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Merge pull request #2511 from eurodatacube/adding-biomass-data
feat: add 5 new biomass datasets from VEDA
2 parents d46c297 + 9ef7f3f commit c82066e

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## Gridded 2012 EPA Methane Emissions - Field Burning (monthly)
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## Dataset Description:
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Dataset represents a gridded inventory of U.S. anthropogenic methane emissions from various sources. The inventory is designed to be consistent with the 2016 U.S. EPA [Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.
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This data can be used by researchers to better compare the national-level inventory with measurement results that may be at other scales.
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- Resolution: 0.1° x 0.1°
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- GeographicalCoverage: North America (-128, 23, -72, 52)
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- TemporalAvailability: 2012-01-01 - 2012-12-31
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- TemporalResolution: monthly
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- Provider: "[EPA](https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions)"
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- Host: "[VEDA](https://www.earthdata.nasa.gov/esds/veda)"
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## Data Access
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- "[VEDA Catalog](https://staging-stac.delta-backend.com/collections/EPA-monthly-emissions_4F_Field_Burning)"
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## Gridded 2012 EPA Methane Emissions - Forest Fires (daily)
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## Dataset Description:
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Dataset represents a gridded inventory of U.S. anthropogenic methane emissions from various sources. The inventory is designed to be consistent with the 2016 U.S. EPA [Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.
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This data can be used by researchers to better compare the national-level inventory with measurement results that may be at other scales.
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- Resolution: 0.1° x 0.1°
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- GeographicalCoverage: North America (-128, 23, -72, 52)
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- TemporalAvailability: 2012-01-01 - 2012-12-31
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- TemporalResolution: daily
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- Provider: "[EPA](https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions)"
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- Host: "[VEDA](https://www.earthdata.nasa.gov/esds/veda)"
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## Data Access
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- "[VEDA Catalog](https://staging-stac.delta-backend.com/collections/EPA-daily-emissions_5_Forest_Fires)"
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## Gridded 2012 EPA Methane Emissions - Forest Fires
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## Dataset Description:
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Dataset represents a gridded inventory of U.S. anthropogenic methane emissions from various sources. The inventory is designed to be consistent with the 2016 U.S. EPA [Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.
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This data can be used by researchers to better compare the national-level inventory with measurement results that may be at other scales.
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- Resolution: 0.1° x 0.1°
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- GeographicalCoverage: North America (-128, 23, -72, 52)
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- TemporalAvailability: 2012-01-01 - 2012-12-31
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- TemporalResolution: yearly composite
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- Provider: "[EPA](https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions)"
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- Host: "[VEDA](https://www.earthdata.nasa.gov/esds/veda)"
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## Data Access
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- "[VEDA Catalog](https://staging-stac.delta-backend.com/collections/EPA-annual-emissions_5_Forest_Fires)"
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## Normalized difference vegetation index from HLS
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## Dataset Description:
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Dataset represents a NDVI calculated from Harmonized Landsat and Sentinel-2 Data over Punta Gorda, Florida, USA.
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- GeographicalCoverage: [-82.37,26.31,-81.9,27.03]
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- TemporalAvailability: 2022-09-05 - 2022-09-30
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- TemporalResolution: individual dates
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- Host: "[VEDA](https://www.earthdata.nasa.gov/esds/veda)"
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## Data Access
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- "[VEDA Catalog](https://staging-stac.delta-backend.com/collections/hls-ndvi)"
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# Evapotranspiration - LIS 10km Global DA
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## Dataset Description:
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Dataset represents Gridded total evapotranspiration (in kg m-2 s-1) from 10km global LIS with assimilation.
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- Resolution: 10km
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- GeographicalCoverage: Global
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- TemporalAvailability: 2002-08-02 - 2021-12-01
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- TemporalResolution: daily
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- Host: "[VEDA](https://www.earthdata.nasa.gov/esds/veda)"
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## Data Access
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- "[VEDA Catalog](https://staging-stac.delta-backend.com/collections/lis-global-da-evap)"
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app/public/legends/legends.json

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"cm": [[0, [56, 56, 148]], [2,[82, 133, 140]], [4,[111, 213, 132]], [6,[136, 210, 111]], [8,[155, 116, 78]], [10,[175, 28, 47]]],
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"label": "Turbidity [NTU]",
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"ticks": [0, 2, 4, 6, 8, 10]
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},
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"EPA_Forest_fire_Methane_Yearly": {
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"range": [0, 2],
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"cm": "rainbow",
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"label": "*10^10[molec/cm2/s]"
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},
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"EPA_Forest_fire_Methane_Daily": {
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"range": [0, 2],
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"cm": "rainbow",
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"label": "*10^12[molec/cm2/s]"
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},
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"EPA_Field_burning_Monthly": {
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"range": [0, 4.5],
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"cm": "rainbow",
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"label": "*10^9[molec/cm2/s]"
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},
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"LIS_Global_DA_Evap": {
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"range": [0, 100],
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"cm": "viridis",
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"label": "mg/m2/s"
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},
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"HLS_NDVI": {
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"range": [-1, 1],
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"cm": "cfastie",
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"label": "NDVI",
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"ticks": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1]
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}
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},
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"gtif": {
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app/src/components/IndicatorData.vue

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},
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mounted() {
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const d = this.indicatorObject.time[this.indicatorObject.time.length - 1];
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if (d.toFormat) {
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if (d?.toFormat) {
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const formatted = d.toFormat('dd. MMM');
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this.dataLayerTime = {
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value: formatted,

app/src/components/map/Map.vue

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if (timeEntry === undefined && time.isLuxonDateTime) {
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// search for closest time to datetime if provided as such
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const searchTimes = this.availableTimeEntries.map((e) => {
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if (e.value?.isLuxonDateTime) {
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return e.value;
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const timeValue = Array.isArray(e.value) ? e.value[0] : e.value;
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if (timeValue?.isLuxonDateTime) {
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return timeValue;
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}
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return DateTime.fromISO(e.value);
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return DateTime.fromISO(timeValue);
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});
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const closestTime = findClosest(searchTimes, time);
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// get back the original unmapped object with value and name
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timeEntry = this.availableTimeEntries.find((e) => {
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if (e.value?.isLuxonDateTime) {
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return e.value.ts === closestTime.ts;
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const timeValue = Array.isArray(e.value) ? e.value[0] : e.value;
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if (timeValue?.isLuxonDateTime) {
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return timeValue.ts === closestTime.ts;
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}
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return DateTime.fromISO(e.value).ts === closestTime.ts;
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return DateTime.fromISO(timeValue).ts === closestTime.ts;
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});
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} else {
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// Use most recent time since there is none defined in the map timeline
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return;
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}
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window.dispatchEvent(new CustomEvent('set-custom-area-indicator-loading', { detail: true }));
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const options = {
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currentTimeIndex: this.currentTimeIndex,
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};
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try {
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const custom = await fetchCustomAreaObjects(
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{},
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options,
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this.drawnArea.area,
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this.mergedConfigsData[0],
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this.indicator,

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