Enterprise AI Analysis
Geospatial Technologies for Flood and Drought Management: A Review of Earth Observation Data, Procedures, and their Operational Effectiveness
Authors: Sona Guliyeva, Piero Boccardo
This review synthesizes the current state of Earth Observation (EO)-based flood and drought management, focusing on operational integration of EO data and procedures across key response substages. It assesses core EO sensor capabilities and introduces the Operational EO Integration Framework (OEI-F), aligning data types, integration approaches, spatial scales, and response substages. The findings highlight EO's pivotal role in climate adaptation, multi-hazard resilience, and decision-making.
Key Insights for Strategic Implementation
Leveraging advanced geospatial technologies and Earth Observation data is critical for enhancing flood and drought management. Our analysis distills the core findings, offering actionable intelligence for robust disaster resilience and climate adaptation strategies.
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Active EO Satellites
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Projected EO Fleet Growth
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Disasters Annually (2023-2024)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Hazard Impact & Drivers
EO Role & Evolution
Core EO Sensor Capabilities
OEI-F
Multi-Source Data Integration
400+
Disasters Annually (2023-2024)
Floods and droughts are among the most damaging hydrological hazards, escalating globally due to increasing exposure, systemic vulnerabilities, and intensifying impacts of climate change and rapid urbanization. Floods cause immediate, large-scale damage and billions in losses, while droughts are recognized as the 'most severe natural hazard worldwide' in terms of societal impact. The EM-DAT reported nearly 400 disasters annually in 2023 and 2024, with floods comprising over one-third of global events.
EO's Pivotal Role in Disaster Management
Geospatial technologies, especially Earth Observation (EO), provide multi-scale, near-real-time information crucial for disaster management. With over 1,000 active EO satellites and fleets projected to nearly triple, EO's institutionalization is seen in frameworks like the Sendai Framework and UN-SPIDER, and its integration into policy like UN Agenda 2030 and Copernicus Programme, highlights its relevance for climate adaptation, early warning, and risk-informed decision-making. Despite advancements, challenges remain in integrating heterogeneous multi-sensor datasets, ensuring interoperability, adapting workflows to compound extremes, and bridging the research-to-practice gap.
| Sensor Type | Key Strengths (Flood) | Key Strengths (Drought) | Limitations |
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| Optical (VNIR, SWIR) |
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| Thermal Infrared (TIR) |
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| Microwave (Active SAR) |
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| Microwave (Passive Radiometers) |
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| LiDAR (Laser Altimetry) |
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Enterprise Process Flow: Operational EO Integration Framework (OEI-F)
Early Situation Assessment
→
Emergency Decision Support
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Recovery & Planning
The OEI-F systematically aligns EO data types, integration approaches, spatial scales, and response substages within an operational context. It explicitly links data families, fusion levels, spatial scales (Global, Regional, National/Local), and response substages, providing a coherent structure for understanding EO contributions to disaster management.
Synergistic Integration for Robust Monitoring
No single EO dataset can capture the full complexity of flood and drought dynamics. Multi-source integration is fundamental, bridging sensor limitations and enhancing reliability. For example, the fusion of Sentinel-1 SAR and Sentinel-2 optical data is routinely applied for cloud-robust flood extent mapping. Feature-level fusion, like the Vegetation Health Index (VHI), combines NDVI and LST anomalies for drought detection. Model-level fusion assimilates EO products into hydrological models, such as LISFLOOD for flood forecasting or SMAP soil moisture into GLDAS for large-scale drought monitoring. Cross-spectral integration, multi-platform approaches (satellite with UAV-mounted LiDAR for urban flood depth), and multi-scale integration (MODIS + Sentinel-2 for crop-level stress) demonstrate enhanced capabilities. These integrated approaches routinely exceed 90% classification accuracy in flood susceptibility mapping and drought forecasting.
Calculate Your Potential ROI
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Annual Cost Savings
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Annual Hours Reclaimed
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Your Strategic Implementation Roadmap
A strategic phased approach to integrate advanced geospatial technologies into your disaster management and climate adaptation strategies, leveraging Earth Observation data for enhanced resilience.
Phase 1: Develop Interoperable Multi-Hazard Frameworks
Create frameworks that jointly monitor floods, droughts, and compound events, ensuring comprehensive situational awareness.
Phase 2: Address Policy and Regulatory Barriers
Overcome challenges related to UAV restrictions, data licensing issues, and weak cross-border data-sharing mechanisms through targeted policies and agreements.
Phase 3: Expand Open and Equitable Access to EO Data
Promote access to Earth Observation data, especially in underserved regions, through cloud infrastructures and international partnerships.
Phase 4: Leverage AI, Small Satellites, and Digital Twins
Utilize emerging technologies to accelerate hazard detection, enable near-real-time scenario modeling, and enhance predictive capabilities.
Phase 5: Strengthen Institutional Capacity
Embed Earth Observation into disaster management protocols and provide training for local agencies to use EO products operationally, fostering evidence-based decision-making.
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