Global Urban Rural Vegetation Dataset

Overview This dataset supports the study "Global urban-rural contrasts in vegetation amount, subtype, and structure modulated by background climate and socioeconomic conditions." It contains processed CSV files representing vegetation characteristics across 83,102 urban clusters globally. The data includes analysis of vegetation cover, structural metrics (LAI, Tree Height), and temporal trends from 1990 to 2020. Data Sources Land Cover: ESA WorldCover 2020 (10m), Landsat-based Global Land CoverStructure: Sentinel-2 (for LAI), Meta Canopy Height (1m)Climate/Socioeconomic: Koppen-Geiger climate classification, World Bank income groups (Global North/South) Vegetation cover (ESA WorldCover) urbanRural_VegBiomeKoppen_withLatLon_with_countries.csv urbanRural_VegBiomeKoppen_withLatLon_with_countries_global_ns.csv Leaf area index (LAI) urbanRuralLAI_with_countries_veg.csv urbanRuralLAI_with_countries_global_ns_veg.csv Tree height (Meta canopy height) urbanRural_TreesBiomeKoppen_withLatLon_with_countries.csv Vegetation indices (NDVI & EVI) EVI urbanRural_EVIBiomeKoppen_withLatLon_with_countries_global_ns.csv urbanRural_EVIBiomeKoppen_withLatLon_with_countries.csv Country-level temporal EVI change between 1990 and 2020 urbanEVI_1990_perCountry.csv urbanEVI_2020_perCountry.csv NDVI urbanRural_NDVIBiomeKoppen_withLatLon_with_countries_global_ns.csv urbanRural_NDVIBiomeKoppen_withLatLon_with_countries.csv Country-level temporal NDVI change between 1990 and 2020 urbanNDVI_1990_perCountry.csv urbanNDVI_2020_perCountry.csv Country-level temporal analysis: fixed urban extents (1990 & 2020) Vegetation vegUrban_1990_2020_constBuiltUp2020_100m.csv vegUrban_1990_2020_constBuiltUp1992_100m.csv Tree treeUrban_1990_2020_constBuiltUp2020_100m.csv treeUrban_1990_2020_constBuiltUp1992_100m.csv Temporal change (1990 vs 2020) Vegetation vegUrban_2020_constBuiltUp2020_100m.csv vegUrban_1990_constBuiltUp1992_100m.csv Tree treeUrban_2020_constBuiltUp2020_100m.csv treeUrban_1990_constBuiltUp1992_100m.csv Crop croplandUrban_1990_constBuiltUp1990_100m.csv croplandUrban_2020_constBuiltUp2020_100m.csv Grass grassUrban_1990_constBuiltUp1990_100m.csv grassUrban_2020_constBuiltUp2020_100m.csv Shrub shrubUrban_1990_constBuiltUp1990_100m.csv shrubUrban_2020_constBuiltUp2020_100m.csv Temporal change: 5-Year increments Vegetation vegUrban1990.csv vegUrban1995.csv vegUrban2000.csv vegUrban2005.csv vegUrban2010.csv vegUrban2015.csv vegUrban2020.csv Tree treeUrban1990.csv treeUrban1995.csv treeUrban2000.csv treeUrban2005.csv treeUrban2010.csv treeUrban2015.csv treeUrban2020.csv Climate zone analysis Vegetation urbanVegetationClimate_1990_2020_tropical.csv urbanVegetationClimate_1992_2020_arid.csv urbanVegetationClimate_1990_2020_continental.csv urbanVegetationClimate_1990_2020_temperate_100m.csv Tree urbanTreeCover_1992_2020_tropical.csv urbanTreeCover_1992_2020_continental.csv urbanTreeCover_1992_2020_arid.csv urbanTreeCover_1992_2020_temperate.csv Code Associated Google Earth Engine and Python code to generate these datasets and perform analysis as described in the paper: https://github.com/Rohit18/GlobalUrbanRuralVegetation v0.1-beta