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).
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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) |
