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Canopy Cover Density and Height Distribution 2017-2022 (Tree Characteristics)

The Canopy Density and Canopy Height Distribution 2017–2022 dataset, part of the CoRE Stack, maps the spatial distribution of tree canopy height for the year 2017–2022. It provides insights into forest structure, biomass, and ecological integrity, supporting landscape-level conservation and restoration planning.

About Dataset

The Canopy Density 2017–2022 and Canopy Height Distribution 2017–2022 datasets are part of the CoRE Stack (Commoning for Resilience and Equality) — a digital public infrastructure supporting resilient and sustainable landscape management. The Canopy Density dataset quantifies tree canopy cover as a percentage of total land area, derived from satellite imagery using open-source algorithms and machine learning models, providing insights into vegetation density, forest condition, ecological health, forest degradation, carbon storage potential, and biodiversity. The Canopy Height Distribution dataset captures spatial variation in canopy height using satellite-based remote sensing and machine learning, supporting analysis of forest structure, vertical diversity, biomass distribution, carbon sequestration, and habitat complexity. When used together and integrated with other CoRE Stack layers such as Land Use and Land Cover, Terrain, and Hydrology, these datasets enable comprehensive socio-ecological assessments, monitoring of vegetation dynamics, and evaluation of ecological restoration outcomes. All datasets are harmonized for interoperability across analytical workflows and are actively applied in 200+ villages in India through partnerships with 15+ civil society organizations.

Technical details and methodologies are available in the CoRE Stack Technical Manual: https://core-stack.org/core-stack-technical-manual-v2/

Purpose of Dataset

The Purpose Of The Canopy Density And Canopy Height Distribution 2017–2022 Dataset Is To Assess And Monitor Vegetation And Forest Health By Quantifying The Percentage Of Tree Canopy Cover. It Supports Tracking Forest Degradation, Evaluating Restoration Progress, Estimating Carbon Storage, And Guiding Biodiversity Conservation. Integrated With Other Core Stack Datasets, It Enables Data-driven Landscape Planning And Helps Communities And Policymakers Make Informed Decisions For Sustainable Ecosystem Management And Climate Resilience.