GIS-based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, anal
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GIS‑based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, analytic hierarchy process and fuzzy modeling techniques Anuj Tiwari1 · Mohammad Shoab2 · Abhilasha Dixit3 Received: 4 May 2020 / Accepted: 26 September 2020 © Springer Nature B.V. 2020
Abstract This study performs a comparative evaluation of Frequency Ratio (FR), Analytic Hierarchy Process (AHP), and Fuzzy AHP (FAHP) modeling techniques for forest fire susceptibility mapping in Pauri Garhwal, Uttarakhand, India. Locations of past forest fire events reported from November 2002 to July 2019 were collected from the Uttarakhand Forest Department and Forest Survey of India and combined with the ground observations obtained from the manual survey. Then, the locations were categorized into two groups of 70% (10,500 locations) and 30% (4500 locations), randomly, for training and validation purposes, respectively. Forest fire susceptibility mapping was performed on the basis of fourteen different topographic, biological, human-induced and climatic criteria such as Digital Elevation Model, Slope, Aspect, Curvature, Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Topographic Wetness Index, Soil, Distance to Settlement, Distance to Road, Distance to Drainage, Rainfall, Temperature, and Wind Speed. The Receiver Operating Characteristic curve and the Area Under the Curve (AUC) were implemented for validation of the three achieved Forest Fire Susceptibility Maps. The AUC plot evaluation revealed that FAHP has a maximum prediction accuracy of 83.47%, followed by AHP (81.75%) and FR (77.21%). Thus, the map produced by FAHP exhibits the most satisfactory properties. Results and findings of this study will help in developing more efficient fire management strategies in both the open and the protected forest areas (Rajaji and Jim Corbett National Park) of the district. Keywords Forest fire susceptibility map (FFSM) · Multi-criteria decision analysis (MCDA) · Frequency ratio (FR) · Analytical hierarchical process (AHP) · Fuzzy analytical hierarchical process (FAHP)
* Anuj Tiwari [email protected] Extended author information available on the last page of the article
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Natural Hazards
1 Introduction According to the recent reports of global Forest Resources Assessment (FRA) of the Food and Agriculture Organization (FAO), United Nations, world forests occupy an area of 4.06 billion hectares, representing 30.60% of the planet’s total surface area (Fao 2015). Forests are the primary natural resources and nature’s most enormous bounty to humanity that play a central role in sustaining ecological balance and shaping the journey of human civilization. But forests around the world are under threat, jeopardizing all the advantages. The threats manifest themselves in the form of deforestation and forest degradation. Along with other factors, forest fires are the significant cause of deforestation and forest degradation (Hosonuma et al. 2012). The increasing rate of f
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