diff --git a/.veda/ui b/.veda/ui index 3fd694f77..af635ffb6 160000 --- a/.veda/ui +++ b/.veda/ui @@ -1 +1 @@ -Subproject commit 3fd694f7757c370cea048c7e6c6d5c2613932e2c +Subproject commit af635ffb6d692b7a9a16bf10740abd7277c7b26c diff --git a/datasets/CMIP-winter-median-ta.data.mdx b/datasets/CMIP-winter-median-ta.data.mdx index 3773fc9f8..579cfbfd1 100644 --- a/datasets/CMIP-winter-median-ta.data.mdx +++ b/datasets/CMIP-winter-median-ta.data.mdx @@ -31,6 +31,8 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: °C type: gradient label: Air temperature difference [C] min: "-5.5" @@ -65,6 +67,8 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: °C type: gradient label: Air temperature difference [C] min: "-5.5" diff --git a/datasets/co2.data.mdx b/datasets/co2.data.mdx index 4cd523023..e002b00c5 100644 --- a/datasets/co2.data.mdx +++ b/datasets/co2.data.mdx @@ -60,9 +60,11 @@ layers: - -0.0000015 - 0.0000015 legend: + unit: + label: ppm type: gradient - min: "-1.5 ppm" - max: "1.5 ppm" + min: "-1.5" + max: "1.5" stops: - "#384cc2" - "#6384eb" diff --git a/datasets/fire--dataset-cover.jpg b/datasets/fire--dataset-cover.jpg new file mode 100644 index 000000000..aa3158ad2 Binary files /dev/null and b/datasets/fire--dataset-cover.jpg differ diff --git a/datasets/fire.data.mdx b/datasets/fire.data.mdx new file mode 100644 index 000000000..01fbdd695 --- /dev/null +++ b/datasets/fire.data.mdx @@ -0,0 +1,52 @@ +--- +id: fire +name: Fire Perimeters +description: Fire perimeters generated from VIIRs sensor observations. +usage: + - url: https://nasa-impact.github.io/veda-docs/notebooks/tutorials/mapping-fires.html + label: View example notebook + title: VEDA documentation for visualization and download +media: + src: ::file ./fire--dataset-cover.jpg + alt: Forest burning at night + author: + name: Matt Howard + url: https://unsplash.com/photos/eAKDzK4lo4o +thematics: + - eis + +layers: + - id: eis_fire_perimeter + stacCol: eis_fire_perimeter + name: Fire Perimeter + type: vector + description: eis_fire_perimeter + zoomExtent: + - 5 + - 20 +--- + + + + ## FEDs Fire Perimeters + + Fire perimeter data is generated by the FEDs algorithm. The FEDs algorithm tracks fire movement and severity by ingesting observations from the VIIRS thermal sensors on the Suomi NPP and NOAA-20 satellites. This algorithm uses raw VIIRS observations to generate a polygon of the fire, locations of the active fire line, and estimates of fire mean Fire Radiative Power (FRP). The VIIRS sensors overpass at ~1:30 AM and PM local time, and provide estimates of fire evolution ~ every 12 hours. The data produced by this algorithm describe where fires are in space and how fires evolve through time. This CONUS-wide implementation of the FEDs algorithm is based on [Chen et al 2020’s algorithm for California.](https://www.nature.com/articles/s41597-022-01343-0) + + + + + + ## Scientific Application Using FEDS Fire Perimeters + FEDS Fire Perimeters offer insight into pre-fire risk, fire behaviour, and post-fire effects. The Earth Information System - Fire team is using FEDs perimeters to understand the full lifecycle of a fire + + + + + ## Datasets generated using FEDs Fire perimeters + + * Caldor Fire Behavior and Burn Severity + * Burn Area Reflectance Classification for Thomas Fire + * Maximum Fire Radiative Power for Thomas Fire + + + diff --git a/datasets/geoglam.data.mdx b/datasets/geoglam.data.mdx index 4916801c0..0999324c3 100644 --- a/datasets/geoglam.data.mdx +++ b/datasets/geoglam.data.mdx @@ -6,16 +6,18 @@ media: src: ::file ./geoglam--dataset-cover.jpg alt: Bird's eye view of fields author: - name: jean wimmerlin + name: Jean Wimmerlin url: https://unsplash.com/photos/RUj5b4YXaHE thematics: - agriculture +sources: + - geoglam layers: - id: geoglam stacCol: geoglam name: GEOGLAM Crop Conditions type: raster - description: "Add dataset description here" + description: Combined crop conditions across both the Crop Monitor for AMIS and Crop Monitor for Early Warning zoomExtent: - 0 - 16 diff --git a/datasets/global-reanalysis-da.data.mdx b/datasets/global-reanalysis-da.data.mdx index e25ebd8d9..2372845e3 100644 --- a/datasets/global-reanalysis-da.data.mdx +++ b/datasets/global-reanalysis-da.data.mdx @@ -35,10 +35,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: kg m-2 s-1 type: gradient label: Evapotranspiration [kg m-2 s-1] min: "0" - max: "0.0001 kg m-2 s-1" + max: "0.0001" stops: - '#440154' - '#3b528b' @@ -69,10 +71,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: g m-2 s-1 type: gradient label: Gross primary productivity [g m-2 s-1] min: "0" - max: "0.0001 g m-2 s-1" + max: "0.0001" stops: - '#440154' - '#3b528b' @@ -103,10 +107,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: mm type: gradient label: Groundwater storage [mm] min: "4500" - max: "5000 mm" + max: "5000" stops: - '#440154' - '#3b528b' @@ -137,10 +143,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: mm type: gradient label: Snow Water Equivalent [mm] min: "0" - max: "500 mm" + max: "500" stops: - "#F7FBFF" - "#D0E1F2" @@ -172,10 +180,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: m3 s-1 type: gradient label: Streamflow [m3 s-1] min: "0" - max: "2500 m3 s-1" + max: "2500" stops: - '#440154' - '#3b528b' @@ -206,10 +216,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: kg m-2 s-1 type: gradient label: Surface runoff [kg m-2 s-1] min: "0" - max: "0.00001 kg m-2 s-1" + max: "0.00001" stops: - '#440154' - '#3b528b' @@ -240,10 +252,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: kg m-2 s-1 type: gradient label: Subsurface runoff [kg m-2 s-1] min: "0" - max: "0.0001 kg m-2 s-1" + max: "0.0001" stops: - '#440154' - '#3b528b' @@ -274,10 +288,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: mm type: gradient label: Terrestrial Water Storage [mm] min: "5000" - max: "5800 mm" + max: "5800" stops: - '#440154' - '#3b528b' @@ -308,10 +324,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: kg m-2 s-1 type: gradient label: Total precipitation [kg m-2 s-1] min: "0" - max: "0.00001 kg m-2 s-1" + max: "0.00001" stops: - "#F7FBFF" - "#D0E1F2" diff --git a/datasets/lis.da.trend.data.mdx b/datasets/lis.da.trend.data.mdx index 231849cea..b623df39c 100644 --- a/datasets/lis.da.trend.data.mdx +++ b/datasets/lis.da.trend.data.mdx @@ -34,10 +34,12 @@ layers: return `TWS trend (2003-2021) VS GPP trend (2003-2021)`; } legend: + unit: + label: (mm/yr) type: gradient label: TWS Trend (mm/yr) min: "-20" - max: "20 (mm/yr)" + max: "20" stops: - "#a50026" - "#f46d43" @@ -61,10 +63,12 @@ layers: - 40 nodata: -9999. legend: + unit: + label: (gC/m2/yr) type: gradient label: GPP Trend (gC/m2/yr) min: "-40" - max: "40 (gC/m2/yr)" + max: "40" stops: - "#a50026" - "#f46d43" diff --git a/datasets/no2.data.mdx b/datasets/no2.data.mdx index 140e94251..5bccd6ba9 100644 --- a/datasets/no2.data.mdx +++ b/datasets/no2.data.mdx @@ -4,10 +4,10 @@ name: 'Nitrogen Dioxide' featured: true description: "Since the outbreak of the novel coronavirus, atmospheric concentrations of nitrogen dioxide have changed by as much as 60% in some regions." usage: - - url: 'https://github.com/NASA-IMPACT/veda-docs/blob/no2-single-item-viz/example-notebooks/no2-single-item-vizualization.ipynb' + - url: 'https://github.com/NASA-IMPACT/veda-docs/blob/main/notebooks/quickstarts/no2-map-plot.ipynb' label: View example notebook title: 'Static view in VEDA documentation' - - url: "https://nasa-veda.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FNASA-IMPACT%2Fveda-docs&urlpath=lab%2Ftree%2Fveda-docs%2Fexample-notebooks%2Fno2-single-item-vizualization.ipynb&branch=no2-single-item-viz" + - url: "https://nasa-veda.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FNASA-IMPACT%2Fveda-docs&urlpath=lab%2Ftree%2Fveda-docs%2Fnotebooks%2Fquickstarts%2Fno2-map-plot.ipynb&branch=main" label: Run example notebook title: 'Interactive session in VEDA 2i2c JupyterHub (requires account)' media: @@ -99,9 +99,11 @@ layers: - 0 - 30E14 legend: + unit: + label: mol/cm2 type: gradient min: 0 - max: 30e14 mol/cm2 + max: 30e14 stops: - '#ffffff' - '#fdd1bf' diff --git a/datasets/snow-projections-median.data.mdx b/datasets/snow-projections-median.data.mdx index d4afbee24..b5544067e 100644 --- a/datasets/snow-projections-median.data.mdx +++ b/datasets/snow-projections-median.data.mdx @@ -31,10 +31,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: mm type: gradient label: Snow Water Equivalent [mm] min: "0" - max: "1000 mm" + max: "1000" stops: - "#F7FBFF" - "#D0E1F2" @@ -62,10 +64,12 @@ layers: return `${dateFns.format(datetime, 'DD LLL yyyy')}`; } legend: + unit: + label: mm type: gradient label: Snow Water Equivalent [mm] min: "0" - max: "1000 mm" + max: "1000" stops: - "#F7FBFF" - "#D0E1F2" diff --git a/discoveries/air-quality-and-covid-19.discoveries.mdx b/discoveries/air-quality-and-covid-19.discoveries.mdx index 6e8d36c43..e123c1a10 100644 --- a/discoveries/air-quality-and-covid-19.discoveries.mdx +++ b/discoveries/air-quality-and-covid-19.discoveries.mdx @@ -191,8 +191,6 @@ thematics: ## Measuring Air Pollution on the Ground at Airports New research during the pandemic is also looking at how COVID-related travel bans are impacting air quality around airports. Current conditions create a unique opportunity to study airport-related pollutants, especially nitrogen dioxide and formaldehyde. While travel bans and strict regulations around air travel have been in place, air traffic has yet to return to previous levels, and many planes remain grounded. - - They are comparing the on-the-ground sensor information from NASA's [Pandora Project](https://pandora.gsfc.nasa.gov/ "Explore the Pandora Project") with satellite information from TROPOMI. So far, they have found that nitrogen dioxide hotspots in Atlanta shifted from the airport, shown here, to the city center from April-June 2020. By September, however, satellites revealed the airport had reemerged as a dominant nitrogen dioxide emission source.
Explore How COVID-19 Is Affecting Earth's Climate \ No newline at end of file diff --git a/discoveries/coastal-flooding-and-slr.discoveries.mdx b/discoveries/coastal-flooding-and-slr.discoveries.mdx index bfdfa0484..10aa1ffcb 100644 --- a/discoveries/coastal-flooding-and-slr.discoveries.mdx +++ b/discoveries/coastal-flooding-and-slr.discoveries.mdx @@ -185,7 +185,7 @@ thematics: - The ECCO model shows that there are seasonal variations in sea-level change and a background increase of **3.6 mm/yr** over time. Sea-level rise compounds the risk of coastal flooding by raising the water level at river mouths and increasing flood magnitudes.separates total sea-level change into two components: extra water mass added to the ocean (barystatic) and ocean temperature and salinity changes (steric). At this location, the steric component remains steady over time, while the barystatic component is increasing, meaning that **sea-level rise off the coast of Bangladesh is driven by extra water mass added to the ocean from the ice sheets, glaciers, and changes to land-water storage**. Understanding the sources of past sea-level rise helps researchers create better projections of future sea-level rise. + The ECCO model shows that there are seasonal variations in sea-level change and a background increase of **3.6 mm/yr** over time. Sea-level rise compounds the risk of coastal flooding by raising the water level at river mouths and increasing flood magnitudes. ECCO separates total sea-level change into two components: extra water mass added to the ocean (barystatic) and ocean temperature and salinity changes (steric). At this location, the steric component remains steady over time, while the barystatic component is increasing, meaning that **sea-level rise off the coast of Bangladesh is driven by extra water mass added to the ocean from the ice sheets, glaciers, and changes to land-water storage**. Understanding the sources of past sea-level rise helps researchers create better projections of future sea-level rise. Analyze the ECCO data further: - interactive notebook diff --git a/package.json b/package.json index 6858236b4..8a14ffeda 100644 --- a/package.json +++ b/package.json @@ -1,7 +1,7 @@ { "name": "veda-config", "description": "Configuration for Veda", - "version": "0.8.1", + "version": "0.9.0", "source": "./.veda/ui/app/index.html", "license": "Apache-2.0", "scripts": { diff --git a/taxonomies.yml b/taxonomies.yml index fa98b214e..47b1a3462 100644 --- a/taxonomies.yml +++ b/taxonomies.yml @@ -22,4 +22,6 @@ sources: - id: nasa-ciesin-grdi name: NASA CIESIN - id: atsdr-svi - name: ATSDR \ No newline at end of file + name: ATSDR + - id: geoglam + name: GEOGLAM \ No newline at end of file