Multi-hazard vulnerability zone identification using GIS-based fuzzy AHP and MCDM techniques

被引:0
|
作者
Sood, Atisha [1 ]
Vignesh, K. S. [2 ]
Prapanchan, V. N. [3 ]
机构
[1] SRM Inst Sci & Technol, Sch Publ Hlth, Kattankulathur, Tamil Nadu, India
[2] SRM Inst Sci & Technol, Ctr Occupat Safety & Hlth, Dept Mech Engn, Kattankulathur, Tamil Nadu, India
[3] Anna Univ, Coll Engn CEG, Dept Geol, Chennai 600025, Tamil Nadu, India
关键词
Multi-hazard; Urban region; FAHP; Frequency ratio; Mutli-hazard index (MHI); RISK-ASSESSMENT; FLOODS;
D O I
10.1007/s11069-025-07125-2
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The increasing frequency and intensity of natural disasters due to climate change and anthropogenic influences necessitate multi-hazard assessments in vulnerable urban areas. This study identifies potential multi-hazard zones in the Greater Chennai Corporation, Tamil Nadu, focusing on flood, cyclone, and tsunami risks. The Fuzzy Analytical Hierarchical Process (FAHP)-based Multi-Criteria Decision Making (MCDM) approach was used to determine potential hazard zones by considering individual hazards previously recorded in the study area. The three estimated hazard zones were combined using the Frequency Ratio (FR) method to calculate the Multi-Hazard Index (MHI), which was then categorized to identify probable multi-hazard zones using a geospatial platform. Various hazard-influencing factors, including topographical, meteorological, and inundation parameters, were considered in the analysis. Accuracy assessment, crucial for reliable LULC classification, showed high overall accuracy. The identified multi-hazard zones were classified into five categories: very High (17 sq. km.), High (139 sq. km.), Moderate (203 sq. km.), Low (61 sq. km.), and Very Low (3.8 sq. km.). The Moderate category exhibited the highest occupancy rate at 47.70%, while the Very Low category had the lowest occupancy rate at 0.80%. To evaluate the precision of the FAHP models, an analysis was conducted using the Receiver Operating Characteristic (ROC) curve method. The results revealed an Area Under the Curve (AUC) of 0.85, 0.82, and 0.83 for flood, cyclone, and tsunami, respectively, signifying superior model efficiency. These results provide valuable insights for policymakers in developing robust strategies for multi-hazard mitigation and disaster resilience planning.
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页数:39
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