Geospatial Big Data: Survey and Challenges
CoRR(2024)
摘要
In recent years, geospatial big data (GBD) has obtained attention across
various disciplines, categorized into big earth observation data and big human
behavior data. Identifying geospatial patterns from GBD has been a vital
research focus in the fields of urban management and environmental
sustainability. This paper reviews the evolution of GBD mining and its
integration with advanced artificial intelligence (AI) techniques. GBD consists
of data generated by satellites, sensors, mobile devices, and geographical
information systems, and we categorize geospatial data based on different
perspectives. We outline the process of GBD mining and demonstrate how it can
be incorporated into a unified framework. Additionally, we explore new
technologies like large language models (LLM), the Metaverse, and knowledge
graphs, and how they could make GBD even more useful. We also share examples of
GBD helping with city management and protecting the environment. Finally, we
discuss the real challenges that come up when working with GBD, such as issues
with data retrieval and security. Our goal is to give readers a clear view of
where GBD mining stands today and where it might go next.
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