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Crisp and Fuzzy AHP in GIS-MCDA for Wildlife Habitat Suitability Analysis

Crisp and Fuzzy AHP in GIS-MCDA for Wildlife Habitat Suitability Analysis
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Author(s): Suman Sinha (Amity University, Kolkata, India)
 Copyright: 2020
 Pages: 23
 Source title: Spatial Information Science for Natural Resource Management
Source Author(s)/Editor(s): Suraj Kumar Singh (Suresh Gyan Vihar University, Jaipur, India), Shruti Kanga (Suresh Gyan Vihar University, Jaipur, India)and Varun Narayan Mishra (Suresh Gyan Vihar University, Jaipur, India)
 DOI: 10.4018/978-1-7998-5027-4.ch001

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Abstract

Geographic information system-based multi-criteria decision analysis (GIS-MCDA) is a process of decision making where geographical data and value judgments are integrated. Analytic hierarchy process (AHP) is a useful technique in MCDA for determining weights. This study focuses on the evaluation of GIS-MCDA using different uncertainty levels in AHP. Best suitable sites for tiger habitats are located and analyzed in Sariska Wildlife Reserve, India using crisp and fuzzy AHP in GIS-MCDA, and thereafter, an optimal habitat suitability model is proposed. The percentage deviation over the uncertainty levels ranges slightly over 5%. The relative difference between CAHP and FAHP is nearly 2.7%. Chi-square test reveals relationship between the degree of uncertainty and the difference between the maps. For real-world situations with increased variability, fuzzification is preferred and shows the best results. The worldwide declining status of the tigers is a serious threat to the overall biodiversity, and the methods adopted in this study thus target their conservation and management.

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