| snippet:
|
This dataset is used for metrics that require population to be spatially allocated at a higher resolution than census blocks. This dataset is associated with the journal article (Baynes, J., Neale, A., Hultgren, T. (2022). Improving intelligent dasymetric mapping population density estimates at 30 m resolution for the conterminous United States by excluding uninhabited areas. Earth System Science Data, 14(6), 2833-2849. https://doi.org/10.5194/essd-14-2833-2022). The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. |
| summary:
|
This dataset is used for metrics that require population to be spatially allocated at a higher resolution than census blocks. This dataset is associated with the journal article (Baynes, J., Neale, A., Hultgren, T. (2022). Improving intelligent dasymetric mapping population density estimates at 30 m resolution for the conterminous United States by excluding uninhabited areas. Earth System Science Data, 14(6), 2833-2849. https://doi.org/10.5194/essd-14-2833-2022). The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. |
| accessInformation:
|
|
| thumbnail:
|
|
| maxScale:
|
0 |
| typeKeywords:
|
["ArcGIS Server","Data","Image Service","Service"] |
| description:
|
|
| licenseInfo:
|
|
| catalogPath:
|
|
| title:
|
Dasymetric_Population_CONUS_2020_V1 |
| type:
|
Image Service |
| url:
|
https://awsbutterfly.epa.gov:6443/arcgis/rest |
| tags:
|
["EPA","EnviroAtlas","Dasymetric Population","2020","CONUS"] |
| culture:
|
en-US |
| name:
|
Dasymetric_Population_CONUS_2020_V1 |
| guid:
|
|
| minScale:
|
0 |
| spatialReference:
|
|