Temporal and Spatial Dynamics of Land Use and Land Cover in Shirur Kasar Tehsil, Maharashtra Using Geospatial Technology

Abstract

Geographical information systems and Remote Sensing has become efficient tool for land use and land cover classification. This study was conducted in Shirur Kasar Tehsil, in the Beed district of Maharashtra, India. Multispectral images of the Landsat 8 satellite were downloaded from USGS, and a resolution of 30 m was used for this study. The processing of images was done in Arc GIS, which provides various tools and functions for image classification. The maximum likelihood supervised classification technique was used for land use land cover classification. Land use and land cover (LULC) classification was conducted for the years 2014, 2019, and 2024, spanning a decade. During the period from 2014 to 2019, agricultural land and vegetation declined by 9% and 12%, respectively, while barren land, settlement, and water bodies increased by 1%, 31%, and 81%, respectively. From 2019 to 2024, barren land and water bodies decreased by 13% and 58%, respectively, whereas agricultural land, settlement, and vegetation increased by 9%, 5%, and 19%, respectively. Significant changes were observed over the entire study period (2014–2024), particularly in settlement areas, which
exhibited a continuous increase. Conversely, barren land demonstrated a notable decrease. These findings highlight the dynamic shifts in LULC classes over the decade. The study reveals substantial land use change in the study area, which was in settlement. It was increased by 38% due to increased population, migration from rural to urban areas, and demand for settlements. Accuracy assessment was done using the Kappa Coefficient method; according to the Kappa Coefficient, overall accuracy for the years 2014, 2019, and 2024 was found to be 90%, 90%, and 95%, respectively, with Kappa Coefficients 0.9, 0.9, and 0.95. Based on these results, the
accuracy and kappa coefficient values have good criteria and can be used for further analysis.