The Nilgiri Biosphere Reserve (NBR) is one of the largest protected ecologically sensitive areas in India. This study examined the land use/land cover (LULC) changes in NBR for past 18 years from 2001 to 2018 to figure out the LULC changed within a protected area using datasets in 2001, 2010, and 2018 with the help of pertinent geospatial techniques. MODIS Land Cover Type Product (MCD12Q1) accuracy was quantitatively analyzed based on ground truth data and Google Earth imagery. Validation of data were assessed using and overall 635 locations for its accuracy assessment. The obtained kappa coefficient of 0.75, denotes the classification has moderate accuracy. The results showed that in the past 18 years, woody savannas and grasslands were reduced by 299.47 sq.km and 155.32 sq.km respectively. The areas of croplands and cropland/natural vegetation mosaics were also increased by 34.84 sq.km and 54.41 sq.km, respectively. These results showed anthropogenic influences through agricultural practices within the NBR buffer zones. The mixed forests were increased by 266.01 sq.km. One of the significant changes was seen in closed shrublands, which were absent in 2018, that covered 1.50 sq.km in 2001. In addition, A gradual decrease in the area were noticed in woody savannas. From the outcomes, it is recommended that the LULC classes that cover minimal area may be unstable, so measures should be taken for their conservation. The study proved the usefulness of MODIS land cover type data in monitoring large areas periodically for quick decision-making.

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.

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