Analyzing Land Use Change and Fragmentation Using Earth Observation Data: A Case Study of the Ken River Basin, India
Ankush V. Lal
Department of Civil Engineering, Vaugh Institute of Agricultural Engineering and Technology, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh, India.
R. K. Pandey
Department of Civil Engineering, Vaugh Institute of Agricultural Engineering and Technology, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh, India.
Easterlily Shylla
Centre for Geospatial Technologies, Vaugh Institute of Agricultural Engineering and Technology, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh, India.
Arnab Kundu
Department of Geo-Informatics, Pandit Raghunath Murmu Smriti Mahavidyalaya, Bankura University, West Bengal, India.
Mukesh Kumar *
Centre for Geospatial Technologies, Vaugh Institute of Agricultural Engineering and Technology, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
Land use/land cover (LULC) are a critical concern due to their significant impact on ecosystems, biodiversity, and climate patterns. The objective of this study is to understand the dynamics of land use and land cover (LULC) changes and quantify the fragmentation in the Ken River Basin using open-access remote sensing data and the FRAGSTATS software. Landsat images from 1995, 2015, and 2022 were utilized to analyze changes over these distinct time periods. We employed supervised classification using the maximum likelihood method to produce detailed land use and land cover maps. The analysis identified five land use classes: water bodies, forest, barren land, cultivable land, and built-up land, with cultivable land emerging as the most dominant class, followed closely by forest cover. To quantify the land cover classes, various landscape metrics at the class level were employed. The results reveal a concerning trend: both forest and cultivable land classes are experiencing increasing fragmentation over time. This rising fragmentation poses significant risks to the ecological integrity and sustainability of the Ken River Basin. By quantifying long-term land cover changes, this study assesses the effectiveness of conservation efforts and utilizes remote sensing and GIS techniques to inform and enhance best management practices in the region.
Keywords: LULC, fragmentation, landscape metrics, ecosystems, biodiversity, climate patterns