Forest Fire Risk Zonation Using Remote Sensing and GIS Technology in Kansrao Forest Range of Rajaji National Park, Uttarakhand, India

Tahir Malik, Ghulam Rabbani, Majid Farooq

Abstract


Forest fire is a major cause of changes in forest structure and function. Forest fires are as old as forests themselves. Forest fires are one of the major natural risks in the Uttarakhand forests. In such areas, fires occur frequently and there is a need for supranational approaches that analyze wide scenarios of factors involved. It is impossible to control nature, but is possible to map forest fire risk zone and thereby minimize the frequency of fire. Forest and wild land fire are considered vital natural processes initiating natural exercises of vegetation succession. However uncontrolled and misuse of fire can cause tremendous adverse impacts on the environment and the human society. A risk model for fire spreading is set up for Kansrao Forest Range of Rajaji National Park where Forest and wild land fires have been taking place historically, shaping landscape structure, pattern and ultimately the species composition of ecosystems both flora and fauna. It is based upon a combination of remote sensing and GIS data. In this study, Resourcesat P6 – LISS III (spatial resolution 23.5m, 4 bands (Red) (Green) (NIR) (SWIR), Topo Sheet (SOI) no.53 J/4 on scale 1:50,000 and contour interval 20 meters, ASTER 30m and Garmin 72 GPS were used. For these analyses ArcGIS and ERDAS Imagine software was used. Land use information was obtained from the satellite images in this study. In this phase the distinction of species in the forest was determined using supervised classification. The lands that have priorities in case of fire were decided by combining the moisture of the land and slope classes that were determined by conventional approaches with the satellite images. The results of the analysis were shown by reports and graphs. The test region results should be applied all over Rajaji National Park.

 


Keywords


LISS, Forest Fire, Risk Zonation, DEM, Disaster

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