Version 1
: Received: 3 July 2023 / Approved: 4 July 2023 / Online: 4 July 2023 (03:52:21 CEST)
How to cite:
Singh, G.; Kumar, P.; Mukherjee, S. Forest Fire Risk Mapping in Pauri Garhwal district of Uttarakhand. Preprints2023, 2023070132. https://doi.org/10.20944/preprints202307.0132.v1
Singh, G.; Kumar, P.; Mukherjee, S. Forest Fire Risk Mapping in Pauri Garhwal district of Uttarakhand. Preprints 2023, 2023070132. https://doi.org/10.20944/preprints202307.0132.v1
Singh, G.; Kumar, P.; Mukherjee, S. Forest Fire Risk Mapping in Pauri Garhwal district of Uttarakhand. Preprints2023, 2023070132. https://doi.org/10.20944/preprints202307.0132.v1
APA Style
Singh, G., Kumar, P., & Mukherjee, S. (2023). Forest Fire Risk Mapping in Pauri Garhwal district of Uttarakhand. Preprints. https://doi.org/10.20944/preprints202307.0132.v1
Chicago/Turabian Style
Singh, G., Pardeep Kumar and Saumitra Mukherjee. 2023 "Forest Fire Risk Mapping in Pauri Garhwal district of Uttarakhand" Preprints. https://doi.org/10.20944/preprints202307.0132.v1
Abstract
Forests, integral to human civilization, hold immense value and play a vital role in maintaining ecological harmony. Despite India's goal of extensive forest coverage, significant progress is still needed. Uncontrolled forest fires pose a severe threat, particularly in Uttarakhand's Pauri Garhwal district. To address this challenge, a comprehensive study examined surface and subsurface hydrological factors influencing the forest fire occurrences, such as elevation, aspect, slope, vegetation, proximity to human settlements, proximity to waterbodies, Active faults and lineament density. A total of 15 such factors were integrated with advanced techniques of remote sensing and GIS and coupled with historical fire data to create a precise forest fire risk map using the support vector machine algorithm. Forest fire risk map was classified into 5 distinct risk zones, Very High Risk (47.38 Km2), High Risk (275.98 km2, Moderate Risk (985.49 km2), Low Risk (1741.17 km2) and Very Low Risk (2374.11 km2) aiding in proactive fire management. By embracing this innovative tool, decision-makers can protect forests, preserve biodiversity, and ensure a sustainable future for generations to come.
Keywords
Forest Fire 1; Pauri-Gharwal 2; Surface and Subsurface Hydrology 3; Remote Sensing and GIS 4; Support Vector Machine 5
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
