A comprehensive exploration of land use dynamics, NDVI trends, and stakeholder engagement for crafting sustainable green spaces
Keywords:
Random forest, machine learning, land use/land cover, change detection, green spaceAbstract
This study analyzes three decades of urbanization, land use changes, and green space dynamics in Bhilwara, Rajasthan. Employing a comprehensive methodology blending quantitative analysis, geospatial techniques, and stakeholder engagement, the city's transformation is unveiled. Built-up areas expanded from 12 to 32 square kilometers, indicative of rapid urbanization, coupled with declines in cropland and deciduous forests. The integration of Land Use and Land Cover (LULC) classification and Normalized Difference Vegetation Index (NDVI) analysis exposes ecological impacts, with declining NDVI values suggesting challenges to vegetative health. Stakeholder engagement proved crucial in understanding the dynamics of green space management. The study identified varying levels of involvement among authorities, local bodies, and the community, emphasizing the importance of collaborative governance in urban development and environmental conservation. The study concludes with a sustainable urban green spaces model, encompassing green infrastructure planning, diverse land use practices, sustainable maintenance, community engagement, technology integration, and biodiversity conservation. These recommendations aim to guide future urban planning efforts in Bhilwara, providing actionable insights for policymakers, urban planners, and community stakeholders alike. The study acknowledges limitations, including reliance on remote sensing data, emphasizing the need for continuous monitoring and suggests future research directions exploring socio-economic implications and cultural significance. This research offers a comprehensive analysis of Bhilwaras’ urban transformation and provides a robust framework for enhancing urban su