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@article{180418,
        author = {Sakshi Santosh Deshmukh and Prof Dr K.A.Malgi and Saee Shriram Datar and Arpita Ravindra Dhage},
        title = {Intelligent Tree Enumeration And Forest Analysis System for Environmental Monitoring},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1386-1393},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180418},
        abstract = {Forest monitoring plays a critical role in sustainable environmental management, biodiversity conservation, and climate change mitigation. Traditional methods for tree enumeration, species classification, and green cover estimation are labour intensive, prone to human error, and inefficient for large-scale applications. This research presents an automated image-based forest monitoring system that integrates deep learning and remote sensing techniques to enhance accuracy and efficiency. The proposed framework serves as a robust tool for forest management authorities, policymakers, and researchers seeking data-driven solutions for environmental monitoring and conservation planning.},
        keywords = {GRVI, Machine Learning, NDVI, Random Forest, YOLOv8},
        month = {June},
        }