{"@type": "dcat:Dataset", "DOI": "10.15121/1797283", "accessLevel": "public", "bureauCode": ["019:20"], "contactPoint": {"@type": "vcard:Contact", "fn": "Jim Moraga", "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", "accessURL": "https://gdr.openei.org/files/1306/SaltonSea_geodatabase.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.", "format": "zip", "mediaType": "application/zip", "title": "Salton Sea ArcGIS Geodatabase.zip"}, {"@type": "dcat:Distribution", "accessURL": "https://gdr.openei.org/files/1306/SaltonSeaGDB.tar", "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.", "format": "tar", "mediaType": "application/octet-stream", "title": "Salton Sea Geodatabase Files.tar"}, {"@type": "dcat:Distribution", "accessURL": "https://gdr.openei.org/files/1303/Geodatabase%20Design.docx", "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.", "format": "docx", "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "title": "Geodatabase Design.docx"}], "identifier": "https://data.openei.org/submissions/7424", "issued": "2021-04-27T06:00:00Z", "keyword": ["geothermal", "energy", "geodatabase", "Salton Sea", "artificial intelligence", "ai", "deep learning", "machine learning", "seismic", "remote sensing", "hyperspectral", "hyperspectral imaging", "geospacial database", "exploration", "site detection", "geothermal site detection", "anomaly detection", "short wavelength infrared", "SWIR", "support vector machine", "SVM", "land surface temperature", "LST", "well", "raw data", "processed data", "California", "ArcGis", "GIS", "model", "database", "hydrothermal", "geophysics", "radar", "blind", "blind system", "deformation", "geophysical", "conceptual model fault", "preprocessed", "raster", "vector", "field data", "geospatial data"], "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": {"@type": "org:Organization", "name": "Colorado School of Mines"}, "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"}