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Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes)
This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
]
|
| contactPoint |
{
"fn": "Jordan S. Read",
"@type": "vcard:Contact",
"hasEmail": "mailto:jread@usgs.gov"
}
|
| description | This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Digital Data",
"format": "XML",
"accessURL": "http://dx.doi.org/10.5066/P9AQPIVD",
"mediaType": "application/http",
"description": "Landing page for access to the data"
},
{
"@type": "dcat:Distribution",
"title": "Original Metadata",
"format": "XML",
"mediaType": "text/xml",
"description": "The metadata original format",
"downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5d89d8e3e4b0c4f70d0ae4dc.xml"
}
]
|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_5d89d8e3e4b0c4f70d0ae4dc |
| keyword |
[
"007",
"012",
"MN",
"Minnesota",
"US",
"USGS:5d89d8e3e4b0c4f70d0ae4dc",
"United States",
"WI",
"Wisconsin",
"climate change",
"deep learning",
"environment",
"hybrid modeling",
"inlandWaters",
"machine learning",
"modeling",
"reservoirs",
"temperate lakes",
"temperature",
"thermal profiles",
"water"
]
|
| modified | 2020-08-20T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -94.2609062307949, 42.5692312672573, -87.9475441739278, 48.6427837911633 |
| theme |
[
"Geospatial"
]
|
| title | Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes) |
