# Geospatial Big Data: Survey and Challenges

arXiv: https://arxiv.org/abs/2404.18428 · HTML: https://mlsanity.com/paper/2404.18428/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2024.

## Built on by (most cited first, 5 of 5)

- [An LLM Agent for Automatic Geospatial Data Analysis](https://mlsanity.com/paper/2410.18792/) (2024)
- [Artificial Intelligence in Landscape Architecture: A Survey](https://mlsanity.com/paper/2408.14700/) (2024)
- [Towards Intelligent Geospatial Data Discovery: a knowledge graph-driven multi-agent framework powered by large language models](https://mlsanity.com/paper/2603.20670/) (2026)
- [Improving the Computational Efficiency and Explainability of GeoAggregator](https://mlsanity.com/paper/2507.17977/) (2025)
- [Lightweight Multi-scale Hierarchical Anomaly Detection and Localization for Geospatial Big Data Applications at the Edge](https://mlsanity.com/paper/2608.22648/) (2026)

## Abstract (arXiv)

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.