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@article{189812,
        author = {Dr. P. Ganesh and Dr.M.Mohamed Ismail and Dr.P.Karthi},
        title = {Deep Learning–Driven Assessment of Urban Water Body Encroachment and its Socio-Environmental Impact in Tamil Nadu},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {1485-1490},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189812},
        abstract = {This study leverages a deep learning framework to systematically assess the encroachment dynamics of urban water bodies in Tamil Nadu, India, and quantify their cascading socio-environmental impacts. Utilizing a multi-temporal analysis of high-resolution satellite imagery, we implement an attention-based U-Net algorithm for precise semantic segmentation and change detection to delineate water body boundaries and identify illegal settlements, land reclamation, and infrastructure development over the past two decades. The algorithm’s efficacy is enhanced by its ability to focus on critical spatial features amidst complex urban landscapes, providing high-accuracy encroachment maps. Subsequently, these geospatial outputs are integrated with socio-economic datasets—including groundwater levels, flood incidence records, and urban heat island metrics—within a GIS environment to model impacts such as increased flood vulnerability, loss of livelihood for dependent communities, groundwater depletion, and localized micro-climatic changes. The research establishes a direct, data-driven correlation between the rate of encroachment and the degradation of ecosystem services, offering a scalable, automated tool for urban planners and policymakers to prioritize conservation efforts, enforce regulatory measures, and design mitigation strategies for sustainable urban water resource management.},
        keywords = {Deep Learning; Water Body Encroachment; Semantic Segmentation; Socio-Environmental Impact; Tamil Nadu.},
        month = {January},
        }