Abstract
The surge in the frequency of disasters worldwide has heightened the concern for efficient disaster risk management (DRM). All phases of DRM require substantial amounts of precise, pertinent, and timely geospatial data, also referred to as Big Spatiotemporal Data. The main sources of these Spatiotemporal data can be categorized into two broad categories: traditional sources, such as satellite imagery, aerial imagery; and emerging sources, such Internet of Things (IoT), and Volunteer Geographic Information (VGI) data. In fact, the emergence of VGI presents the potential for near real-time data gathering as well as extensive data collection during and after disasters. This paper reviews the current research landscape regarding the utilization of VGI and big spatiotemporal data in disaster risk management. The objective is to highlight key application areas, current trends, available data sources, and persistent challenges within these fields.
| Original language | English |
|---|---|
| Article number | 25 |
| Journal | International Journal of Data Science and Analytics |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jun 2026 |
Keywords
- Disaster risk management
- Spatiotemporal big data
- Streaming processing
- VGI
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