Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site.
Resources
3 resources available
-
Geodatabase Design.docx
DOCX -
Salton Sea Geodatabase Files.tar
TAR -
Salton Sea ArcGIS Geodatabase.zip
ZIP
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "019:20" ] |
| contactPoint |
{ "fn": "Jim Moraga", "@type": "vcard:Contact", "hasEmail": "mailto:jmoraga@mines.edu" } |
| dataQuality |
true
|
| description | These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Geodatabase Design.docx", "format": "docx", "accessURL": "https://gdr.openei.org/files/1303/Geodatabase%20Design.docx", "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "description": "This document acts as a guide to the structure of the database. It is also a useful tool for understanding the organization of files in the database." }, { "@type": "dcat:Distribution", "title": "Salton Sea Geodatabase Files.tar", "format": "tar", "accessURL": "https://gdr.openei.org/files/1306/SaltonSeaGDB.tar", "mediaType": "application/octet-stream", "description": "Salton Sea geodatabase as files. Directory structure follows the geodatabase standard structure that can be found in the Geodatabase Design document. The database includes raw, pre-processed , and post-processed data, each with the six raster catalog types." }, { "@type": "dcat:Distribution", "title": "Salton Sea ArcGIS Geodatabase.zip", "format": "zip", "accessURL": "https://gdr.openei.org/files/1306/SaltonSea_geodatabase.zip", "mediaType": "application/zip", "description": "Salton Sea Geothermal Field Geodatabase to use with ArcGIS. Includes geodatabase files (.gdb) that can be brought in to ArcGIS from the raw, pre-processed, and post-processed data categories." } ] |
| DOI | 10.15121/1797283 |
| identifier | https://data.openei.org/submissions/7424 |
| issued | 2021-04-27T06:00:00Z |
| keyword |
[ "ArcGis", "California", "GIS", "LST", "SVM", "SWIR", "Salton Sea", "ai", "anomaly detection", "artificial intelligence", "blind", "blind system", "conceptual model fault", "database", "deep learning", "deformation", "energy", "exploration", "field data", "geodatabase", "geophysical", "geophysics", "geospacial database", "geospatial data", "geothermal", "geothermal site detection", "hydrothermal", "hyperspectral", "hyperspectral imaging", "land surface temperature", "machine learning", "model", "preprocessed", "processed data", "radar", "raster", "raw data", "remote sensing", "seismic", "short wavelength infrared", "site detection", "support vector machine", "vector", "well" ] |
| landingPage | https://gdr.openei.org/submissions/1306 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2021-09-07T17:49:35Z |
| programCode |
[ "019:006" ] |
| projectLead | Mike Weathers |
| projectNumber | EE0008760 |
| projectTitle | Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning |
| publisher |
{ "name": "Colorado School of Mines", "@type": "org:Organization" } |
| spatial |
"{"type":"Polygon","coordinates":[[[-115.8,33],[-115.4,33],[-115.4,33.4],[-115.8,33.4],[-115.8,33]]]}"
|
| title | Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence |
