Temporal Remote Sensing and GIS Analysis of Land Use/Land Cover Transitions: A Case Study in Annamayya District, Andhra Pradesh, India

Understanding and managing the changing landscape of our planet requires analyzing land use and land cover (LULC) transitions. This study combines remote sensing data and GIS analysis to uncover the intricate patterns and drivers behind these transitions. By integrating GIS analysis, we identify factors such as urbanization, agricultural expansion, deforestation, and natural resource management contributing to these changes. Accurate data preprocessing and calibration are emphasized to reduce errors and uncertainties in LULC maps. The study covers the period from 2017 to 2022, utilizing digitized LULC maps created with GIS tools and satellite data interpretation, specifically Sentinel-2 images. The landscape was classified into seven land cover types: agricultural land, built-up areas, barren or degraded land, flooded vegetation areas, forests, vegetation or shrub-covered areas, and waterbodies. Findings revealed a decrease of 1063.73 km2 in barren land between 2017 and 2022. Agricultural land expanded by 228.93 km2, forest land increased by 632.90 km2, and waterbodies grew by 33.05 km2. These changes suggest a conversion of areas likely influenced by the high intensity of rainfall between 2017 and 2022, leading to notable ecological consequences such as reduced soil erosion and improved biodiversity protection. The study's results have significant implications for land management, environmental protection, and sustainable development. The extensive analysis of spatial and temporal data equips policymakers, urban planners, and researchers with crucial knowledge to make well-informed decisions. This research provides a solid basis for monitoring and managing LULC transitions, offering valuable methodologies and insights to promote a resilient and harmonious coexistence between human activities and the environment.