An overview of city analytics
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paper_title: Comparison of social structures within cities of very different sizes

paper_content:

People make a city, making each city as unique as the combination of its inhabitants. However, some cities are similar and some cities are inimitable. We examine the social structure of 10 different cities using Twitter data. Each city is decomposed to its communities. We show that in many cases one city can be thought of as an amalgamation of communities from another city. For example, we find the social network of Manchester is very similar to the social network of a virtual city of the same size, where the virtual city is composed of communities from the Bristol network. However, we cannot create Bristol from Manchester since Bristol contains communities with a social structure that are not present in Manchester. Some cities, such as Leeds, are outliers. That is, Leeds contains a particularly wide range of communities, meaning we cannot build a similar city from communities outside of Leeds. Comparing communities from different cities, and building virtual cities that are comparable to real cities, is a novel approach to understand social networks. This has implications when using social media to inform or advise residents of a city.
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paper_title: Comparing and modeling land use organization in cities

paper_content:

The advent of geolocated ICT technologies opens the possibility of exploring how people use space in cities, bringing an important new tool for urban scientists and planners, especially for regions where data is scarce or not available. Here we apply a functional network approach to determine land use patterns from mobile phone records. The versatility of the method allows us to run a systematic comparison between Spanish cities of various sizes. The method detects four major land use types that correspond to different temporal patterns. The proportion of these types, their spatial organization and scaling show a strong similarity between all cities that breaks down at a very local scale, where land use mixing is specific to each urban area. Finally, we introduce a model inspired by Schelling's segregation, able to explain and reproduce these results with simple interaction rules between different land uses.
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paper_title: Assessing urban strategies for reducing the impacts of extreme weather on infrastructure networks

paper_content:

Critical infrastructure networks, including transport, are crucial to the social and economic function of urban areas but are at increasing risk from natural hazards. Minimizing disruption to these networks should form part of a strategy to increase urban resilience. A framework for assessing the disruption from flood events to transport systems is presented that couples a high-resolution urban flood model with transport modelling and network analytics to assess the impacts of extreme rainfall events, and to quantify the resilience value of different adaptation options. A case study in Newcastle upon Tyne in the UK shows that both green roof infrastructure and traditional engineering interventions such as culverts or flood walls can reduce transport disruption from flooding. The magnitude of these benefits depends on the flood event and adaptation strategy, but for the scenarios considered here 3–22% improvements in city-wide travel times are achieved. The network metric of betweenness centrality, weighted by travel time, is shown to provide a rapid approach to identify and prioritize the most critical locations for flood risk management intervention. Protecting just the top ranked critical location from flooding provides an 11% reduction in person delays. A city-wide deployment of green roofs achieves a 26% reduction, and although key routes still flood, the benefits of this strategy are more evenly distributed across the transport network as flood depths are reduced across the model domain. Both options should form part of an urban flood risk management strategy, but this method can be used to optimize investment and target limited resources at critical locations, enabling green infrastructure strategies to be gradually implemented over the longer term to provide city-wide benefits. This framework provides a means of prioritizing limited financial resources to improve resilience. This is particularly important as flood management investments must typically exceed a far higher benefit–cost threshold than transport infrastructure investments. By capturing the value to the transport network from flood management interventions, it is possible to create new business models that provide benefits to, and enhance the resilience of, both transport and flood risk management infrastructures. Further work will develop the framework to consider other hazards and infrastructure networks.
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paper_title: Predicting the impact of urban flooding using open data

paper_content:

This paper aims to explore whether there is a relationship between search patterns for flood risk information on the Web and how badly localities have been affected by flood events. We hypothesize that localities where people stay more actively informed about potential flooding experience less negative impact than localities where people make less effort to be informed. Being informed, of course, does not hold the waters back; however, it may stimulate (or serve as an indicator of) such resilient behaviours as timely use of sandbags, relocation of possessions from basements to upper floors and/or temporary evacuation from flooded homes to alternative accommodation. We make use of open data to test this relationship empirically. Our results demonstrate that although aggregated Web search reflects average rainfall patterns, its eigenvectors predominantly consist of locations with similar flood impacts during 2014-2015. These results are also consistent with statistically significant correlations of Web search eigenvectors with flood warning and incident reporting datasets.
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paper_title: Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes

paper_content:

We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized.
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paper_title: Spatio-temporal networks: reachability, centrality and robustness

paper_content:

Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.
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paper_title: User-based representation of time-resolved multimodal public transportation networks

paper_content:

Multimodal transportation systems can be represented as time-resolved multilayer networks where different transportation modes connecting the same set of nodes are associated to distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geolocalised transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, our aim is to provide a novel user-based methodological framework to represent public transportation systems considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. Using this framework we analyse public transportation systems in several French municipal areas. We incorporate travel routes and times over multiple transportation modes to identify efficient transportation connections and non-trivial connectivity patterns. The proposed method enables us to quantify the network's overall efficiency as compared to the specific demand and to the car alternative.
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paper_title: Chatty maps: constructing sound maps of urban areas from social media data

paper_content:

Urban sound has a huge influence over how we perceive places. Yet, city planning is concerned mainly with noise, simply because annoying sounds come to the attention of city officials in the form of complaints, while general urban sounds do not come to the attention as they cannot be easily captured at city scale. To capture both unpleasant and pleasant sounds, we applied a new methodology that relies on tagging information of geo-referenced pictures to the cities of London and Barcelona. To begin with, we compiled the first urban sound dictionary and compared it to the one produced by collating insights from the literature: ours was experimentally more valid (if correlated with official noise pollution levels) and offered a wider geographic coverage. From picture tags, we then studied the relationship between soundscapes and emotions. We learned that streets with music sounds were associated with strong emotions of joy or sadness, while those with human sounds were associated with joy or surprise. Finally, we studied the relationship between soundscapes and people's perceptions and, in so doing, we were able to map which areas are chaotic, monotonous, calm, and exciting.Those insights promise to inform the creation of restorative experiences in our increasingly urbanized world.
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Title: An overview of city analytics

Section 1: Background
Description 1: This section introduces the context and importance of city analytics, discussing the proliferation of data generated from city life and the interdisciplinary nature of the field.

Section 2: The themed issue
Description 2: This section provides information about the workshop and call for papers that led to this themed issue, outlines the criteria for submissions, and summarizes the acceptance process and the content of the published articles.

Section 3: Further details
Description 3: This section delves deeper into the specific methodologies and findings of a selection of the published articles, highlighting the diverse applications and interdisciplinary approaches used in city analytics research.

Section 4: Forward look
Description 4: This section discusses the future of city analytics, emphasizing the interdisciplinary foundations of the field and the potential of new data streams and technologies to advance research and practical applications.