diff --git a/.delta/ui b/.delta/ui index 3ef9c40b5..03d7b0bfc 160000 --- a/.delta/ui +++ b/.delta/ui @@ -1 +1 @@ -Subproject commit 3ef9c40b5696fccc2f6eb05d2c1319fd1fb219fc +Subproject commit 03d7b0bfc06450d59aadef0ab0169b232d9b8604 diff --git a/.env b/.env index 91791250f..ddd64de6e 100644 --- a/.env +++ b/.env @@ -1,8 +1,8 @@ # Title of the application shown on the header and wherever the name is needed. -APP_TITLE=Dashboard Delta +APP_TITLE=VEDA Dashboard # Short description used in meta tags. It shows up when the app url is shared. -APP_DESCRIPTION=Earth changing dashboard +APP_DESCRIPTION=Visualization, Exploration, and Data Analysis (VEDA) # Email to reach out when an error occurs or the users have questions. APP_CONTACT_EMAIL=email@example.org @@ -20,4 +20,7 @@ MAPBOX_STYLE_URL='mapbox://styles/covid-nasa/ckb01h6f10bn81iqg98ne0i2y' # If the app is being served in from a subfolder, the domain url must be set. # For example, if the app is served from /mysite: -# PUBLIC_URL=http://example.com/mysite \ No newline at end of file +# PUBLIC_URL=http://example.com/mysite + +# Google form for feedback +GOOGLE_FORM = 'https://docs.google.com/forms/d/e/1FAIpQLSfGcd3FDsM3kQIOVKjzdPn4f88hX8RZ4Qef7qBsTtDqxjTSkg/viewform?embedded=true' diff --git a/.github/workflows/deploy-prod.yml b/.github/workflows/deploy-prod.yml index a96656d01..3929e743a 100644 --- a/.github/workflows/deploy-prod.yml +++ b/.github/workflows/deploy-prod.yml @@ -9,7 +9,8 @@ on: env: NODE: 16 - DOMAIN_PROD: https://earthdata.nasa.gov/dashboard + # DOMAIN_PROD: https://www.earthdata.nasa.gov/dashboard + DOMAIN_PROD: /dashboard DEPLOY_BUCKET_PROD: climatedashboard DEPLOY_BUCKET_PROD_REGION: us-east-1 diff --git a/datasets/socioeconomic--dataset-cover.png b/datasets/socioeconomic--dataset-cover.png new file mode 100644 index 000000000..f12221ad9 Binary files /dev/null and b/datasets/socioeconomic--dataset-cover.png differ diff --git a/datasets/svi-household--dataset-cover.png b/datasets/svi-household--dataset-cover.png new file mode 100644 index 000000000..d70671991 Binary files /dev/null and b/datasets/svi-household--dataset-cover.png differ diff --git a/datasets/svi-housing--dataset-cover.png b/datasets/svi-housing--dataset-cover.png new file mode 100644 index 000000000..e98936c5d Binary files /dev/null and b/datasets/svi-housing--dataset-cover.png differ diff --git a/datasets/svi-minority--dataset-cover.png b/datasets/svi-minority--dataset-cover.png new file mode 100644 index 000000000..4742c34cd Binary files /dev/null and b/datasets/svi-minority--dataset-cover.png differ diff --git a/datasets/svi-overall--dataset-cover.png b/datasets/svi-overall--dataset-cover.png new file mode 100644 index 000000000..4d17ddd4e Binary files /dev/null and b/datasets/svi-overall--dataset-cover.png differ diff --git a/datasets/svi-socioeconomic--dataset-cover.png b/datasets/svi-socioeconomic--dataset-cover.png new file mode 100644 index 000000000..0fce64128 Binary files /dev/null and b/datasets/svi-socioeconomic--dataset-cover.png differ diff --git a/datasets/svi_household.ej.data.mdx b/datasets/svi_household.ej.data.mdx new file mode 100644 index 000000000..69a2b9fcb --- /dev/null +++ b/datasets/svi_household.ej.data.mdx @@ -0,0 +1,127 @@ +--- +id: svi-household +name: 'Household and Disability Score' +description: "Household composition and disability score for the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) gridded at a spatial resolution of 1 km" +media: + src: ::file ./svi-household--dataset-cover.png + alt: 2018 Social Vulnerability Index (SVI) based on household and disability score. + author: + name: NASA + url: https://nasa.gov/ +thematics: + - environmental-justice +layers: + - id: social-vulnerability-index-household + name: Household and Disability Score + type: raster + description: 'Household Composition & Disability (Aged 65 or Older, Aged 17 or Younger, Civilian with a Disability, Single-Parent Households) - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: oranges + rescale: + - 0 + - 1 + compare: + datasetId: svi-household + layerId: social-vulnerability-index-household + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#fff5eb" + - "#fdd9b4" + - "#fda762" + - "#f3701b" + - "#c54102" + - "#7f2704" + - id: social-vulnerability-index-household-nopop + name: Household and Disability Score (No Pop) + type: raster + description: 'Household Composition & Disability (Aged 65 or Older, Aged 17 or Younger, Civilian with a Disability, Single-Parent Households) - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: oranges + rescale: + - 0 + - 1 + compare: + datasetId: svi-household + layerId: social-vulnerability-index-household-nopop + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#fff5eb" + - "#fdd9b4" + - "#fda762" + - "#f3701b" + - "#c54102" + - "#7f2704" +--- + + + +CDC's Social Vulnerability Index (SVI) uses 15 variables at the census tract level. The data comes from the U.S. decennial census for the years 2000 & 2010, and the American Community Survey (ACS) for the years 2014, 2016, and 2018. It is a hierarchical additive index (Tate, 2013), with the component elements of CDC’s SVI including the following for 4 themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation. + +SVI indicates the relative vulnerability of every U.S. Census tract–subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. + + + + + +## Scientific research +The Household Composition & Disability Score (HCDS) is one of the four themes used in determining a community’s social vulnerability. This dataset can be used to create a community evacuation plan accounting for individuals who have special needs, the elderly, and/or families with young children. In the event of a disaster, this data can also help responders determine the number of emergency personnel required for special household cases (accessibility assistance), the type of supplies needed based on age, and the amount of supplies, food, and other restorative resources needed¹. The HCDS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC)was provided under the U.S. National Aeronautics and Space Administration (NASA)². + + + + +
+ + + Comparison of the household composition and disability score for New Orleans, LA between 2014 and 2016. + +
+ +## Interpreting the data +The Household Composition & Disability score displays the vulnerability in a given county tract based on household composition using values that range from 0 (less vulnerable) to 1 (more vulnerable). The SVI is presented as a percentile that allows a tract to be compared directly to the tracts around it. Vulnerable household compositions were those identified as having residents who were aged 65 or older, aged 17 or younger, had a disability, and/or were a single-parent with children under the age of 18. People in any of these categories are more likely to require financial support, transportation, medical care, or assistance with ordinary daily activities during disasters and therefore have an increased vulnerability³. County tracts with a higher percentage of vulnerable household compositions were given higher SVI values. + + + + + +## Credits +1) Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry/ Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index Database. https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/pdf/SVI2018Documentation_01192022_1.pdf + +2) Center for International Earth Science Information Network, (CIESIN), Columbia University. 2021. Documentation for the U.S. Social Vulnerability Index Grids. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/fjr9-a973. Accessed 13 May 2022. + +3) Flanagan, Barry E.; Gregory, Edward W.; Hallisey, Elaine J.; Heitgerd, Janet L.; and Lewis, Brian (2011) "A Social Vulnerability Index for Disaster Management," Journal of Homeland Security and Emergency Management: Vol. 8: Iss. 1, Article 3. DOI: 10.2202/1547-7355.1792 Available at: http://www.bepress.com/jhsem/vol8/iss1/3 + + diff --git a/datasets/svi_housing.ej.data.mdx b/datasets/svi_housing.ej.data.mdx new file mode 100644 index 000000000..021fd0300 --- /dev/null +++ b/datasets/svi_housing.ej.data.mdx @@ -0,0 +1,132 @@ +--- +id: svi-housing +name: 'Housing Type and Transportation Score' +description: "Housing Type and Transportation score for the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) gridded at a spatial resolution of 1 km" +media: + src: ::file ./svi-housing--dataset-cover.png + alt: 2018 Social Vulnerability Index (SVI) based on housing type and transportation score. + author: + name: NASA + url: +thematics: + - environmental-justice +layers: + - id: social-vulnerability-index-housing + name: Housing Type and Transportation Score + type: raster + description: 'Housing Type & Transportation (Multi-Unit Structures, Mobile Homes, Crowding, No Vehicle, Group Quarters) - Percentile ranking' + datetime: | + ::js ({ datetime, dateFns }) => { + return dateFns.sub(datetime, { years: 2 }); + } + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: blues + rescale: + - 0 + - 1 + compare: + datasetId: svi-housing + layerId: social-vulnerability-index-housing + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#f7fbff" + - "#d0e1f2" + - "#94c4df" + - "#4a98c9" + - "#1764ab" + - "#08306b" + - id: social-vulnerability-index-housing-nopop + name: Housing Type and Transportation Score - Masked for No Population + type: raster + description: 'Housing Type & Transportation (Multi-Unit Structures, Mobile Homes, Crowding, No Vehicle, Group Quarters) - Percentile ranking masked for regions with no population' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: blues + rescale: + - 0 + - 1 + compare: + datasetId: svi-housing + layerId: social-vulnerability-index-housing-nopop + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#f7fbff" + - "#d0e1f2" + - "#94c4df" + - "#4a98c9" + - "#1764ab" + - "#08306b" +--- + + + +CDC's Social Vulnerability Index (SVI) uses 15 variables at the census tract level. The data comes from the U.S. decennial census for the years 2000 & 2010, and the American Community Survey (ACS) for the years 2014, 2016, and 2018. It is a hierarchical additive index (Tate, 2013), with the component elements of CDC’s SVI including the following for 4 themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation. + +SVI indicates the relative vulnerability of every U.S. Census tract–subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. + + + + + +## Scientific research +The Housing Type & Transportation Score (HTTS) is one of the four themes used in determining a community’s social vulnerability, examining it against housing structure/type and vehicle access. As with the other SVI thematic areas, in the event of a disaster, or to better prepare for one, this dataset can help emergency personnel create an evacuation plan for individuals without vehicles, allocate emergency preparedness funding by community need, and identify areas in need of emergency shelters¹. It can also be used for local governments to identify areas needing more robust public transportation, areas of overcrowding, and local housing vulnerability. The HTTS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC)was provided under the U.S. National Aeronautics and Space Administration (NASA)². + + + + +
+ + + Comparison of the housing and transportation score for Philadelphia, PA between 2016 and 2018. + +
+ +## Interpreting the data +Interpreting the Data +Housing Type & Transportation Score displays the vulnerability in a given county tract based on housing type and transportation accessibility using values that range from 0 (less vulnerable) to 1 (more vulnerable). The score is broken down into several variables, all of which have been identified as areas of vulnerability for a community in the event of a disaster: number of multi-unit structures, mobile homes, level of crowding, vehicle accessibility, and grouped housing. Housing structure and quality are important factors in evaluating disaster vulnerability, as it is closely tied to personal wealth. Low-income communities often live in more poorly constructed houses or mobile homes that are especially vulnerable to strong storms or earthquakes³. The time, effort, and personnel that may be needed to evacuate crowded spaces can delay a community and the individual’s ability to avoid disasters or vulnerable situations. On the other hand, having access to reliable transportation can increase an individual’s ability to avoid vulnerable situations. + + + + + +## Credits +1) Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry/ Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index Database. https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/pdf/SVI2018Documentation_01192022_1.pdf + +2) Center for International Earth Science Information Network, (CIESIN), Columbia University. 2021. Documentation for the U.S. Social Vulnerability Index Grids. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/fjr9-a973. Accessed 13 May 2022. + +3) Flanagan, Barry E.; Gregory, Edward W.; Hallisey, Elaine J.; Heitgerd, Janet L.; and Lewis, Brian (2011) "A Social Vulnerability Index for Disaster Management," Journal of Homeland Security and Emergency Management: Vol. 8: Iss. 1, Article 3. DOI: 10.2202/1547-7355.1792 Available at: http://www.bepress.com/jhsem/vol8/iss1/3 + + diff --git a/datasets/svi_minority.ej.data.mdx b/datasets/svi_minority.ej.data.mdx new file mode 100644 index 000000000..4047f4af2 --- /dev/null +++ b/datasets/svi_minority.ej.data.mdx @@ -0,0 +1,136 @@ +--- +id: svi-minority +name: 'Minority Status and Language Score' +description: "Minority Status and Language score for the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) gridded at a spatial resolution of 1 km" +media: + src: ::file ./svi-minority--dataset-cover.png + alt: 2018 Social Vulnerability Index (SVI) based on minority status and language score. + author: + name: NASA + url: +thematics: + - environmental-justice +layers: + - id: social-vulnerability-index-minority + name: Minority Status and Language Score + type: raster + description: 'Minority Status & Language (Minority, Speaks English “Less than Well”) - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: purples + rescale: + - 0 + - 1 + compare: + datasetId: svi-minority + layerId: social-vulnerability-index-minority + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#fcfbfd" + - "#e2e2ef" + - "#b6b6d8" + - "#8683bd" + - "#61409b" + - "#3f007d" + - id: social-vulnerability-index-minority-nopop + name: Minority Status and Language Score - Masked for No Population + type: raster + description: 'Minority Status & Language (Minority, Speaks English “Less than Well”) - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: purples + rescale: + - 0 + - 1 + compare: + datasetId: svi-minority + layerId: social-vulnerability-index-minority-nopop + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#fcfbfd" + - "#e2e2ef" + - "#b6b6d8" + - "#8683bd" + - "#61409b" + - "#3f007d" +--- + + + +CDC's Social Vulnerability Index (SVI) uses 15 variables at the census tract level. The data comes from the U.S. decennial census for the years 2000 & 2010, and the American Community Survey (ACS) for the years 2014, 2016, and 2018. It is a hierarchical additive index (Tate, 2013), with the component elements of CDC’s SVI including the following for 4 themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation. + +SVI indicates the relative vulnerability of every U.S. Census tract–subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. + + + + + +## Scientific research +The Minority Status & Language Score (MSLS), as with the other SVI thematic areas, is used to calculate a community’s social vulnerability. This data set can be used to prepare emergency plans for communities with lower English-proficiency levels¹, and has helped contribute to efforts such as the Minority Health SVI and its related Dashboard. The Minority Health SVI is an extension of the CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI), which is a database that helps emergency response planners and public health officials identify, map, and plan support for communities that will most likely need support before, during, and after a public health emergency². The MSLS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)³. + + + + +
+ + + Comparison of the minority and language score for Blackfeet Indian Reservation between 2016 and 2018. + +
+ +## Interpreting the data +The MSLS vulnerability rank in a given county tract is based on minority status and level of English proficiency, using values ranging from 0 (less vulnerable) to 1 (more vulnerable). Communities with English proficiency levels classified as “ Less than Well” and/or with more individuals identifying as minorities had higher SVIs and are therefore more vulnerable. For individuals with limited English proficiency, disaster communication may be increasingly difficult and the marginalization of certain racial and ethnic groups (including real estate discrimination) has left these communities in areas of higher vulnerability⁴. + + + + + +## Credits +1. Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry/ Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index Database. https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/pdf/SVI2018Documentation_01192022_1.pdf + +2. U.S. Department of Health and Human Services Office of Minority Health. Minority Health SVI. https://www.minorityhealth.hhs.gov/minority-health-svi/assets/downloads/MH%20SVI%20Overview_8.4.2021_9.1.2021.pdf + +3. Center for International Earth Science Information Network, (CIESIN), Columbia University. 2021. Documentation for the U.S. Social Vulnerability Index Grids. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/fjr9-a973. Accessed 13 May 2022. + +4. Flanagan, Barry E.; Gregory, Edward W.; Hallisey, Elaine J.; Heitgerd, Janet L.; and Lewis, Brian (2011) "A Social Vulnerability Index for Disaster Management," Journal of Homeland Security and Emergency Management: Vol. 8: Iss. 1, Article 3. DOI: 10.2202/1547-7355.1792 Available at: http://www.bepress.com/jhsem/vol8/iss1/3 + + + + + +## Additional resources +The Minority Health SVI dashboard is an interactive platform for users to view and map Minority Health SVI variables and index by county. The dashboard is a deployment of Esri ArcGIS Enterprise Operations Dashboard, hosted on the CDC OneMap platform and available at: https://onemap.cdc.gov/Portal/apps/MapSeries/index.html?appid=3384875c46d649ee9b452913fd64e3c4 + + diff --git a/datasets/svi_overall.ej.data.mdx b/datasets/svi_overall.ej.data.mdx new file mode 100644 index 000000000..efeb2b40b --- /dev/null +++ b/datasets/svi_overall.ej.data.mdx @@ -0,0 +1,125 @@ +--- +id: svi-overall +name: 'Overall Social Vulnerability' +description: "Overall score for the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) gridded at a spatial resolution of 1 km" +media: + src: ::file ./svi-overall--dataset-cover.png + alt: 2018 overall Social Vulnerability Index (SVI). + author: + name: NASA + url: +thematics: + - environmental-justice +layers: + - id: social-vulnerability-index-overall + name: Overall Social Vulnerability - Percentile Ranking + type: raster + description: 'Overall Social Vulnerability Index - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: ylgnbu + rescale: + - 0 + - 1 + compare: + datasetId: svi-overall + layerId: social-vulnerability-index-overall + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#ffffd9" + - "#d6efb3" + - "#73c8bd" + - "#2498c1" + - "#234da0" + - "#081d58" + - id: social-vulnerability-index-overall-nopop + name: Overall (NoPop) Social Vulnerability - Percentile Ranking + type: raster + description: 'Overall Social Vulnerability Index - Percentile ranking masked for areas with no population' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: ylgnbu + rescale: + - 0 + - 1 + compare: + datasetId: svi-overall + layerId: social-vulnerability-index-overall-nopop + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#ffffd9" + - "#d6efb3" + - "#73c8bd" + - "#2498c1" + - "#234da0" + - "#081d58" +--- + + + +CDC's Social Vulnerability Index (SVI) uses 15 variables at the census tract level. The data comes from the U.S. decennial census for the years 2000 & 2010, and the American Community Survey (ACS) for the years 2014, 2016, and 2018. It is a hierarchical additive index (Tate, 2013), with the component elements of CDC’s SVI including the following for 4 themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation. + +SVI indicates the relative vulnerability of every U.S. Census tract–subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. + + + + + +## Scientific research +The SVI Overall Score provides the overall, summed social vulnerability score for a given tract. The Overall Score SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)¹. + + + + +
+ + + Comparison of the overall social vulnerability index for Houston, TX between 2016 and 2018. + +
+ +## Interpreting the data +The Overall SVI Score describes the vulnerability in a given county tract based on the combined percentile ranking of the four SVI scores (Socioeconomic Status, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation). The summed percentile ranking from the four themes is ordered, and then used to calculate an overall percentile ranking, ranging from 0 (less vulnerable) to 1 (more vulnerable)². Tracts with higher Overall SVI Scores typically rank high in other SVI domains, and reveal communities that may require extra support, resources, and preventative care in order to better prepare for and manage emergency situations. + + + + + +## Credits +1. Center for International Earth Science Information Network, (CIESIN), Columbia University. 2021. Documentation for the U.S. Social Vulnerability Index Grids. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/fjr9-a973. Accessed 13 May 2022. + +2. Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry/ Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index Database. https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/pdf/SVI2018Documentation_01192022_1.pdf + + diff --git a/datasets/svi_socioeconomic.ej.data.mdx b/datasets/svi_socioeconomic.ej.data.mdx new file mode 100644 index 000000000..7712ae0a0 --- /dev/null +++ b/datasets/svi_socioeconomic.ej.data.mdx @@ -0,0 +1,154 @@ +--- +id: svi-socioeconomic +name: 'Socioeconomic indicators' +description: "Socioeconomic status score for the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) gridded at a spatial resolution of 1 km" +media: + src: ::file ./svi-socioeconomic--dataset-cover.png + alt: 2018 Social Vulnerability Index (SVI) based on socioeconomic data. + author: + name: NASA + url: +thematics: + - environmental-justice +layers: + - id: social-vulnerability-index-socioeconomic + name: Socioeconomic Vulnerability Score + type: raster + description: 'Socioeconomic Status (Below Poverty, Unemployed, Income, No High School Diploma) - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: greens + rescale: + - 0 + - 1 + compare: + datasetId: svi-socioeconomic + layerId: social-vulnerability-index-socioeconomic + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#f7fcf5" + - "#d3eecd" + - "#98d594" + - "#4bb062" + - "#157f3b" + - "#00441b" + - id: social-vulnerability-index-socioeconomic-nopop + name: Socioeconomic (No Pop) Vulnerability Score + type: raster + description: 'Socioeconomic Status (Below Poverty, Unemployed, Income, No High School Diploma) - Percentile ranking' + zoomExtent: + - 2 + - 16 + sourceParams: + resampling_method: bilinear + bidx: 1 + colormap_name: greens + rescale: + - 0 + - 1 + compare: + datasetId: svi-socioeconomic + layerId: social-vulnerability-index-socioeconomic-nopop + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#f7fcf5" + - "#d3eecd" + - "#98d594" + - "#4bb062" + - "#157f3b" + - "#00441b" +--- + + + +CDC's Social Vulnerability Index (SVI) uses 15 variables at the census tract level. The data comes from the U.S. decennial census for the years 2000 & 2010, and the American Community Survey (ACS) for the years 2014, 2016, and 2018. It is a hierarchical additive index (Tate, 2013), with the component elements of CDC’s SVI including the following for 4 themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation. + +SVI indicates the relative vulnerability of every U.S. Census tract–subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. + + + + + +## Scientific research +The Economic Status Score, like the three other themes, is used in observing a community’s social vulnerability. As with other SVI scores, the economic status score can help local officials and teams identify communities that will need continued support to recover following an emergency or natural disaster¹. The Economic Status SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)². + +
+ + + Socioeconomic vulnerability score for Huntsville, AL for 2018. + +
+ + + +
+ + + Comparison of socioeconomic vulnerability score for San Francisco, CA between 2016 and 2018. + +
+ +## Interpreting the data +The Socioeconomic Status score displays the vulnerability in a given county tract based on poverty level, employment, income, and education level using values that range from 0 (less vulnerable) to 1 (more vulnerable). Of these variables, tracts with more individuals who are below the poverty level, unemployed, lower-income, and have no high school diploma are identified as more vulnerable³. Conversely, as income, education, and level of employment increase, the social vulnerability for a tract decreases. Likely, communities with higher education and employment levels are exposed to higher income opportunities and often have access to resources that are preventative (well-structured housing, extra supplies), accessible (vehicles, medical attention, spacious) and responsive (higher communication levels, faster recovery rates). + + + + + +## Credits +1. Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry/ Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index Database. https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/pdf/SVI2018Documentation_01192022_1.pdf + +2. Center for International Earth Science Information Network, (CIESIN), Columbia University. 2021. Documentation for the U.S. Social Vulnerability Index Grids. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/fjr9-a973. Accessed 13 May 2022. + +3. Flanagan, Barry E.; Gregory, Edward W.; Hallisey, Elaine J.; Heitgerd, Janet L.; and Lewis, Brian (2011) "A Social Vulnerability Index for Disaster Management," Journal of Homeland Security and Emergency Management: Vol. 8: Iss. 1, Article 3. DOI: 10.2202/1547-7355.1792 Available at: http://www.bepress.com/jhsem/vol8/iss1/3 + + + + + +## Additional resources +### NASA Features + +### Explore the data + +### Explore the Missions + + + diff --git a/discoveries/hurricane-maria-and-ida.discoveries.mdx b/discoveries/hurricane-maria-and-ida.discoveries.mdx new file mode 100644 index 000000000..c7aa8e79b --- /dev/null +++ b/discoveries/hurricane-maria-and-ida.discoveries.mdx @@ -0,0 +1,44 @@ +--- +featuredOn: + - covid-19 +id: 'hurricane-maria-and-ida' +name: Connecting Disaster Recovery with Environmental Justice +description: "Featuring Hurricane María and Hurricane Ida" +media: + src: ::file ./air-quality-and-covid-19--discovery-cover.jpg + alt: Clear nightsky with crescent moon above the mountains + author: + name: Benjamin Voros + url: https://unsplash.com/photos/U-Kty6HxcQc +pubDate: 2020-12-01 +thematics: + - environmental-justice +--- + + + ## Connecting Disaster Recovery with Environmental Justice: Hurricane María + + Hurricane María made landfall in Puerto Rico as a Category 4 or 5 hurricane on September 20, 2017, leaving a path of destruction in its wake. [Over 1.5 million people on the island lost power, leading to the longest blackout in US history](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218883). Although efforts to repair the damage on the island were extensive, the [areas with the most severe and prolonged impacts were areas of lower socioeconomic status](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218883). These communities lacked the resources and the representation to repair damage quickly, leading to long-term lack of access to electricity, water, and other critical supplies. + + NASA hosts a wide variety of continuous Earth observation data useful in environmental justice research. This dashboard features a selection of NASA datasets from across the Agency, including socioeconomic data, Earth observation analysis, and other combined datasets. These tools allow users to visualize and download data to understand the environmental issues brought on by Hurricane María. Merging Earth data and socioeconomic data can help communities like those in Puerto Rico to better prepare for and respond to future natural disasters. + + **About the Data** + + *Rest of the text will be an explanation about the data used. No need to be reviewed by PB* + + + + + + ## Connecting Disaster Recovery with Environmental Justice: Hurricane Ida + + Known as the city that can barely catch its breath between storms, New Orleans experienced another devastating event on August 29, 2021 as Hurricane Ida made landfall as a Category 4 hurricane. The effects of the storm were widespread, causing millions of dollars worth of damage and affecting the lives and homes of millions of people. + + [Disadvantaged communities](https://www.nature.com/articles/d41586-021-02520-8) in Louisiana and across the country already struggle with higher rates of asthma, cancer, and COVID-19 infections. These communities are often hardest-hit by storms like Ida. Research has shown that disadvantaged communities often receive less federal aid than other communities, only prolonging their hardships. NASA is prioritizing open access to environmental justice data such as the datasets in this dashboard in an effort to help communities better prepare for and respond to natural disasters and to help shed light on cases of environmental injustice. + + + **About the Data** + + *Rest of the text will be an explanation about the data used. No need to be reviewed by PB* + + diff --git a/thematic/environmental-justice.thematic.jpg b/thematic/environmental-justice.thematic.jpg new file mode 100644 index 000000000..5693e1b04 Binary files /dev/null and b/thematic/environmental-justice.thematic.jpg differ diff --git a/thematic/environmental-justice.thematic.mdx b/thematic/environmental-justice.thematic.mdx new file mode 100644 index 000000000..50c1afe97 --- /dev/null +++ b/thematic/environmental-justice.thematic.mdx @@ -0,0 +1,31 @@ +--- +id: environmental-justice +name: 'Environmental Justice' +description: "NASA data are being used to support environmental and climate justice efforts to assess the vulnerability and exposure of communities to environmental challenges." + +media: + src: ::file ./environmental-justice.thematic.jpg + alt: 'Map of heat risk potential for Sacramento, CA' + author: + name: NASA + url: https://science.nasa.gov/files/science-red/s3fs-public/styles/background_image_file_size/public/thumbnails/image/2020Fall_LaRC_SacramentoUrbanDevelopment_WebsiteImage.jpg?itok=5VHhkPYq + +about: + title: Environmental Justice + description: NASA data are being used to support environmental and climate justice efforts to assess the vulnerability and exposure of communities to environmental challenges. + +--- + + +NASA is making a long-term commitment to create an inclusive Open Science community so that NASA science and technology benefits people across the U.S. and its territories by helping them make informed decisions about challenges they face in their communities. The agency’s Earth Science Division (ESD) supports environmental justice communities by expanding awareness, accessibility, and use of Earth science data and enabling contributions to Earth science research and applications. When paired with socioeconomic data, NASA Earth data equips decision makers, community leaders, and individuals with the information they need to help identify environmental hazards in their own communities. + +The United States Environmental Protection Agency (EPA) defines environmental justice as the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies. The White House Environmental Justice Advisory Council further defines environmental justice communities as "geographic locations within the U.S. and its territories with significant representation of persons of color, low-income persons, indigenous persons or members of Tribal nations, where such individuals experience, or are at risk of experiencing, higher or more adverse human health or environmental outcomes”. + +Some environmental hazards and events that result in environmental injustices include natural disasters, drought, air and water pollution, urban heat exposure, and proximity to emissions of hazardous and toxic substances. Addressing environmental justice requires an understanding of environmental conditions, locations, and communities at risk of environmental hazards. Environmental justice research is complex and interdisciplinary, drawing from Earth science, socioeconomics, health sciences, and many other fields. + +This dashboard will feature environmental justice case studies, beginning with Hurricane Ida and Hurricane Maria. + +To learn more about how NASA data are being used to support environmental and climate justice research, click here: [NASA EJ Data Backgrounder](https://earthdata.nasa.gov/learn/backgrounders/environmental-justice) + + +