ESA-eodashboards · AparicioSF · Sep 9, 2025 · Sep 9, 2025 · Sep 9, 2025 · Sep 9, 2025
diff --git a/catalogs/trilateral.json b/catalogs/trilateral.json
@@ -1,151 +1,153 @@
 {
-    "id": "trilateral",
-    "title": "Earth Observing Dashboard",
-    "description": "A Tri-Agency Dashboard by NASA, ESA, JAXA",
-    "endpoint": "https://eurodatacube.github.io/eodash-catalog/trilateral/",
-    "geodb_default_form": "https://santilland.github.io/process_example/definitions/geodbform.json",
-    "geodb_default_vega": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/geodb_vega_definition.json",
-    "default_xcube_process": {
-        "JsonForm": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/xcube_form.json",
-        "VegaDefinition": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/xcube_vega.json",
-        "EndPoints": [
-        {
-            "Identifier": "xcube_statistics",
-            "Method": "POST",
-            "Body": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/xcube_body.json",
-            "Type": "application/json"
-        }]
-    },
-    "assets_endpoint": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/main/collections",
-    "default_base_layers": "layers/baselayers",
-    "default_overlay_layers": "layers/overlays",
-    "collections": [
-        "E9_car_containers",
-        "N1_NO2",
-        "N1_methane_monitoring",
-        "N1_CO",
-        "N1_SO2",
-        "N1_NO2_monthly",
-        "N1_NO2_diff_monthly",
-        "N1_NO2_city_trilateral",
-        "N2_CO2_mean",
-        "N2_CO2_diff",
-        "facebook_population_density",
-        "N9_OMI_trno2-COG",
-        "NPP_ocean_primary_productivity",
-        "NPPN_net_primary_production",
-        "SITI_IS2SITMOGR4-cog",
-        "nceo_africa_2017",
-        "grdi-v1-built",
-        "grdi-v1-raster",
-        "grdi-shdi-raster",
-        "grdi-vnl-slope-raster",
-        "grdi-vnl-raster",
-        "grdi-filled-missing-values-count",
-        "grdi-imr-raster",
-        "grdi-cdr-raster",
-        "N10_OMSO2PCA-COG",
-        "SIE_sea_ice_thickness_envisat",
-        "SIC_sea_ice_thickness_cryosat",
-        "NASAPopulation",
-        "WSF_world_settlement_footprint_ind",
-        "N12_sea_ice_concentration_antarctic",
-        "N12_1_sea_ice_concentration_arctic",
-        "E10e_ndvi",
-        "N11_ocean_primary_productivity",
-        "SMC_soil_moisture_anomaly",
-        "PRC_precipitation_anomaly",
-        "PRCG_precipitation",
-        "E10a1_agricultural_production_productive_area",
-        "E10a2_agricultural_production_area",
-        "E10a3_agricultural_production_area_change",
-        "E10a6_harvested_parcels_evolution",
-        "E10a8_winter_cereals",
-        "E10c_rice_planting",
-        "N2_greenhouse_gases",
-        "VITS_vegetation_index_timeseries",
-        "SMCTS_soil_moisture_timeseries",
-        "PRCTS_precipitation_timeseries",
-        "LWE_lake_water_extent",
-        "LWL_lake_water_level",
-        "NLK_lakes",
-        "Lakes_S2L2A",
-        "Lakes_ALOS2",
-        "Lakes_Sentinel1",
-        "Lakes_SWT",
-        "Lakes_WQ_TC_water_quality",
-        "Lakes_WQ_TURB_water_turbidity",
-        "SMCG_soil_moisture_content",
-        "SIF_solar_induced_chlorophyll_fluorescence",
-        "N5_nightlights",
-        "N6_geoglam",
-        "CDS7_windu_ERA5-SingleLevel_100m_GLOBAL",
-        "CDS8_windv_ERA5-SingleLevel_100m_GLOBAL",
-        "N3b_water_quality_tsm_chart",
-        "N3b_water_quality_chl_chart",
-        "N3a2_chl_concentration_tri_esa",
-        "N3a2_chl_concentration_tri_jaxa",
-        "N3a2_chl_concentration_tri_nasa",
-        "N3a2_total_suspended_matter_tri_esa",
-        "N3a2_total_suspended_matter_tri_jaxa",
-        "N3a2_total_suspended_matter_tri_nasa",
-        "N3a2_sea_surface_temperature",
-        "N1_NO2_jaxa",
-        "N2_CO2_jaxa_gosat",
-        "GHS_BUILT-S-R2023A",
-        "RECCAP2_1_AGC_LVOD_amazonia_methods_mean_crop",
-        "RECCAP2_2_AGC_LVOD_amazonia_smooth_max_crop",
-        "RECCAP2_3_AGC_LVOD_amazonia_smooth_mean_crop",
-        "RECCAP2_4_AGC_LVOD_amazonia_trend_mean_crop",
-        "RECCAP2_5_SF_biomass_growth",
-        "RECCAP2_6_deforested_biomass",
-        "RECCAP2_7_degraded_biomass",
-        "RECCAP2_8_edge_biomass_change",
-        "RECCAP2_9_intact_biomass_change_methods_mean",
-        "RECCAP2_10_intact_biomass_change_smooth_max",
-        "RECCAP2_11_intact_biomass_change_smooth_mean",
-        "RECCAP2_12_intact_biomass_change_trend_mean",
-        "GGI_CO2",
-        "GGI_N2O",
-        "GGI_CH4",
-        "ESDC_gross_primary_productivity",
-        "ESDC_kndvi",
-        "ESDC_net_ecosystem_exchange",
-        "GG_Google_Mobility_Data_trilateral",
-        "E13c_shipping_activity",
-        "E13b_parked_airplanes",
-        "CV_Covid_19_cases_trilateral",
-        "OW_Covid_19_vaccinations_trilateral",
-        "FNF_Palsar",
-        "Modis_SNPP_2023",
-        "ADD_West_Antarctica_S1",
-        "ADD_Landsat_L2_Antarctica",
-        "ADD_Melt_Duration",
-        "ADD_Melt_Onset",
-        "ADD_Melt_Season_End",
-        "ADD_Meltmap",
-        "ESDL_Hydrology_SM",
-        "ESDL_Hydrology_Precipitation",
-        "MCD_S14Amazonas_detections",
-        "EPA_Field_burning_Monthly",
-        "EPA_Forest_fire_Methane_Daily",
-        "EPA_Forest_fire_Methane_Yearly",
-        "HLS_NDVI",
-        "LIS_Global_DA_Evap",
-        "NTLU_JAXA_Nighttimelevel_Urban",
-        "NTLR_JAXA_Nighttimelevel_Rural",
-        "4D_Greenland_Duration",
-        "4D_Greenland_Melt_Onset",
-        "4D_Greenland_Melt_Season_End",
-        "4D_Greenland_Meltmap",
-        "ENSST_by_GCOM-W-AMSR_JAXA",
-        "SLSTR1_Sentinel-3-SLSTR-L2-LST",
-        "SSLC1_Seasonal_S1_AMP_hv_interferometric_coherence",
-        "SSLC2_Seasonal_S1_COH12_hh_interferometric_coherence",
-        "OHC300_Ocean_Heat_Content_upper_300m",
-        "NELST_ECOSTRESS_LST",
-        "alos2_floods",
-        "SMOS_ocean_salinity",
-        "SMOS_soil_moisture"
+  "id": "trilateral",
+  "title": "Earth Observing Dashboard",
+  "description": "A Tri-Agency Dashboard by NASA, ESA, JAXA",
+  "endpoint": "https://eurodatacube.github.io/eodash-catalog/trilateral/",
+  "geodb_default_form": "https://santilland.github.io/process_example/definitions/geodbform.json",
+  "geodb_default_vega": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/geodb_vega_definition.json",
+  "default_xcube_process": {
+    "JsonForm": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/xcube_form.json",
+    "VegaDefinition": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/xcube_vega.json",
+    "EndPoints": [
+      {
+        "Identifier": "xcube_statistics",
+        "Method": "POST",
+        "Body": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/refs/heads/main/defaults/xcube_body.json",
+        "Type": "application/json"
+      }
     ]
+  },
+  "assets_endpoint": "https://raw.githubusercontent.com/eurodatacube/eodash-assets/main/collections",
+  "default_base_layers": "layers/baselayers",
+  "default_overlay_layers": "layers/overlays",
+  "collections": [
+    "E9_car_containers",
+    "N1_NO2",
+    "N1_methane_monitoring",
+    "N1_CO",
+    "N1_SO2",
+    "N1_NO2_monthly",
+    "N1_NO2_diff_monthly",
+    "N1_NO2_city_trilateral",
+    "N2_CO2_mean",
+    "N2_CO2_diff",
+    "facebook_population_density",
+    "N9_OMI_trno2-COG",
+    "NPP_ocean_primary_productivity",
+    "NPPN_net_primary_production",
+    "SITI_IS2SITMOGR4-cog",
+    "nceo_africa_2017",
+    "grdi-v1-built",
+    "grdi-v1-raster",
+    "grdi-shdi-raster",
+    "grdi-vnl-slope-raster",
+    "grdi-vnl-raster",
+    "grdi-filled-missing-values-count",
+    "grdi-imr-raster",
+    "grdi-cdr-raster",
+    "N10_OMSO2PCA-COG",
+    "SIE_sea_ice_thickness_envisat",
+    "SIC_sea_ice_thickness_cryosat",
+    "NASAPopulation",
+    "WSF_world_settlement_footprint_ind",
+    "N12_sea_ice_concentration_antarctic",
+    "N12_1_sea_ice_concentration_arctic",
+    "E10e_ndvi",
+    "N11_ocean_primary_productivity",
+    "SMC_soil_moisture_anomaly",
+    "PRC_precipitation_anomaly",
+    "PRCG_precipitation",
+    "E10a1_agricultural_production_productive_area",
+    "E10a2_agricultural_production_area",
+    "E10a3_agricultural_production_area_change",
+    "E10a6_harvested_parcels_evolution",
+    "E10a8_winter_cereals",
+    "E10c_rice_planting",
+    "N2_greenhouse_gases",
+    "VITS_vegetation_index_timeseries",
+    "SMCTS_soil_moisture_timeseries",
+    "PRCTS_precipitation_timeseries",
+    "LWE_lake_water_extent",
+    "LWL_lake_water_level",
+    "NLK_lakes",
+    "Lakes_S2L2A",
+    "Lakes_ALOS2",
+    "Lakes_Sentinel1",
+    "Lakes_SWT",
+    "Lakes_WQ_TC_water_quality",
+    "Lakes_WQ_TURB_water_turbidity",
+    "SMCG_soil_moisture_content",
+    "SIF_solar_induced_chlorophyll_fluorescence",
+    "N5_nightlights",
+    "N6_geoglam",
+    "CDS7_windu_ERA5-SingleLevel_100m_GLOBAL",
+    "CDS8_windv_ERA5-SingleLevel_100m_GLOBAL",
+    "N3b_water_quality_tsm_chart",
+    "N3b_water_quality_chl_chart",
+    "N3a2_chl_concentration_tri_esa",
+    "N3a2_chl_concentration_tri_jaxa",
+    "N3a2_chl_concentration_tri_nasa",
+    "N3a2_total_suspended_matter_tri_esa",
+    "N3a2_total_suspended_matter_tri_jaxa",
+    "N3a2_total_suspended_matter_tri_nasa",
+    "N3a2_sea_surface_temperature",
+    "N1_NO2_jaxa",
+    "N2_CO2_jaxa_gosat",
+    "GHS_BUILT-S-R2023A",
+    "RECCAP2_1_AGC_LVOD_amazonia_methods_mean_crop",
+    "RECCAP2_2_AGC_LVOD_amazonia_smooth_max_crop",
+    "RECCAP2_3_AGC_LVOD_amazonia_smooth_mean_crop",
+    "RECCAP2_4_AGC_LVOD_amazonia_trend_mean_crop",
+    "RECCAP2_5_SF_biomass_growth",
+    "RECCAP2_6_deforested_biomass",
+    "RECCAP2_7_degraded_biomass",
+    "RECCAP2_8_edge_biomass_change",
+    "RECCAP2_9_intact_biomass_change_methods_mean",
+    "RECCAP2_10_intact_biomass_change_smooth_max",
+    "RECCAP2_11_intact_biomass_change_smooth_mean",
+    "RECCAP2_12_intact_biomass_change_trend_mean",
+    "GGI_CO2",
+    "GGI_N2O",
+    "GGI_CH4",
+    "ESDC_gross_primary_productivity",
+    "ESDC_kndvi",
+    "ESDC_net_ecosystem_exchange",
+    "GG_Google_Mobility_Data_trilateral",
+    "E13c_shipping_activity",
+    "E13b_parked_airplanes",
+    "CV_Covid_19_cases_trilateral",
+    "OW_Covid_19_vaccinations_trilateral",
+    "FNF_Palsar",
+    "Modis_SNPP_2023",
+    "ADD_West_Antarctica_S1",
+    "ADD_Landsat_L2_Antarctica",
+    "ADD_Melt_Duration",
+    "ADD_Melt_Onset",
+    "ADD_Melt_Season_End",
+    "ADD_Meltmap",
+    "ESDL_Hydrology_SM",
+    "ESDL_Hydrology_Precipitation",
+    "MCD_S14Amazonas_detections",
+    "EPA_Field_burning_Monthly",
+    "EPA_Forest_fire_Methane_Daily",
+    "EPA_Forest_fire_Methane_Yearly",
+    "HLS_NDVI",
+    "LIS_Global_DA_Evap",
+    "NTLU_JAXA_Nighttimelevel_Urban",
+    "NTLR_JAXA_Nighttimelevel_Rural",
+    "4D_Greenland_Duration",
+    "4D_Greenland_Melt_Onset",
+    "4D_Greenland_Melt_Season_End",
+    "4D_Greenland_Meltmap",
+    "ENSST_by_GCOM-W-AMSR_JAXA",
+    "SLSTR1_Sentinel-3-SLSTR-L2-LST",
+    "SSLC1_Seasonal_S1_AMP_hv_interferometric_coherence",
+    "SSLC2_Seasonal_S1_COH12_hh_interferometric_coherence",
+    "OHC300_Ocean_Heat_Content_upper_300m",
+    "NELST_ECOSTRESS_LST",
+    "alos2_floods",
+    "SMOS_ocean_salinity",
+    "SMOS_soil_moisture",
+    "grdi"
+  ]
 }
diff --git a/collections/grdi.json b/collections/grdi.json
@@ -0,0 +1,20 @@
+{
+  "Name": "GRDIv1",
+  "EodashIdentifier": "GRDIv1",
+  "Title": "Global Gridded Relative Deprivation Index (GRDI)",
+  "Description": "# Global Gridded Relative Deprivation Index \nThe **Global Gridded Relative Deprivation Index (GRDI)**, Version 1 (GRDIv1) dataset  characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a **value of 100 represents the highest level of deprivation and a value of 0 the lowest**.\n\n### Creation of GRDIv1:\nGRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into **six main components** (described bellow) to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage. GRDIv1 has six input components, or dimensions, that are combined to determine the degree of relative deprivation:\n\n* **1) The child dependency ratio (CDR):** defined as the ratio between the population of children (ages 0 to 14) to the working-age population (age 15 to 64), where a higher ratio implies a higher dependency on the working population (UN DESA 2006). CDR is intreperted as a dimension where higher dependency ratios are generally associated with younger age structures, implying higher relative deprivation.\n* **2) Infant mortality rates (IMRs):** Is defined as the number of deaths in children under 1 year of age per 1,000 live births in the same year, are a common indicator of population health (Reidpath & Allotey, 2003; Schell et al., 2007). Higher IMRs imply higher deprivation.\n* **3) The Subnational Human Development Index (SHDI):** attempts to assess human well-being through a combination of “three dimensions: education, health, and standard of living (Smits & Permanyer, 2019)”. Lower SHDIs imply higher deprivation.\n* **4) Global rural populations:** are more likely to experience a higher degree of multidimensional poverty when compared to urban populations, other things being equal (Castañeda et al., 2018; Laborde Debucquet & Martin, 2018; Lee & Kind, 2021; UN DESA, 2021; UNDP & OPHI, 2020). Therefore, low values of the ratio of built-up area to non-built up area (BUILT) imply higher deprivation.\n* **5) Intensity of nighttime lights:** are closely associated with anthropogenic activities, economic output, and infrastructure development (Elvidge et al., 2007; Ghosh et al., 2013; Lu et al., 2021; Small et al., 2013). Low values of nighttime lights for the year 2020 (VIIRS Night Lights (**VNL**) 2020) imply higher deprivation.\n* **6) Linear regression from annual VNL data between 2012 and 2020 (VNL slope)**: higher values (increasing brightness) imply decreasing deprivation and lower values (decreasing brightness) imply increasing deprivation.  \n\n### GRDIv1 Citation\nCenter For International Earth Science Information Network-CIESIN-Columbia University. (2022). <i>Global Gridded Relative Deprivation Index (GRDI), Version 1</i> (Version 1.00) [Data set]. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/3XXE-AP97 ",
+  "Resources": [
+    {
+      "Name": "VEDA",
+      "EndPoint": "https://openveda.cloud/api/stac/",
+      "Type": "cog",
+      "CollectionId": "grdi-v1-raster",
+      "Bidx": 1,
+      "Rescale": [
+        0,
+        100
+      ],
+      "ColormapName": "viridis"
+    }
+  ]
+}