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@article{180110,
        author = {Lavanya G R and Kumaraswamy P and Ashwin M Hegde and Sahana S Gowda and Mrs. Deepthi Das.V},
        title = {Hyperspectral Water Monitoring System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {118-123},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180110},
        abstract = {—In today’s data-driven world, environmental 
monitoring demands scalable and intelligent systems to 
process complex satellite imagery. To address the 
challenges in surface water resource detection, we 
introduce a Flask-based web application that integrates 
deep learning with hyperspectral imaging. This system 
automates the classification of water and non-water 
bodies using CNN and GCN models trained on spectral 
bands. Hyperspectral images are preprocessed, 
analysed, and visualized in an intuitive interface that 
enables efficient decision-making. Unlike traditional 
methods that are costly and time-consuming, our 
solution offers rapid, accurate, and accessible surface 
water detection at scale.},
        keywords = {Hyperspectral Imaging, Water Resource  Monitoring, CNN, GCN, Satellite Imagery, Flask  Application, Deep Learning.},
        month = {May},
        }