Satellite-based drought assessment: integrating AHP method and fuzzy logic for comprehensive vulnerability and risk analysis

Kamila Hodasová (), Dávid Krčmář and Ivana Ondrejková
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Kamila Hodasová: Comenius University in Bratislava
Dávid Krčmář: Comenius University in Bratislava
Ivana Ondrejková: Comenius University in Bratislava

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 10, No 14, 11609-11632

Abstract: Abstract Drought research is a timely issue, as drought is an extreme phenomenon with consequences that threaten nature, landscapes and society. Drought is typically defined as a prolonged period of abnormally low precipitation leading to water shortages in soils and water supplies. This study investigates the vulnerability and risk of the landscape to drought in the Banská Bystrica region of Slovakia, focusing on the integration of Landsat 8 satellite image analysis, fuzzy logic and Analytic Hierarchy Process (AHP) methods. The evaluation process involves the selection and processing of input factors from Landsat 8 satellite imagery that are key contributors to drought vulnerability. These methods are used to assess drought vulnerability and associated risks. The resulting drought vulnerability map was created using fuzzy logic in a GIS environment. The final drought risk map was then evaluated. The final maps were categorised into four classes, with comparisons made between drought vulnerability index (DVI) and drought risk index (DRI) at gauging stations. Our findings highlight significant differences in drought vulnerability and risk across different areas of the region. The study provides valuable insights into the comprehensive analysis of drought. Examination of the map shows that the highest levels of risk are found in both the northern and southern parts of the region. This spatial pattern highlights areas that are particularly vulnerable to drought.

Keywords: Drought vulnerability; Drought risk; AHP method; Fuzzy logic; Landsat 8 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07254-8

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