Monitoring Land Use and Land Cover Change of Forest Ecosystems of Shendurney Wildlife Sanctuary, Western Ghats, India

Abstract

Understanding forest degradation due to human and natural phenomena is crucial to conserving and managing remnant forest resources. However, forest ecosystem assessment over a large and remote area is usually complex and arduous. The present study on land use and land cover change detection of the Shendurney Wildlife Sanctuary forest ecosystems was carried out to utilize the potential application of remote sensing (RS) and geographic information system (GIS). Moreover, to understand the trend in the forest ecosystem changes. The supervised classification with Maximum Likelihood Algorithm and change detection comparison approach was employed to study the land use and land cover changes, using the Landsat Enhanced Thematic Mapper (ETM±) and Landsat 8 OLI-TIRS using data captured on July 01, 2001, and January 14, 2018. The study indicated the rigorous land cover changes. It showed a significant increase in the proportion of degraded forest with negligible gain in the proportion of evergreen forest from 21.31% in 2001 to 22.97% in 2018. A substantial loss was also observed in moist deciduous from 27.11 % in 2001 to 17.23 % in 2018. The result of the current study indicated the degree of impacts on forests from the various activities of their surroundings. This study provides baseline information for planning and sustainable management decisions.

Monitoring of Land use/ land cover changes of Daying Ering Wildlife Sanctuary, Arunachal Pradesh, India, using Remote Sensing and Geographic Information System

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Globally, researchers have extensively studied the changes in Land use/ Land cover (LULC) using Remote Sensing (RS) and Geographical Information System (GIS) and have concluded that LULC must be conducted regularly (Annayat et al 2022;Lodhi et al 2014). Understanding LULC of a particular area, more unfortunately so, if a protected area, is an important question for holistic management and the locals living in proximity (Mutanga et al 2015;Bilyaminu et al 2021). With the application of remote sensing, it has been made possible to study the patterns of changes in land use/land cover at low cost, less time and high accuracy (Kachhwaha 1985).

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