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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

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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.

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(Source Local Residents, Field Survey, and Uttarakhand Forest Department, India)

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Acknowledgements

The authors would like to express their great appreciation to Dr Kamal Jain, Professor, Department of Civil Engineering, IIT Roorkee, India, for his professional guidance, enthusiastic encouragement and valuable support. The authors would also like to thank Mr. Surendra Sharma, Scientist-C, IIRS-ISRO, Dehradun, India, for his constructive suggestions during the planning and development of this research work. Our grateful thanks are also extended to Mr. Deepak Tyagi, M. Tech, NIIT University, Neemrana, Rajasthan, India, Mr. Indresh Upadhyay, DFO, Uttarakhand Forest Department, India and Mr. Anurag Joshi, Forest Ranger, Uttarakhand Forest Department, India, for their help in forest fire field data collection, analysis and interpretation.

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  1. Department of Civil Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, India

    Anuj Tiwari

  2. Department of Computer Science, College of Science and Humanities, Shaqra University, Al Dawadmi, Riyadh Province, Kingdom of Saudi Arabia

    Mohammad Shoab

  3. Centre of Excellence in Disaster Mitigation and Management, Indian Institute of Technology, Roorkee, Uttarakhand, India

    Abhilasha Dixit

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Tiwari, A., Shoab, M. & Dixit, A. GIS-based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, analytic hierarchy process and fuzzy modeling techniques. Nat Hazards 105, 1189–1230 (2021). https://doi.org/10.1007/s11069-020-04351-8

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