Collection of thematic maps for the Peru - Pucallpa/Aguaytía agroforestry corridor

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This map collection integrates multi-source, multi-temporal Earth observation data and thematic maps to support multifunctional landscape analysis and monitoring in the Pucallpa–Aguaytía agroforestry corridor, Ucayali Region, Perú. Developed within the framework of the CGIAR Multifunctional Landscapes Science Program, the collection encompasses 70+ spatial layers organized across thematic categories: hydrological features, land cover dynamics, climate variables, ecosystem health indicators, human footprint measures, protected areas, physiographic characteristics, forests, biomass, carbon stocks, and location reference data. The collection employs a hierarchical approach to landscape characterization, combining fine-scale observations (30-meter resolution) with broader regional context. Temporal coverage spans four decades (1985-2025), enabling retrospective analysis of landscape transformation and current condition assessment. Core components include: (1) annual land cover classifications from MapBiomas Peru tracking land use change at five-year intervals; (2) climate variable analysis comparing recent observations (2024) against a 30-year baseline period (1981-2010) for evapotranspiration, temperature, and precipitation; (3) ecosystem integrity assessment using a composite index that integrates functional productivity (NPP), compositional diversity, and structural connectivity; (4) forest dynamics monitoring through Hansen Global Forest Change and GLAD datasets documenting deforestation patterns from 2000-2024; and (5) atmospheric pollution measurements from Sentinel-5P capturing carbon monoxide, nitrogen dioxide, ozone, and sulfur dioxide concentrations. Data integration follows standardized geospatial protocols with consistent geographic coverage focused on the Pucallpa–Aguaytía agroforestry corridor and surrounding buffer area, enabling cross-dataset analysis and multi-criteria evaluation. Raster datasets employ 30–90-meter spatial resolutions appropriate for landscape-scale assessment, while vector datasets maintain source-appropriate scales ranging from local to national coverage. The collection draws from authoritative international sources including NASA, ESA Copernicus, MODIS, WWF, USGS, TerraClimate and national Peruvian institutions (MINAM, INEI, IBC, and SENAMHI). Explore the web version in the Google Earth Engine app. Use online resources.https://ee-javierochoacip.projects.earthengine.app/view/mflpclperu The dataset related to this report is available here https://data.cipotato.org/dataset.xhtml?persistentId=doi:10.21223/P3/ZPHD7W

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agroforestry, land use, deforestation, remote sensing, carbon stock assessments

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