EventsThe 6th International Electronic Conference on Remote Sensing
Published
This submission belongs to the session S2. SAR Remote Sensing of the event The 6th International Electronic Conference on Remote Sensing
Published date
14 Oct, 2026
Academic Editor
author-avatarTimo Balz
Citation
Mohamed Taieb Benamara, An Integrated Geospatial Intelligence Framework for Groundwater Hazard Vulnerability Assessment Using Sentinel-1 DinSAR, GIS, Hydrochemistry, and Multi-Criteria Decision Analysis, in Proceedings of The 6th International Electronic Conference on Remote Sensing, 19 October–21 October 2026, MDPI: Basel, Switzerland
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An Integrated Geospatial Intelligence Framework for Groundwater Hazard Vulnerability Assessment Using Sentinel-1 DinSAR, GIS, Hydrochemistry, and Multi-Criteria Decision Analysis

Mohamed Taieb Benamara 1
1. Department of Geophysics, Geodesy and Cartography Program, University of Science and Technology Houari Boumediene (USTHB), Algiers 16111, Algeria
Abstract

1. Introduction

Groundwater-related hazards, including rising water tables, seawater intrusion, and groundwater quality degradation, pose significant threats to civil engineering structures in rapidly urbanizing coastal regions. The commune of Réghaïa (Algeria) is particularly vulnerable due to its shallow Quaternary aquifer, rapid urban expansion, and the presence of the Ramsar wetland. This study aims to develop an integrated GIS- and remote sensing-based approach to assess groundwater-related vulnerability and support sustainable urban planning.

2. Methods

A multidisciplinary methodology was implemented by integrating Sentinel-1 DinSAR data, remote sensing indices (NDVI, NDWI, NDMI), land use/land cover mapping, laboratory physicochemical analyses of 17 groundwater samples, Geographic Information Systems (GIS), and the Analytic Hierarchy Process (AHP). All thematic layers were standardized and weighted to generate a groundwater vulnerability map, which was subsequently validated through field observations.

3. Results

Hydrochemical analyses revealed significant groundwater mineralization, with electrical conductivity reaching 2209.47 µS/cm and chloride concentrations up to 1075 mg/L, indicating seawater intrusion and anthropogenic impacts. DinSAR analysis detected slight ground uplift ranging from 0.001 to 0.074 mm/year, particularly along the coastal area. The AHP model (Consistency Ratio = 0.074) produced a five-class vulnerability map, successfully identifying the Bouraada and Cité Sonacom sectors as highly vulnerable areas, consistent with observed infrastructure deterioration and water accumulation.

4. Conclusions

The proposed integrated methodology effectively combines remote sensing, GIS, hydrochemical analysis, and multi-criteria decision analysis to identify areas vulnerable to groundwater-related hazards. The resulting vulnerability map provides a practical decision-support tool for groundwater management, infrastructure protection, and sustainable urban planning in coastal environments. This framework can also be adapted to other semi-arid coastal regions facing similar hydrogeological challenges.

Keywords
Sentinel-1
DInSAR
Synthetic Aperture Radar (SAR)
Groundwater
GIS
Hydrogeology
Land Subsidence
Urban Areas
AHP
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