Brady Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for 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. These inputs and outputs were used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems at the Brady Hot Springs Geothermal Site. 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 Brady Hot Springs Geothermal Site.
Resources
3 resources available
-
Geodatabase Design.docx
DOCX -
Brady Geodatabase.tar
TAR -
Brady Geodatabase ArcGIS.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 Brady's Geothermal Field. It includes all input and output files for 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. These inputs and outputs were used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems at the Brady Hot Springs Geothermal Site. 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 Brady Hot Springs 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": "A guide to the structure of the database. This document outlines the organization of the files in the database."
},
{
"@type": "dcat:Distribution",
"title": "Brady Geodatabase.tar",
"format": "tar",
"accessURL": "https://gdr.openei.org/files/1304/BradyGDB.tar",
"mediaType": "application/octet-stream",
"description": "Brady Geothermal Field geodatabase as files. Directory structure follows the geodatabase standard structure found in the geodatabase design document."
},
{
"@type": "dcat:Distribution",
"title": "Brady Geodatabase ArcGIS.zip",
"format": "zip",
"accessURL": "https://gdr.openei.org/files/1304/Brady_geodatabase.zip",
"mediaType": "application/zip",
"description": "Geodatabase structure for use with ArcGIS. Includes geodatabase files (.gbd) which can be brought into ArcGIS. This data follows the three categories of data that are outlined in the geodatabase design document"
}
]
|
| DOI | 10.15121/1797281 |
| identifier | https://data.openei.org/submissions/7422 |
| issued | 2021-04-27T06:00:00Z |
| keyword |
[
"AI",
"ArcGIS",
"Brady",
"Brady Well",
"Brady hot springs",
"GIS",
"LST",
"Nevada",
"SVM",
"SWIR",
"anomaly detection",
"artificial intelligence",
"blind",
"blind system",
"conceptual model",
"database",
"deep learning",
"deformation",
"energy",
"exploration",
"fault",
"field data",
"geodatabase",
"geophysical",
"geophysics",
"geospatial data",
"geospatial database",
"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/1304 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2021-09-07T17:48:14Z |
| 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":[[[-119.2167,39.5883],[-118.8167,39.5883],[-118.8167,39.9883],[-119.2167,39.9883],[-119.2167,39.5883]]]}"
|
| title | Brady Geodatabase for Geothermal Exploration Artificial Intelligence |
