Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/113963
Title: Wildfire Risk Zone Mapping in Contrasting Climatic Conditions: An Approach Employing AHP and F-AHP Models
Authors: Sinha, Aishwarya
Nikhil, Suresh
Ajin, Rajendran Shobha
Danumah, Jean Homian
Saha, Sunil
Costache, Romulus
Rajaneesh, Ambujendran
Sajinkumar, Kochappi Sathyan
Amrutha, Kolangad
Johny, Alfred
Marzook, Fahad
Mammen, Pratheesh Chacko
Abdelrahman, Kamal
Fnais, Mohammed S.
Abioui, Mohamed 
Keywords: anthropogenic factors; AHP; F-AHP; ROC; wildfires; wildlife sanctuaries
Issue Date: 2023
Publisher: MDPI
Project: Researchers Supporting Project number RSP2023R351, King Saud University, Riyadh, Saudi Arabia 
Serial title, monograph or event: Fire
Volume: 6
Issue: 2
Abstract: Wildfires are one of the gravest and most momentous hazards affecting rich forest biomes worldwide; India is one of the hotspots due to its diverse forest types and human-induced reasons. This research aims to identify wildfire risk zones in two contrasting climate zones, the Wayanad Wildlife Sanctuary in the Western Ghats and the Kedarnath Wildlife Sanctuary in the Himalayas, using geospatial tools, analytical hierarchy process (AHP), and fuzzy-AHP models to assess the impacts of various conditioning factors and compare the efficacy of the two models. Both of the wildlife sanctuaries were severely battered by fires in the past, with more than 100 fire incidences considered for this modeling. This analysis found that both natural and anthropogenic factors are responsible for the fire occurrences in both of the two sanctuaries. The validation of the risk maps, utilizing the receiver operating characteristic (ROC) method, proved that both models have outstanding prediction accuracy for the training and validation datasets, with the F-AHP model having a slight edge over the other model. The results of other statistical validation matrices such as sensitivity, accuracy, and Kappa index also confirmed that F-AHP is better than the AHP model. According to the F-AHP model, about 22.49% of Kedarnath and 17.12% ofWayanad fall within the very-high risk zones. The created models will serve as a tool for implementing effective policies intended to reduce the impact of fires, even in other protected areas with similar forest types, terrain, and climatic conditions.
URI: https://hdl.handle.net/10316/113963
ISSN: 2571-6255
DOI: 10.3390/fire6020044
Rights: openAccess
Appears in Collections:FCTUC Ciências da Terra - Artigos em Revistas Internacionais
I&D MARE - Artigos em Revistas Internacionais

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