EcoScope – Framework for Tree Mapping and Species Classification for Sustainability

EcoScope (TreeTrackAI) is a modern AI-based forestry analytics system that can be easily integrated to enhance tree mapping and species monitoring in the Indian forest settings and later be functionalized to rural and urban areas as well. The conventional satellite-based methods have very low resolution, poor species identification, and inability to find understorey vegetation in thick, multi-layer forests. The fusion of aerial high-resolution images, multispectral data, and LiDAR point clouds by TreeTrackAI allows the accurate counting of trees, division of canopies, and initial classification according to species. The deep learning pipeline that uses multiple modalities and combines the detection with YOLO, canopy segmentation with U-Net, and LiDAR height modeling works to increase the accuracy in Indian terrains that are difficult to negotiate. The system comes up with a new kind of layered fusion of LiDAR that can reveal both the trees that make up the canopy and the hidden trees that form the understorey. A real-time processing engine and an interactive dashboard give access to the visualization of species distribution, canopy density, and region-wise ecological patterns by users such as forestry departments, NGOs, environmental researchers, and the like. EcoScope, by providing high-accuracy, season-robust, and region-specific analyses, helps in the conservation of biodiversity, forest planning, carbon stock estimation, and management of sustainable ecosystems.