Remote Sensing Metrics for Spatial Health Analysis


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Documentation for package ‘land4health’ version 0.3.0

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l4h_chirps Extract CHIRPS v3 precipitation data from Google Earth Engine
l4h_co_column Extracts carbon monoxide (CO) concentration from Sentinel-5P TROPOMI
l4h_dengue Extract dengue case data from OpenDengue
l4h_era5land Extract ERA5-Land climate variables from Google Earth Engine
l4h_forest_loss Extracts forest cover loss within a defined polygon
l4h_human_built Extracts built‑up surface area from GHSL Built‑Up Surface dataset
l4h_install Install Python dependencies for land4health package
l4h_list_metrics List available metrics in _land4health_
l4h_malaria Extract malaria metrics from the Malaria Atlas Project GeoServer
l4h_night_lights Extracts global night‑time lights using harmonized DMSP‑OLS and VIIRS data
l4h_packages List all _land4health_ packages
l4h_pm2_5 Extract Global PM2.5 (monthly) from Google Earth Engine
l4h_rural_access_index Compute Rural Access Index (RAI)
l4h_sebal_modis Download and process evapotranspiration data
l4h_surface_temp Extracts Land Surface Temperature (LST) from MODIS MOD11A1
l4h_terra_climate Extract TerraClimate variables (monthly) from Google Earth Engine
l4h_travel_time Travel Time to Healthcare or Cities (Oxford Dataset)
l4h_urban_heat_index Calculates the Surface Urban Heat Island (SUHI) index using MODIS LST and GHS-SMOD
l4h_urban_rural_area Extracts surface areas by urban and rural categories from GHS-SMOD
l4h_use_python Configure Python environment for land4health
l4h_vegetation Extract vegetation indices from MODIS MOD13A1