Monitoring land use and land cover (LULC) dynamics is essential for sustainable land management in regions experiencing rapid urbanization and environmental change. This study analyses the spatiotemporal transformation of LULC in Haridwar district, Uttarakhand, India, over a 15-year period (2008–2023) using multi-temporal Landsat imagery and a Support Vector Machine (SVM) classification approach within a GIS framework. Six LULC classes urban, agriculture, forest, water bodies, grassland, and sand were delineated for 2008, 2013, 2018, and 2023, with classification accuracies ranging from 85% to 89%. The results indicate a substantial expansion of urban (214.34%) and agricultural (19.75%) areas, driven largely by industrial growth, infrastructure development, and agrarian policies. In contrast, grasslands (−71.75%), sand (−53.65%), water bodies (−34.91%), and forests (−3.39%) declined, reflecting increasing anthropogenic pressures and ecological stress. These findings highlight the need for integrated land management and conservation strategies to balance economic development with environmental sustainability. The methodological framework and insights generated here can inform regional planning, climate adaptation, and policy interventions in rapidly transforming landscapes.
