement. A single file is a set of moving entities, which are following each other, one behind the other. Our algorithm is the first one developed for detecting such movement patterns. For this application, we analyse demonstrate the performance of our tool both theoretically experimentally.
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paper_title: Reporting Leaders and Followers Among Trajectories of Moving Point Objects

paper_content:

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern `one object is leading others', which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.
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paper_title: Discovering relative motion patterns in groups of moving point objects

paper_content:

Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been impleme...
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paper_title: Finding REMO — Detecting Relative Motion Patterns in Geospatial Lifelines

paper_content:

Technological advances in position aware devices increase the availability of tracking data of everyday objects such as animals, vehicles, people or football players. We propose a geographic data mining approach to detect generic aggregation patterns such as flocking behaviour and convergence in geospatial lifeline data. Our approach considers the object’s motion properties in an analytical space as well as spatial constraints of the object’s lifelines in geographic space. We discuss the geometric properties of the formalised patterns with respect to their efficient computation.
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paper_title: A Field-Based Theory for Time Geography

paper_content:

Classic time geography is powerful but rigid, admitting only uniform travel velocities. Computational time geographic methods that resolve the uniform velocity assumption through transportation networks or isochrones only partially address this weakness and do not have a rigorous theoretical foundation. This article develops an analytical time geographic theory for the case where travel velocities vary continuously across space. Using the continuous transportation or “urban fields” tradition in quantitative geography and regional science, this article formulates analytical definitions of the space–time path and prism for the case where unobserved components are characterized by minimum cost curves through an inverse velocity field rather than straight line segments through a uniform velocity plane. This provides a geometrically and visually oriented approach to capturing complex velocities that complements existing methods. Time geographic fields also generalize time geography as the classic and isochrone...
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paper_title: Network Density Estimation: A GIS Approach for Analysing Point Patterns in a Network Space

paper_content:

Human activities and more generally the phenomena related to human behaviour take place in a network-constrained subset of the geographical space. These phenomena can be expressed as locations having their positions configured by a road network, as address points with street numbers. Although these events are considered as points on a network, point pattern analysis and the techniques implemented in a GIS environment generally consider events as taking place in a uniform space, with distance expressed as Euclidean and over a homogeneous and isotropic space. Network-spatial analysis has developed as a research agenda where the attention is drawn towards point pattern analytical techniques applied to a space constrained by a road network. Little attention has been put on first order properties of a point pattern (i.e. density) in a network space, while mainly second order analysis such as nearest neighbour and K -functions have been implemented for network configurations of the geographical space. In this article, a method for examining clusters of human-related events on a network, called Network Density Estimation (NDE), is implemented using spatial statistical tools and GIS packages. The method is presented and compared to conventional first order spatial analytical techniques such as Kernel Density Estimation (KDE). Network Density Estimation is tested using the locations of a sample of central, urban activities associated with bank and insurance company branches in the central areas of two midsize European cities, Trieste (Italy) and Swindon (UK).
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paper_title: Are kernels the mustard? Data from global positioning system (GPS) collars suggests problems for kernel home-range analyses with least-squares cross-validation

paper_content:

1. Kernel-density estimation (KDE) is one of the most widely used home-range estimators in ecology. The recommended implementation uses least squares cross-validation (LSCV) to calculate the smoothing factor (h) which has a considerable influence on the home-range estimate. 2. We tested the performance of least squares cross-validated kernel-density estimation (LSCV KDE) using data from global positioning system (GPS)-collared lions subsampled to simulate the effects of hypothetical radio-tracking strategies. 3. LSCV produced variable results and a 7% failure rate for fewer than 100 locations (H = 2069) and a 61% failure rate above 100 points (n = 1220). Patterns of failure and variation were not consistent among lions, reflecting different individual space use patterns. 4. Intensive use of core areas and site fidelity by animals caused LSCV to fail more often than anticipated from studies that used computer-simulated data. 5. LSCV failures at large sample sizes and variation at small sample sizes, limits the applicability of LSCV KDE to fewer situations than the literature suggests, and casts doubts over the method's reliability and comparability as a home-range estimator. © 2005 British Ecological Society.
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paper_title: Time-geographic density estimation for moving point objects

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This research presents a time-geographic method of density estimation for moving point objects. The approach integrates traditional kernel density estimation (KDE) with techniques of time geography to generate a continuous intensity surface that characterises the spatial distribution of a moving object over a fixed time frame. This task is accomplished by computing density estimates as a function of a geo-ellipse generated for each consecutive pair of control points in the object's space-time path and summing those values at each location in a manner similar to KDE. The main advantages of this approach are: (1) that positive intensities are only assigned to locations within a moving object's potential path area and (2) that it avoids arbitrary parameter selection as the amount of smoothing is controlled by the object's maximum potential velocity. The time-geographic density estimation technique is illustrated with a sample dataset, and a discussion of limitations and future work is provided.
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paper_title: Towards a probabilistic time geography

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Time geography uses space-time volumes to represent the possible locations of a mobile agent over time in a x-y-t space. Space-time volumes are qualitative statements, enabling qualitative analysis. In this paper these statements will be quantified, modeling an agent's possible locations from a stochastic perspective. With such a model time geography can be improved in expressiveness as well as accuracy.
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paper_title: Directed movements in probabilistic time geography

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This article studies probabilistic time geography for space-time prisms, that is, for situations where observers know the location of an agent at one time and then again at another time. In the intervening period, the agent would have moved freely, according to its time budget. The article demonstrates that the probability of finding the agent somewhere in the space-time prism is not equally distributed, so any attempt of a quantitative time geographic analysis must consider the actual probability distribution. This article develops, implements, and demonstrates this distribution. A preceding article introduced probabilistic time geography for space-time cones. With cones and prisms, the elementary space-time volumes of time geography are provided.
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paper_title: Density estimation for statistics and data analysis

paper_content:

Introduction. Survey of Existing Methods. The Kernel Method for Univariate Data. The Kernel Method for Multivariate Data. Three Important Methods. Density Estimation in Action.
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paper_title: Measurement of non-circular home range.

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Abstract We examine the use of conventional sampling data to estimate the area extent of an animal's home range. Popular methods of estimation based on polygons and capture radii are discussed. A simple example shows they are not directly comparable. Furthermore, when home ranges lack circular symmetry, methods based on capture radii suffer large biases. On the other hand, methods based on polygons have sample size biases. A new method, based on the determinant of the covariance matrix of the capture points, is introduced. We show that this method, under specified assumptions, is free from both forms of bias. Tables that identify the biases in the polygon methods are provided. An important use of the tables, that of making comparisons between values obtained by the various methods of estimation, is illustrated. The statistical stability of each method is given by means of a table or formula for its relative variance as a function of sample size. Finally, the methods are evaluated. For purposes of estimating home range area, the determinant method is recommended, the old convex polygon method is defended, and the use of methods based on capture radii is discouraged.
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paper_title: An exploratory data analysis (EDA) of the paths of moving animals

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Abstract This work presents an exploratory data analysis of the trajectories of deer and elk moving about in the Starkey Experimental Forest and Range in eastern Oregon. The animals’ movements may be affected by habitat variables and the behavior of the other animals. In the work of this paper a stochastic differential equation-based model is developed in successive stages. Equations of motion are set down motivated by corresponding equations of physics. Functional parameters appearing in the equations are estimated nonparametrically and plots of vector fields of animal movements are prepared. Residuals are used to look for interactions amongst the movements of the animals. There are exploratory analyses of various sorts. Statistical inferences are based on Fourier transforms of the data, which are unequally spaced. The sections of the paper start with motivating quotes and aphorisms from the writings of John W. Tukey.
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paper_title: The Use Of Potential Functions In Modelling Animal Movement

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Potential functions are a physical science concept often used in modelling the motion of particles and planets. In the work of this paper potential function based models are considered for the movement of free-ranging elk in a large, fenced ex- perimental forest. Equations of motion are set down and the parameters involved are estimated nonparametrically. The question of whether a potential function is plausible for describing the elk motion is considered. The conclusion is that it is not possible to reject this hypothesis for the data set and estimates considered.
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paper_title: Space–time density of trajectories: exploring spatio-temporal patterns in movement data

paper_content:

Modern positioning and identification technologies enable tracking of almost any type of moving object. A remarkable amount of new trajectory data is thus available for the analysis of various phenomena. In cartography, a typical way to visualise and explore such data is to use a space-time cube, where trajectories are shown as 3D polylines through space and time. With increasingly large movement datasets becoming available, this type of display quickly becomes cluttered and unclear. In this article, we introduce the concept of 3D space-time density of trajectories to solve the problem of cluttering in the space-time cube. The space-time density is a generalisation of standard 2D kernel density around 2D point data into 3D density around 3D polyline data (i.e. trajectories). We present the algorithm for space-time density, test it on simulated data, show some basic visualisations of the resulting density volume and observe particular types of spatio-temporal patterns in the density that are specific to trajectory data. We also present an application to real-time movement data, that is, vessel movement trajectories acquired using the Automatic Identification System (AIS) equipment on ships in the Gulf of Finland. Finally, we consider the wider ramifications to spatial analysis of using this novel type of spatio-temporal visualisation.
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paper_title: A kernel density estimation method for networks, its computational method and a GIS‐based tool

paper_content:

We develop a kernel density estimation method for estimating the density of points on a network and implement the method in the GIS environment. This method could be applied to, for instance, finding 'hot spots' of traffic accidents, street crimes or leakages in gas and oil pipe lines. We first show that the application of the ordinary two-dimensional kernel method to density estimation on a network produces biased estimates. Second, we formulate a 'natural' extension of the univariate kernel method to density estimation on a network, and prove that its estimator is biased; in particular, it overestimates the densities around nodes. Third, we formulate an unbiased discontinuous kernel function on a network. Fourth, we formulate an unbiased continuous kernel function on a network. Fifth, we develop computational methods for these kernels and derive their computational complexity; and we also develop a plug-in tool for operating these methods in the GIS environment. Sixth, an application of the proposed methods to the density estimation of traffic accidents on streets is illustrated. Lastly, we summarize the major results and describe some suggestions for the practical use of the proposed methods.
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paper_title: A potential function approach to the flow of play in soccer

paper_content:

There is a growing literature on the statistical analysis of data from association-football/soccer games, seasons or groups of seasons. In contrast this paper is concerned with a single play, that is a sequence of successful passes. The play studied contained 25 passes and ended in a goal for Argentina in World Cup 2006. One question addressed is how to describe analytically the spatial-temporal movement of such a particular sequence of passes.The basic data are points in the plane, successively joined by straight lines. The resulting figure represents the trajectory of the moving soccer ball. The approach of this study is to develop a useful potential function, a concept arising from physics and engineering. In particular the potential function leads to a regression model that may be fit directly by linear least squares.The resulting potential function may be used for simple description, summary, comparison, simulation, prediction, model appraisal, bootstrapping, and employed for estimating quantities of interest. The purpose illustrated here is to simulate play in a game where the ball goes back and forth between two teams each having their own potential function.
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paper_title: Kernel Methods for Estimating the Utilization Distribution in Home-Range Studies

paper_content:

In this paper kernel methods for the nonparametric estimation of the utilization distribution from a random sample of locational observations made on an animal in its home range are described. They are of flexible form, thus can be used where simple parametric models are found to be inappropriate or difficult to specify. Two examples are given to illustrate the fixed and adaptive kernel approaches in data analysis and to compare the methods. Various choices for the smoothing parameter used in kernel methods are discussed. Since kernel methods give alternative approaches to the Anderson (1982) Fourier transform methods, some comparisons are made.
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paper_title: Statistical Analysis Of Spatial Point Patterns

paper_content:

A spatial point pattern is a set of data consisting of a map of points. These points might represent, for example, cases of a disease in a human or animal population, or trees in a forest, or cells in a microscopic tissue section. This book provides an introduction to statistical methods for analysing data in the form of spatial point distributions. Theoretical results are described in intuitive terms and statistical methods are illustrated by many applications to real data drawn from the biological and biomedical sciences.
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paper_title: Employing stochastic differential equations to model wildlife motion

paper_content:

The concern is with the properties of stochastic differential equations (SDEs) describing the motion of particles in 3 dimensional space, on the sphere or in the plane. There is consideration of the case where the drift function comes from a potential function. There is study of SDEs whose parameters are periodic in time. These are useful for incorporating circadian rhythm in the behavior. The cases of a seal in a frozen lake in Alaska, an elephant seal migrating a great distance in the Pacific Ocean and of a group of "free-ranging" elk in a reserve in Oregon are referred to. For the elk nonparametric estimates of the drift and variance terms of an SDE model are discussed and evaluated and the fit of the model assessed. One issue is how to include explanatories, beyond location and time, in the model. A number of questions motivated by the wildlife motion concerning diffusion processes of the type considered are posed at the end of the paper.
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paper_title: The home-range concept: are traditional estimators still relevant with modern telemetry technology?

paper_content:

Recent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.
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paper_title: Analysing space use patterns by Thiessen polygon and triangulated irregular network interpolation: a non-parametric method for processing telemetric animal fixes

paper_content:

This paper describes a new non-parametric model to estimate space use. We test the similarity in space use patterns between an artificially generated utilization distribution (Seaman- UD) and the model estimates for five different sample sizes. Three different test statistics (Kappa,gamma,Tc) reveal a high similarity between the estimates and the Seaman-UD. The tests also show that, beyond a certain threshold value, larger sample sizes do not return significantly better results. W e further demonstrate that the Thiessen model delineated areas of intensive use more effectively in a home range than Kernel estimators. UD estimation uses AML (ArcInfo Macro Language), thus facilitating overlay operations with habitat information stored in the same ArcInfo GIS environment.
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paper_title: A Critical Review of Home Range Studies

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Abstract No consensus currently exists for the methods of estimation of home range size or for reporting home-range analysis results. Studies currently employ a variety of disparate methods or provide inadequate information for reproducing their analyses. We reviewed 161 home range studies published in 2004, 2005, and 2006 to assess what methods are currently employed and how results are reported. We found that home range reporting was generally inadequate for reproducing studies; that the methods employed varied considerably; that home range estimates were often reported and analyzed using inappropriate methods; and that many comparisons were made between studies that may produce spurious results. We urge for minimum editorial standards for reporting home range studies and we urge researchers to follow a unified methodology for estimating animal home ranges. We supply recommendations for such reporting and methodology. These recommendations will increase the reproducibility of studies and allow for more ...
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paper_title: A Characteristic-Hull Based Method for Home Range Estimation

paper_content:

Recent literature has reported inaccuracies associated with some popular home range estimators such as kernel density estimation, especially when applied to point patterns of complex shapes. This study explores the use of characteristic hull polygons (CHPs) as a new method of home range estimation. CHPs are special bounding polygons created in GIS that can have concave edges, be composed of disjoint regions, and contain areas of unoccupied space within their interiors. CHPs are created by constructing the Delaunay triangulation of a set of points and then removing a subset of the resulting triangles. Here, CHPs consisting of 95% of the smallest triangles, measured in terms of perimeter, are applied for home range estimation. First, CHPs are applied to simulated animal locational data conforming to five point pattern shapes at three sample sizes. Then, the method is applied to black-footed albatross (Phoebastria nigripes) locational data for illustration and comparison to other methods. For the simulated data, 95% CHPs produced unbiased home range estimates in terms of size for linear and disjoint point patterns and slight underestimates (8–20%) for perforated, concave, and convex ones. The estimated and known home ranges intersected one another by 72–96%, depending on shape and sample size, suggesting that the method has potential as a home range estimator. Additionally, the CHPs applied to estimate albatross home ranges illustrate how the method produces reasonable estimates for bird species that intensively forage in disjoint habitat patches.
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paper_title: Time geography and wildlife home range delineation

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Funding for this work was provided by Canada’s Natural Science and Engineering Research Council (NSERC) and GEOIDE through the Government of Canada’s Networks of Centres of Excellence program.
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paper_title: Space-Time and Integral Measures of Individual Accessibility: A Comparative Analysis Using a Point-based Framework

paper_content:

Conventional integral measures of accessibility, although valuable as indicators of place accessibility, have several limitations when used to evaluate individual accessibility. Two alternatives for overcoming some of the difficulties involved are explored in this study. One is to adapt these measures for evaluating individual accessibility using a disaggregate, nonzonal approach. The other is to develop different types of measures based on an alternative conceptual framework. To pursue the former alternative, this study specifies and examines eighteen gravity-type and cumulative-opportunity accessibility measures using a point-based spatial framework. For the latter option, twelve space-time accessibility measures are developed based on the construct of a prism-constrained feasible opportunity set. This paper compares the relationships and spatial patterns of these thirty measures using network-based GIS procedures. Travel diary data collected in Columbus, Ohio, and a digital data set of 10,727 selected land parcels are used for all computation. Results of this study indicate that space-time and integral indices are distinctive types of accessibility measures which reflect different dimensions of the accessibility experience of individuals. Since space-time measures are more capable of capturing interpersonal differences, especially the effect of space-time constraints, they are more “gender sensitive” and helpful for unraveling gender/ethnic differences in accessibility. An important methodological implication is that whether accessibility is observed to be important or different between individuals depends heavily on whether the measure used is capable of revealing the kind of differences the analyst intends to observe.
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paper_title: Application of GIS to investigate the use of space in coral reef fish: a comparison of territorial behaviour in two Red Sea butterflyfishes

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The space use of two coral‐feeding Red Sea butterflyfish species (Chaetodon austriacus and C. trifascialis) was studied at three sites in the Gulf of Aqaba to determine the extent of intraspecific territoriality. Individuals or pairs were observed in shallow water (<5 m). Their locations were recorded on maps of each study reef. The Animal Movement Analysis Extension (AMAE) in ArcView was used to plot territory borders and compute territory size for each species. Chaetodon austriacus, a generalist corallivore that exploited evenly distributed food resources, maintained small exclusive pair territories with clearly defined territory boundaries. In contrast, C. trifascialis, a specialist corallivore that exploited patchily distributed food resources, demonstrated considerable variation in territorial behaviour that ranged from the defence of small exclusive solitary territories to the shared use of a large home range. Comparisons of territory area estimates showed that 95% kernel probability density function territory boundaries matched intuitive territory boundaries and, unlike the minimum convex polygon area, did not contain obvious areas that were not used by individuals or pairs. We show that comparing different territory size measures can be very useful in describing subtle differences in territorial behaviour between species and studies. For this purpose, GIS is an ideal technology with which to carry out such analyses quickly and easily.
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paper_title: Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants

paper_content:

Why study movement? data for measuring movement modelling movement building behaviourally based models analysis of movement paths mass mark-recapture individual mark-recapture. Appendix A: diffusion for ecologists.
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paper_title: Harmonic Mean Measure of Animal Activity Areas

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A new method of calculating centers and areas of animal activity is presented based on the harmonic mean of an areal distribution. The center of activity is located in the area of greatest activity; in fact, more than one “center” may exist. The activity area isopleth is related directly to the frequency of occurrence of an individual within its home range. The calculation of home range allows for the heterogeneity of any habitat and is illustrated with data collected near Corvallis, Oregon, on the brush rabbit (Sylvilagus bachmani.)
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paper_title: A Framework For Temporal Geographic Information

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This paper defines the critical components of cartographic time and compares temporal and spatial topologies. Because time is topologically similar to space, spatial data structuring principles can be adapted to temporal data. We present three conceptualizations of temporal geographic information and select one as the most promising basis for a temporal geographic information system. This conceptualization creates a spatial composite of all geometric information (at all times), where each object has an attribute history distinct from that of its neighbors.
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paper_title: The space - time cube revisited from a geovisualization perspective

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At the end of the sixties Hagerstrand introduced a space-time model which included features such as a Space-TimePath, and a Space-Time-Prism. His model is often seen as the start of the time-geography studies. Throughout the years his model has been applied and improved to understand our movements through space. Problems studied can be found in different fields of geography, and range from those on an individual movement to whole theories to optimize transportation. From a visualization perspective the Space-Time-Cube was the most prominent element in Hagerstrand’s approach. In its basic appearance these images consist of a cube with on its base a representation of geography (along the x- and y-axis), while the cube’s height represents time (z-axis). A typical Space-Time-Cube could contain the space time-paths of for instance individuals or bus routes. However, when the concept was introduced the options to create the graphics were limited to manual methods and the user could only experience the single view created by the draftsperson. An alternative view on the cube would mean to go through a laborious drawing exercise. Today’s software has options to automatically create the cube and its contents from a database. Data acquisition of space-time paths for both individuals and groups is also made easier using GPS. Today, the user’s viewing environment is, by default, interactive and allows one to view the cube from any direction. In this paper an extended interactive and dynamic visualization environment is proposed, and demonstrated, in which the user has full flexibility to view, manipulate and query the data in a Space-Time-Cube. Included are options to move slider planes along each of the axes to for instance select, or highlight a period in time or location in space. Examples will be discussed in which the time axis is manipulated by for instance changing world time for event time (time cartograms). Creativity should not stop here since it has been shown that especially an alternative perspective on the data will sparkle the mind with new ideas. The user should be allowed to for instance let the x- and/or y-axis be represented by other variables of the theme studied. Since the cube is seen as an integral part of a geovisualization environment the option to link other views with other graphic representation does exist.
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paper_title: Impact of Data and Task Characteristics on Design of Spatio-Temporal Data Visualization Tools

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It is widely recognized that data visualization may be a powerful methodology for exploratory analysis. In order to fulfill this claim, visualization software must be carefully designed taking into account two principal aspects: characteristics of the data to be visualized and the exploratory tasks to be supported. The tasks that may potentially arise in data exploration are, in their turn, dependent on the data. In the chapter, we present visualization software tools for three different types of spatio-temporal data developed using a task-driven approach to design. We demonstrate that different exploratory tasks may be anticipated in these three cases and that different techniques are required to properly support exploration of the data. Prior to the consideration of the examples, we briefly describe the typologies of data and tasks we use in our work.
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paper_title: Designing visual analytics methods for massive collections of movement data

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Exploration and analysis of large data sets cannot be carried out using purely visual means but require the involvement of database technologies, computerized data processing, and computational analysis methods. An appropriate combination of these technologies and methods with visualization may facilitate synergetic work of computer and human whereby the unique capabilities of each “partner” can be utilized. We suggest a systematic approach to defining what methods and techniques, and what ways of linking them, can appropriately support such a work. The main idea is that software tools prepare and visualize the data so that the human analyst can detect various types of patterns by looking at the visual displays. To facilitate the detection of patterns, we must understand what types of patterns may exist in the data (or, more exactly, in the underlying phenomenon). This study focuses on data describing movements of multiple discrete entities that change their positions in space while preserving their integrity and identity. We define the possible types of patterns in such movement data on the basis of an abstract model of the data as a mathematical function that maps entities and times onto spatial positions. Then, we look for data transformations, computations, and visualization techniques that can facilitate the detection of these types of patterns and are suitable for very large data sets – possibly too large for a computer's memory. Under such constraints, visualization is applied to data that have previously been aggregated and generalized by means of database operations and/or computational techniques.
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paper_title: It's About Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems

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Abstract The study of spatiotemporal dynamics is certainly not new, nor is it unique to the field of geography. Nevertheless, addressing complex human and environmental issues such as global warming and human impacts on the environment requires empirical examination from a much broader and integrated perspective than can be accomplished with current techniques. Although Geographic Information Systems (GIS) are intended to provide an integrated and flexible tool for analyzing large volumes of data, they are historically geared toward the representation and analysis of situations frozen in time. Efforts to enhance the temporal capabilities of GIS have served to reveal many problems at a fundamental conceptual level. In order to address this problem, this paper presents a new Triad representational approach that unifies temporal-as well as locational-and object-related aspects and that incorporates concepts from perceptual psychology, artifical intelligence, and other fields. The goal of this research is a d...
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paper_title: Representations Of Space And Time

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Part I: Theories of World Knowledge Representation. Introduction to Part I. Representation versus Reality. Acquiring World Knowledge: The Overall Process. Storing World Knowledge: Some Elements of Conceptual Structure. Acquiring World Knowledge through Direct Experience. From Observation to Understanding. Acquiring Geographic Knowledge through Indirect Experience. How Spatial Knowledge is Encoded. Part II: The Computer as a Tool for Storing and Acquiring Spatial Knowledge. Introduction to Part II. The Computer as Medium. Storing Geographic Data. A New Perspective for Geographic Database Representation. Interacting with Databases. Issues for Implementing Advanced Geographic Databases. Epilogue: Moving Forward.
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paper_title: Cubic map algebra functions for spatio-temporal analysis

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We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimen- sional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nino/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.
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paper_title: A Space-Time GIS Approach to Exploring Large Individual-based Spatiotemporal Datasets

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The increasing number of large individual-based spatiotemporal datasets in various research fields has challenged the GIS community to develop analysis tools that can efficiently help researchers explore the datasets in order to uncover useful information. Rooted in Hagerstrand's time geography, this study presents a generalized space-time path (GSTP) approach to facilitating visualization and exploration of spatiotemporal changes among individuals in a large dataset. The fundamental idea of this approach is to derive a small number of representative space-time paths (i.e. GSTPs) from the raw dataset by identifying spatial cluster centers of observed individuals at different time periods and connecting them according to their temporal sequence. A space-time GIS environment is developed to implement the GSTP concept. Different methods of handling temporal data aggregation and the creation of GSTPs are discussed in this article. Using a large individual-based migration history dataset, this study successfully develops an operational space-time GIS prototype in ESRI's ArcScene and ArcMap to provide a proof-of-concept study of this approach. This space-time GIS system demonstrates that the proposed GSTP approach can provide a useful exploratory analysis and geovisualization environment to help researchers effectively search for hidden patterns and trends in such datasets.
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paper_title: Using fractal dimensions for characterizing tortuosity of animal trails

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. The tortuosity of mite trails was characterized by their fractal dimension, which is the non-Euclidean dimension varying between 1 (completely straight) and 2 (so tortuous that the complete two-dimensional space is used). This index was shown to be a good, discriminative index for mite trails, which is a completely new use of the fractal dimension. The value of this index is compared with other tortuosity indices.
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paper_title: Timing Space and Spacing Time

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A plea is made for a chronosophical approach to the selection of dimensions of time which might be relevant to the description and explanation of urban processes. Following the definition of some basic terms and concepts which might be used in the future development of a notational schema, the paper considers some possibilities which are inherent in the idea of timing space. This is followed by similar consideration of the idea of spacing time. These themes are compounded in a simple example which suggests that fundamental ongoing processes in daily urban behaviour are usefully summarised by what we call the accordion effect. The final section proposes that new insights into the problem of evaluating the quality of life of urban residents are obtained when such an approach is taken.
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paper_title: Algorithms for constrained k-nearest neighbor queries over moving object trajectories

paper_content:

An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (CkNN) queries and historical continuous CkNN (HCCkNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a CkNN query over trajectories retrieves from D within T, the k (? 1) trajectories that lie closest to q and intersect (or are enclosed by) CR; and (ii) an HCCkNN query on trajectories retrieves the constrained k nearest neighbors (CkNNs) of q at any time instance of T. We propose a suite of algorithms for processing CkNN queries and HCCkNN queries respectively, with different properties and advantages. In particular, we thoroughly investigate two types of CkNN queries, i.e., CkNNP and CkNNT, which are defined with respect to stationary query points and moving query trajectories, respectively; and two types of HCCkNN queries, namely, HCCkNNP and HCCkNNT, which are continuous counterparts of CkNNP and CkNNT, respectively. Our methods utilize an existing data-partitioning index for trajectory data (i.e., TB-tree) to achieve low I/O and CPU cost. Extensive experiments with both real and synthetic datasets demonstrate the performance of the proposed algorithms in terms of efficiency and scalability.
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paper_title: Time-geographic density estimation for home range analysis

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This research presents time-geographic density estimation (TGDE) as a new technique of animal home range analysis in geographic information science (GIS). TGDE combines methodologies of time geography and statistical density estimation to produce a continuous probability distribution of an object's spatial position over time. Once TGDE is applied to animal tracking data to create a density surface, home ranges and core areas can be delineated using specified contours of relative intensity (e.g., 95% or 50%). This article explores the use of TGDE for home range analysis using three data sets: a fixed-interval simulated data set and two variable-interval satellite tracks for a loggerhead sea turtle (Caretta caretta) corresponding to internesting and post-migration foraging periods. These applications are used to illustrate the influence of several parameters, including sample size, temporal sampling scheme, selected distance-weighted geoellipse function, and specified maximum velocity, on home range estimat...
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paper_title: On quantifying insect movements

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We elaborate on methods described by Turchin, Odendaal Rausher for quantifying insect movement pathways. We note the need to scale measurement resolution to the study insects and the questions being asked, and we discuss the use of surveying instrumentation for recording sequential positions of individuals on pathways. We itemize several measures that may be used to characterize movement pathways and illustrate these by comparisons among several Eleodes beetles occurring in shortgrass steppe. The fractal dimension of pathways may provide insights not available from absolute measures of pathway configuration. Finally, we describe a renormalization procedure that may be used to remove sequential interdependence among locations of moving individuals while preserving the basic attributes of the pathway.
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paper_title: A Conceptual View on Trajectories ⋆

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Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an object). This paper explores how conceptual modeling could provide applications with direct support of trajectories (i.e. movement data that is structured into countable semantic units) as a first class concept. A specific concern is to allow enriching trajectories with semantic annotations allowing users to attach semantic data to specific parts of the trajectory. Building on a preliminary requirement analysis and an application example, the paper proposes two modeling approaches, one based on a design pattern, the other based on dedicated data types, and illustrates their differences in terms of implementation in an extended-relational context.
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paper_title: Discovering relative motion patterns in groups of moving point objects

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Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been impleme...
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paper_title: How fast is a cow? Cross‐Scale Analysis of Movement Data

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Data representing the trajectories of moving point objects are becoming increasingly ubiquitous in GIScience, and are the focus of much methodological research aimed at extracting patterns and meaning describing the underlying phenomena. However, current research within GIScience in this area has largely ignored issues related to scale and granularity – in other words how much are the patterns that we see a function of the size of the looking glass that we apply? In this article we investigate the implications of varying the temporal scale at which three movement parameters, speed, sinuosity and turning angle are derived, and explore the relationship between this temporal scale and uncertainty in the individual data points making up a trajectory. A very rich dataset, representing the movement of 10 cows over some two days every 0.25 s is investigated. Our cross-scale analysis shows firstly, that movement parameters for all 10 cows are broadly similar over a range of scales when the data are segmented to remove quasi-static subtrajectories. However, by exploring realistic values of GPS uncertainty using Monte Carlo Simulation, it becomes apparent that fine scale measurement of all movement parameters is masked by uncertainties, and that we can only make meaningful statements about movement when we take these uncertainties into account.
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paper_title: Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants

paper_content:

Why study movement? data for measuring movement modelling movement building behaviourally based models analysis of movement paths mass mark-recapture individual mark-recapture. Appendix A: diffusion for ecologists.
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paper_title: Analysing space use patterns by Thiessen polygon and triangulated irregular network interpolation: a non-parametric method for processing telemetric animal fixes

paper_content:

This paper describes a new non-parametric model to estimate space use. We test the similarity in space use patterns between an artificially generated utilization distribution (Seaman- UD) and the model estimates for five different sample sizes. Three different test statistics (Kappa,gamma,Tc) reveal a high similarity between the estimates and the Seaman-UD. The tests also show that, beyond a certain threshold value, larger sample sizes do not return significantly better results. W e further demonstrate that the Thiessen model delineated areas of intensive use more effectively in a home range than Kernel estimators. UD estimation uses AML (ArcInfo Macro Language), thus facilitating overlay operations with habitat information stored in the same ArcInfo GIS environment.
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paper_title: Local measures of spatial association

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AbstractA fundamental concern in analyzing a spatial data set is to identify the presence and nature of spatial autocorrelation. Global measures can be used to summarize the typical features of spatial autocorrelation for the entire data set. However, if the data set has large spatial coverage, it is likely that there will be one or more subareas, possibly of variable sizes and shapes, that are different from the typical situation. Further, unless prior information is available, we are unlikely to have strong expectations about the number, locations, sizes, and shapes of such anomalies. Local measures of spatial autocorrelation have been developed to provide a way of revealing such peculiarities. By identifying anomalous subareas, local measures provide information that is useful in modelling the spatial processes that are thought to give rise to the data, especially since they give an indication of the spatial scales at which such processes might be operating. In addition, the information they provide is...
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paper_title: META-ANALYSIS OF ANIMAL MOVEMENT USING STATE-SPACE MODELS

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The study of animal movement and behavior is being revolutionized by technology, such as satellite tags and harmonic radar, that allows us to track the movements of individual animals. However, our ability to analyze and model such data has lagged behind the sophisticated collection methods. We review problems with current methods and suggest a more powerful and flexible approach, state-space modeling, and we illustrate how these models can be posed in a meta-analytic framework so that information from individual trajectories may be combined optimally. State-space models enable us to deal with the complexity of modeling animals interacting with their environment but, unlike other methods, they allow simultaneous estimation of measurement error and process noise that are inherent in animal-trajectory data. A Bayesian framework allows us to incorporate important prior information when available and also allows meta-analytic techniques to be incorporated in a straightforward fashion. Meta-analysis enables both individual and broader-level inference from observations of multiple individual pathways. Our approach is powerful because it allows researchers to test hypotheses regarding animal movement, to connect theoretical models to data, and to use modern likelihood-based estimation techniques, all under a single statistical framework.
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paper_title: Directed movements in probabilistic time geography

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This article studies probabilistic time geography for space-time prisms, that is, for situations where observers know the location of an agent at one time and then again at another time. In the intervening period, the agent would have moved freely, according to its time budget. The article demonstrates that the probability of finding the agent somewhere in the space-time prism is not equally distributed, so any attempt of a quantitative time geographic analysis must consider the actual probability distribution. This article develops, implements, and demonstrates this distribution. A preceding article introduced probabilistic time geography for space-time cones. With cones and prisms, the elementary space-time volumes of time geography are provided.
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paper_title: A Field-Based Theory for Time Geography

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Classic time geography is powerful but rigid, admitting only uniform travel velocities. Computational time geographic methods that resolve the uniform velocity assumption through transportation networks or isochrones only partially address this weakness and do not have a rigorous theoretical foundation. This article develops an analytical time geographic theory for the case where travel velocities vary continuously across space. Using the continuous transportation or “urban fields” tradition in quantitative geography and regional science, this article formulates analytical definitions of the space–time path and prism for the case where unobserved components are characterized by minimum cost curves through an inverse velocity field rather than straight line segments through a uniform velocity plane. This provides a geometrically and visually oriented approach to capturing complex velocities that complements existing methods. Time geographic fields also generalize time geography as the classic and isochrone...
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paper_title: Evaluating the Temporal Organization of Public Service Provision Using Space-Time Accessibility Analysis

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In recent years, there has been increasing awareness about the impact of urban time policies on the quality of people's everyday lives. However, within the urban planning field, evaluations of public service delivery have primarily focused on the spatial rather than the temporal organization of public service facilities. This study tries to fill this gap by using space-time accessibility analysis to explore the extent to which changes in open hours affect the social equity of service provision. To this end an accessibility model is implemented and employed in a case study of public service provision in the urban area of Ghent, Belgium. Our analysis not only demonstrates that access to public services exhibits substantial hour-to-hour and day-to-day variations, but it also shows that individuals with certain personal and household attributes are affected differently by changes to the temporal regime of public service facilities.
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paper_title: The Data Avalanche is Here: Shouldn’t We Be Digging?

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We have access to an unprecedented amount of fine-grained data on cities, transportation, economies, and societies, much of these data referenced in geo-space and time. There is a tremendous opportunity to discover new knowledge about spatial economies that can inform theory and modeling in regional science. However, there is little evidence of computational methods for discovering knowledge from databases in the regional science literature. This paper addresses this gap by clarifying the geospatial knowledge discovery process, its relation to scientific knowledge construction, and identifying challenges to a greater role in regional science.
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paper_title: Time-geography – at the end of its beginning

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Let me start by presenting a short 'definition' of the main subject of this essay. Time-geography constitutes a foundation for a general geographical perspective. It represents a new structure of thought under development, which attempts to consolidate the spatial and temporal perspectives of different disciplines on a more solid basis than has thus far taken place. Time-geography is not a subject area per se, or a theory in its narrow sense, but rather an attempt to construct a broad structure of thought which may form a framework capable of fulfilling two tasks. The first is to receive and bring into contact knowledge from highly distinct scientific areas and from everyday praxis. The second is to reveal relations, the nature of which escape researchers as soon as the object of research is separated from its given milieu in order to study it in isolation, experimentally or in some other way distilled. This is a very unofficial and condensed version of the definition given by Torsten Hagerstrand many years ago. It is not very easy to grasp. But to me, it is an excellent and compact version of what time-geography really is. As a backdrop, I will use a 'map' as a frame of reference. I will use a straightforward metaphor life as a drama. Though simple, this is a rather useful starting point. Every drama has three elements namely actors, roles (expressed by behaviors, activities), and the scene. (In fact, life is a drama without any spectators: we are all taking part in the play and cannot analyze the course of events from the comfort of a seat in the audience.) I will not dwell on this metaphor but will move ahead to make some short (and perhaps obvious) remarks. The human actors without them, there will be no play can be observed physically and portrayed by a trajectory in a timegeographic notation as they move around saying and doing things. Their thoughts, their experiences, expectations, aims, etc., are not directly observable, however. What they are doing, their activities, derives from the various roles they try to play. Most of the social sciences are concerned with these roles and how they are created and developed. Roughly speaking, their development is a matter of common culture values, rules, institutional frameworks, power structures, etc. In short, roles express what is called the underlying structure (or structures). The scene is the sum of all physical objects like natural phenomena, lakes, mountains, minerals and all that human beings and societies make out of raw materials transforming them into buildings, roads, machines, tools, etc. To complete the scene, we must add the actors themselves, who are part of the physical scene. This is a brief and rough rendition of Popper and Eccles' division of our world into three parts: the physical world (the scene), our inner worlds (actors' images) and the cultural heritage (role-creating), which has been established in our physical world or perhaps just in our minds. (Actually, I prefer the drama metaphor, because it captures the dynamics in human lives and societies). The name of the game is integration. The point is to deal with all worlds together, because the triad is something that we have superimposed on reality to make it easier to tackle. Time-geography, as a foundation for a general (geographical) perspective, tries to bring all these worlds together into a common framework. Or to put it the other way around, time-geography tries to separate the three worlds as little as possible in the analytic process. In this essay, I will briefly characterize the main areas that time-geographic thought has penetrated over the years. I will use the metaphor 'life as a drama' and Popper's tripartite world as a frame to reference to describe the shifts in emphasis over time and how time-geography has been accepted or rejected. In the same vein, I will sketch the contours of the critique of the time-geographic approach. Finally, I will try to outline the prospects of current developments for the future.
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paper_title: A Relative Representation of Trajectories in Geogaphical Spaces

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The research presented in this paper introduces a relative representation of trajectories in space and time. The objective is to represent space the way it is perceived by a moving observer acting in the environment, and to provide a complementary view to the usual absolute vision of space. Trajectories are characterized from the perception of a moving observer where relative positions and relative velocities are the basic primitives. This allows for a formal identification of elementary trajectory configurations, and their relationships with the regions that compose the environment. The properties of the model are studied, including transitions and composition tables. These properties characterize trajectory transitions by the underlying processes that semantically qualify them. The approach provides a representation that might help the understanding of trajectory patterns in space and time.
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paper_title: REAL-TIME MOOSE TRACKING: AN INTERNET BASED MAPPING APPLICATION USING GPS/GSM-COLLARS IN SWEDEN

paper_content:

To date, moose (Alces alces) tracking has relied on techniques either based on 'Very High Frequency' (VHF) / 'Ultra High Frequency' (UHF) radio collars, or Global Positioning System (GPS) collars, often requiring significant effort in the field to collect data. Here we present a technique that automatically tracks and reports moose in almost real time, and presents moose positions and movement paths with an interactive web-based map service. We equipped 25 female moose with GPS/GSM collars in Vasterbotten county, northern Sweden. The GPS receivers acquired a position every 30 minutes and transmitted them after 3.5 hours as a standard Short Messaging Service (SMS) message using the Global System for Mobile communications (GSM) cell phone network. The positions were automatically extracted from the receiving local GSM-modem and stored in a database. During 18 days in March 2003, 18,638 GPS positions were transmitted by 2,719 SMS messages. Of all positioning attempts 98.1% resulted in a valid position, whereof 99.7% were 3-dimensional positions. The real-time approach allows for many new research studies; e.g., small- scale migrational studies with adapted GPS schedules for different phases of migration. Further, public access to the moose data by a web-based map can be of fundamental importance for public acceptance when dealing with local concerns. ALCES VOL. 40: 13-21 (2004)
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paper_title: Correlation Analysis of Discrete Motions

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Points are dimensionless geometric elements often employed by geographic information systems to model a range of real-world objects such as people and vehicles. Many analytical tools have been developed for finding and validating certain patterns of static points such as clustering. In this paper, we present our preliminary efforts to develop statistical methods for analyzing patterns of moving points whose locations are tracked at equal intervals of time. Focus is placed on simple descriptive statistics—rather than more sophisticated inferential statistics—useful for detecting a tendency of two or more points to move in some coordinated fashion. A major implication of this paper is that statistical analysis complements spatial data query and modeling with respect to dynamics of sets of point-like objects in a way that potentially interrelated subsets are screened.
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paper_title: Modelling potential movement in constrained travel environments using rough space–time prisms

paper_content:

The widespread adoption of location-aware technologies (LATs) has afforded analysts new opportunities for efficiently collecting trajectory data of moving individuals. These technologies enable measuring trajectories as a finite sample set of time-stamped locations. The uncertainty related to both finite sampling and measurement errors makes it often difficult to reconstruct and represent a trajectory followed by an individual in space–time. Time geography offers an interesting framework to deal with the potential path of an individual in between two sample locations. Although this potential path may be easily delineated for travels along networks, this will be less straightforward for more nonnetwork-constrained environments. Current models, however, have mostly concentrated on network environments on the one hand and do not account for the spatiotemporal uncertainties of input data on the other hand. This article simultaneously addresses both issues by developing a novel methodology to capture potential movement between uncertain space–time points in obstacle-constrained travel environments.
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paper_title: Evolution of GPS technology and its subsequent use in commercial markets

paper_content:

The global positioning system (GPS) is not something that the average person thinks about and how it has affected our civilisation. In many of the systems it is used in, people don't think of it as the primary technology being used for the task at hand. It is a technology that has been taken for granted. Yet, without this technology, many of society's activities would be disrupted in some way. In this paper, the beginnings of GPS are traced while also exploring how it has embedded itself into a wide range of today's products. We will see how companies found new markets for their products with this technology and how this technology has displaced other technologies and practices. We also learn about the firms that found ways to use this technology. What were some of the problems they faced? Were they successful in integrating the technology into their products? Which companies failed to see the value of the technology and how were they affected?
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paper_title: Towards a probabilistic time geography

paper_content:

Time geography uses space-time volumes to represent the possible locations of a mobile agent over time in a x-y-t space. Space-time volumes are qualitative statements, enabling qualitative analysis. In this paper these statements will be quantified, modeling an agent's possible locations from a stochastic perspective. With such a model time geography can be improved in expressiveness as well as accuracy.
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paper_title: Kinetic space-time prisms

paper_content:

The space-time path and prism demarcate the estimated and potential locations (respectively) of a moving object with respect to time. The path is typically formed through linear interpolation between sampled locations of a moving object, while the prism is the envelope of all possible paths between two locations given the maximum speed of travel. The classic path and prism, however, are not physically realistic since they imply the ability of the object to make instantaneous changes in direction and speed without acceleration and deceleration. This is not acceptable in applications where kinetics is vital for scientific understanding such as animal ecology, vehicles moving through media such as ships through water and planes through air, human-powered movement such as bicycling and walking and environmental applications of transportation such as energy consumption and emissions modeling. In this paper we demonstrate how imposing an upper bound on acceleration, as well as information such as the initial speed and heading, affects the geometry of the space-time prism. We discuss how to calculate kinetic paths and prisms in one-dimensional and two dimensional space, and provide examples comparing the kinetic prisms and classical prisms.
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paper_title: Constrained free space diagrams: a tool for trajectory analysis

paper_content:

Time plays an important role in the analysis of moving object data. For many applications it is not sufficient to only compare objects at exactly the same times, or to consider only the geometry of their trajectories. We show how to leverage between these two approaches by extending a tool from curve analysis, namely the free space diagram. Our approach also allows us to take further attributes of the objects like speed or direction into account. We demonstrate the usefulness of the new tool by applying it to the problem of detecting single file movement. A single file is a set of moving entities, which are following each other, one behind the other. Our algorithm is the first one developed for detecting such movement patterns. For this application, we analyse demonstrate the performance of our tool both theoretically experimentally.
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paper_title: Reporting Leaders and Followers Among Trajectories of Moving Point Objects

paper_content:

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern `one object is leading others', which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.
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paper_title: Discovering relative motion patterns in groups of moving point objects

paper_content:

Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been impleme...
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paper_title: The Use Of Potential Functions In Modelling Animal Movement

paper_content:

Potential functions are a physical science concept often used in modelling the motion of particles and planets. In the work of this paper potential function based models are considered for the movement of free-ranging elk in a large, fenced ex- perimental forest. Equations of motion are set down and the parameters involved are estimated nonparametrically. The question of whether a potential function is plausible for describing the elk motion is considered. The conclusion is that it is not possible to reject this hypothesis for the data set and estimates considered.
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paper_title: ST‐DMQL: A Semantic Trajectory Data Mining Query Language

paper_content:

Mobile devices are becoming very popular in recent years, and large amounts of trajectory data are generated by these devices. Trajectories left behind cars, humans, birds or other objects are a new kind of data which can be very useful in the decision making process in several application domains. These data, however, are normally available as sample points, and therefore have very little or no semantics. The analysis and knowledge extraction from trajectory sample points is very difficult from the user's point of view, and there is an emerging need for new data models, manipulation techniques, and tools to extract meaningful patterns from these data. In this paper we propose a new methodology for knowledge discovery from trajectories. We propose through a semantic trajectory data mining query language several functionalities to select, preprocess, and transform trajectory sample points into semantic trajectories at higher abstraction levels, in order to allow the user to extract meaningful, understandab...
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paper_title: Classifying movement behaviour in relation to environmental conditions using hidden Markov models

paper_content:

Summary 1. Linking the movement and behaviour of animals to their environment is a central problem in ecology. Through the use of electronic tagging and tracking (ETT), collection of in situ data from free-roaming animals is now commonplace, yet statistical approaches enabling direct relation of movement observations to environmental conditions are still in development. 2. In this study, we examine the hidden Markov model (HMM) for behavioural analysis of tracking data. HMMs allow for prediction of latent behavioural states while directly accounting for the serial dependence prevalent in ETT data. Updating the probability of behavioural switches with tag or remote-sensing data provides a statistical method that links environmental data to behaviour in a direct and integrated manner. 3. It is important to assess the reliability of state categorization over the range of time-series lengths typically collected from field instruments and when movement behaviours are similar between movement states. Simulation with varying lengths of times series data and contrast between average movements within each state was used to test the HMMs ability to estimate movement parameters. 4. To demonstrate the methods in a realistic setting, the HMMs were used to categorize resident and migratory phases and the relationship between movement behaviour and ocean temperature using electronic tagging data from southern bluefin tuna (Thunnus maccoyii). Diagnostic tools to evaluate the suitability of different models and inferential methods for investigating differences in behaviour between individuals are also demonstrated.
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paper_title: Reporting flock patterns

paper_content:

Data representing moving objects is rapidly getting more available, especially in the area of wildlife GPS tracking. It is a central belief that information is hidden in large data sets in the form of interesting patterns, where a pattern can be any configuration of some moving objects in a certain area and/or during a certain time period. One of the most common spatio-temporal patterns sought after is flocks. A flock is a large enough subset of objects moving along paths close to each other for a certain pre-defined time. We give a new definition that we argue is more realistic than the previous ones, and by the use of techniques from computational geometry we present fast algorithms to detect and report flocks. The algorithms are analysed both theoretically and experimentally.
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paper_title: Impact of Data and Task Characteristics on Design of Spatio-Temporal Data Visualization Tools

paper_content:

It is widely recognized that data visualization may be a powerful methodology for exploratory analysis. In order to fulfill this claim, visualization software must be carefully designed taking into account two principal aspects: characteristics of the data to be visualized and the exploratory tasks to be supported. The tasks that may potentially arise in data exploration are, in their turn, dependent on the data. In the chapter, we present visualization software tools for three different types of spatio-temporal data developed using a task-driven approach to design. We demonstrate that different exploratory tasks may be anticipated in these three cases and that different techniques are required to properly support exploration of the data. Prior to the consideration of the examples, we briefly describe the typologies of data and tasks we use in our work.
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paper_title: Extended analysis of path data from mutant mice using the public domain software Wintrack

paper_content:

Abstract Animal tracking by means of videocameras has made considerable progress over the past several years and is now being used in a large number of studies. However, the precision and frequency at which xy path data can be recorded using personal computers contrast with the relative simplicity of the analyses commonly conducted with this type of data. In order to achieve more analytical power and flexibility in numerical and graphical path analysis, we have developed Wintrack, a Windows application that processes data from a variety of commercially available tracking systems. The application provides an intuitive drag-and-drop interface to increase ease and speed of standard analysis and graphical representation of data. A flexible scripting language allows the advanced user to extend the capabilities of the program by defining custom arenas and specialized parameters. For example, this permits to integrate path data with events recorded through the keyboard or to adapt the program for the processing of GPS data from outdoors experiments. A macro language allows for fully automated and database-controlled large-scale data analysis. We are using this feature to develop new analysis parameters for water maze and open-field experiments and to evaluate them retrospectively with reference data from several thousand mice tested in our laboratory. For noncommercial use, the software can be downloaded free of charge at www.dpwolfer.ch/wintrack .
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paper_title: Discovering relative motion patterns in groups of moving point objects

paper_content:

Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been impleme...
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Title: A Review of Quantitative Methods for Movement Data

Section 1: Introduction
Description 1: This section should provide an overview of the historical and theoretical context of movement data analysis in GIScience, the resurgence of quantitative methods due to technological advances, and the aim and structure of the review.

Section 2: Movement Data
Description 2: This section should define movement data, discuss common terms and representations, and highlight the types and granularity of movement data acquisition.

Section 3: Movement Database
Description 3: This section should explain the concept of movement databases, including the storage, indexing, and querying of movement data.

Section 4: Review of Methods
Description 4: This section should review existing quantitative analysis methods within seven areas of movement research: time geography, path descriptors, path similarity indices, pattern and cluster methods, individual-group dynamics, spatial field methods, and spatial range methods.

Section 5: Time Geography
Description 5: This section should detail the concept of time geography, including its historical development, theoretical framework, and quantitative applications.

Section 6: Path Descriptors
Description 6: This section should cover the measurement of path characteristics such as velocity, acceleration, and turning azimuth, and discuss how these descriptors can be calculated and interpreted.

Section 7: Path Similarity Indices
Description 7: This section should discuss various methods for quantifying the similarity between movement paths, including Euclidean distance, Hausdorff distance, Fréchet distance, and others.

Section 8: Pattern and Cluster Methods
Description 8: This section should review methods for identifying spatial-temporal patterns and clusters in large movement databases.

Section 9: Individual-Group Dynamics
Description 9: This section should explore methods focused on individual object movement within the context of a larger group, including the detection of patterns like trend-setters, flocks, and convoys.

Section 10: Spatial Field Methods
Description 10: This section should discuss the representation of movement paths as spatial fields to identify areas of frequent visitation and other spatial patterns.

Section 11: Spatial Range Methods
Description 11: This section should describe methods for quantifying the spatial range of movement, commonly using polygon representations.

Section 12: Challenges
Description 12: This section should identify key challenges in the quantitative analysis of movement data, emphasizing the unique difficulties of characterizing time and scale.

Section 13: Emerging Trends in Quantitative Movement Analysis
Description 13: This section should highlight technological and methodological advancements that facilitate the real-time capture, analysis, and prediction of movement data, as well as emerging research opportunities.

Section 14: Conclusions
Description 14: This section should summarize the review, emphasize the need for novel quantitative methods, and briefly touch on future research directions.