Analytic Hierarchy Process with GIS and Remote Sensing for Natural-Hazard Susceptibility Assessment: Applications, Trends, and Lessons for Kinshasa

Abstract

This article reviews the use of the Analytic Hierarchy Process (AHP) combined with Geographic Information Systems (GIS) and remote sensing for natural-hazard susceptibility mapping, with a focus on lessons applicable to Kinshasa. A total of 62 peer-reviewed studies published between 2000 and 2024 were analyzed, covering six major hazard types: flooding (18 studies), landslides (15), erosion (10), urban heat islands and air quality (6), groundwater recharge and water deficit (7), and multi-hazard analyses (6).

Across all hazards, the most frequently applied criteria were land use/land cover (78%), slope (75%), rainfall (58%), soil type (46%), and geology (38%), reflecting the dominant role of topographic and land-cover factors in susceptibility assessment. Validation practices varied, but ROC/AUC (Receiver Operating Characteristic/ Area Under the Curve) was used in 50% of studies, with a median AUC of 0.82 (IQR: 0.76–0.88), indicating good model performance. However, only 8% of studies included field-based or inventory validation, underscoring the need for more robust approaches.

For Kinshasa, three key recommendations emerge: (1) prioritize slope and land-use mapping at high spatial resolution to capture fine-scale urban and geomorphological dynamics; (2) strengthen validation protocols by combining ROC/AUC with field inventories and community-based hazard reporting; and (3) promote a multi-hazard framework integrating flooding, erosion, and landslides, which are strongly interrelated in tropical urban environments.

This structured review highlights both the strengths and limitations of AHP-based hazard mapping and provides a methodological baseline for applying GIS and remote sensing in rapidly growing African cities facing climate and land-use pressures