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Land Use Land Cover (2005-2024)

The Land Use and Land Cover (LULC) 2005–2024 dataset, developed under the CoRE Stack, maps landscape features such as agricultural land, forest cover, water bodies, and built-up areas for the year 2005–2024. It supports natural resource management and landscape sustainability planning.

About Dataset

The Land Use and Land Cover (LULC) 2005–2024 dataset is part of the CoRE Stack (Commoning for Resilience and Equality) — a digital public infrastructure designed to strengthen the sustainability and resilience of rural landscapes. This dataset provides spatial classifications of land use and land cover for 2017–2024, depicting patterns of agriculture, forest and plantation areas, waterbodies, settlements, and other land categories. Built from open satellite imagery and machine learning pipelines, it follows standardized geospatial processing methods to ensure consistency with other CoRE Stack datasets across years. Together with additional socio-ecological indicators, this dataset enables data-driven planning, monitoring, and collaborative landscape management. Currently, CoRE Stack datasets inform landscape action in over 200 villages across India, in collaboration with 15+ civil society organizations. Further enhancements, such as integration with climate projections and social-hydrological modeling, are ongoing.

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 Core Stack Data Is To Support Sustainable And Resilient Landscape Management By Providing Geospatial And Socio-ecological Datasets That Help Communities, Researchers, And Policymakers Monitor Land Use, Water Resources, Vegetation, And Socio-economic Indicators. It Enables Data-driven Decision-making, Collaborative Planning, And Impact Assessment For Rural And Environmental Development Projects. Through Open Data, Analytical Models, And Digital Dashboards, The Core Stack Empowers Local Stakeholders To Understand Environmental Changes, Plan Restoration Activities, And Align Resources For Long-term Ecological Balance And Community Well-being.