GeoGPT: Understanding and Processing Geospatial Tasks through An
  Autonomous GPT
Yifan Zhang Cheng Wei Shangyou Wu Zhengting He Wenhao Yu
Decision-makers in GIS need to combine a series of spatial algorithms and
operations to solve geospatial tasks. For example, in the task of facility
siting, the Buffer tool is usually first used to locate areas close or away
from some specific entities; then, the Intersect or Erase tool is used to
select candidate areas satisfied multiple requirements. Though professionals
can easily understand and solve these geospatial tasks by sequentially
utilizing relevant tools, it is difficult for non-professionals to handle these
problems. Recently, Generative Pre-trained Transformer (e.g., ChatGPT) presents
strong performance in semantic understanding and reasoning. Especially, AutoGPT
can further extend the capabilities of large language models (LLMs) by
automatically reasoning and calling externally defined tools. Inspired by these
studies, we attempt to lower the threshold of non-professional users to solve
geospatial tasks by integrating the semantic understanding ability inherent in
LLMs with mature tools within the GIS community. Specifically, we develop a new
framework called GeoGPT that can conduct geospatial data collection,
processing, and analysis in an autonomous manner with the instruction of only
natural language. In other words, GeoGPT is used to understand the demands of
non-professional users merely based on input natural language descriptions, and
then think, plan, and execute defined GIS tools to output final effective
results. Several cases including geospatial data crawling, spatial query,
facility siting, and mapping validate the effectiveness of our framework.
Though limited cases are presented in this paper, GeoGPT can be further
extended to various tasks by equipping with more GIS tools, and we think the
paradigm of "foundational plus professional" implied in GeoGPT provides an
effective way to develop next-generation GIS in this era of large foundation
models.