https://www.journalajgr.com/index.php/AJGR <p><strong>Asian Journal of Geographical Research</strong> <strong>(ISSN: 2582-2985) </strong>aims to publish high-quality papers (<a href="https://journalajgr.com/index.php/AJGR/general-guideline-for-authors">Click here for Types of paper</a>) in all areas of Geography and Earth Science. By not excluding papers based on novelty, this journal facilitates the research and wishes to publish papers as long as they are technically correct and scientifically motivated. The journal also encourages the submission of useful reports of negative results. This is a quality controlled, OPEN peer-reviewed, open-access INTERNATIONAL journal.</p> SCIENCEDOMAIN international en-US Asian Journal of Geographical Research 2582-2985 https://www.journalajgr.com/index.php/AJGR/article/view/407 <p>Land use and land cover (LULC) change is a fundamental indicator of environmental transformation, resource consumption and anthropogenic pressure on natural systems. This study presents a temporal analysis of LULC dynamics in Rewa District, Madhya Pradesh for the years 2020 and 2025, using Sentinel-2 multispectral imagery processed through the Google Earth Engine (GEE) cloud platform. A supervised Random Forest classification approach was adopted, integrating a comprehensive feature set comprising spectral bands, vegetation indices (NDVI, EVI, SAVI) water and built-up indices (MNDWI, NDBI, BSI) Grey Level Co-occurrence Matrix (GLCM) texture metrics and terrain derivatives (DEM, slope, aspect) from the SRTM dataset. A year (January–December) cloud-free median composites were used to minimise seasonal bias. Five LULC classes were mapped: Agriculture Land, Vegetation Land, Water Body, Built-up Land, and Waste Land. The classification achieved an Overall Accuracy of 94.59% and a Kappa coefficient of 0.9308 for 2020, and 95.45% and 0.9387 respectively for 2025. Post-classification change analysis reveals a landscape undergoing active transformation driven by agricultural intensification, rapid built-up expansion and large-scale wasteland reclamation. Agriculture Land remained dominant, expanding from 3,441 km² (54.5%) in 2020 to 3,548 km² (56.2%) in 2025. The Built-up Land class recorded the most dramatic proportional change, expanding by 113 km² (+44.66%), driven by highway corridor development along NH-30 and NH-27 and the creation of Mauganj as a new administrative district. Waste land declined most substantially by 239 km² (-13.87%), as ravines and degraded surfaces were reclaimed for cultivation and solar energy infrastructure. Forest cover recorded a marginal increase of 17 km² (+2.16%) attributable to open forest regeneration and social forestry on the Kaimur Range escarpment. The study demonstrates the utility of cloud-based geospatial analysis for regional LULC monitoring and provides a spatial evidence base for land management and development planning in Rewa District.</p> Manas Mishra Durgesh Kurmi Copyright (c) 2026 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2026-05-25 2026-05-25 9 3 1 16 10.9734/ajgr/2026/v9i3407