Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence 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 Desert Peak Geothermal Field.
Citation Formats
Colorado School of Mines. (2021). Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence [data set]. Retrieved from https://dx.doi.org/10.15121/1797282.
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence. United States: N.p., 27 Apr, 2021. Web. doi: 10.15121/1797282.
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, & Jin, Ge. Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence. United States. https://dx.doi.org/10.15121/1797282
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. 2021. "Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence". United States. https://dx.doi.org/10.15121/1797282. https://gdr.openei.org/submissions/1305.
@div{oedi_4090, title = {Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence}, author = {Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge.}, abstractNote = {These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence 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 Desert Peak Geothermal Field.}, doi = {10.15121/1797282}, url = {https://gdr.openei.org/submissions/1305}, journal = {}, number = , volume = , place = {United States}, year = {2021}, month = {04}}
https://dx.doi.org/10.15121/1797282
Details
Data from Apr 27, 2021
Last updated Jul 9, 2021
Submitted Apr 28, 2021
Organization
Colorado School of Mines
Contact
Jim Moraga
303.273.3768
Authors
Original Source
https://gdr.openei.org/submissions/1305Research Areas
Keywords
geothermal, energy, geodatabase, Nevada, Desert Peak, artificial intelligence, AI, raw data, processed data, remote sensing, hyperspectral, machine learning, deep learning, exploration, ArcGIS, model, site detection, anomaly detection, geothermal site detection, database, hydrothermal, geophysics, radar, short wavelength infrared, SWIR, Support Vector Machine, SVM, land surface temperature, LST, well, GIS, blind, blind system, hyperspectral imaging, geophysical, deformation, conceptual model, fault, preprocessed, geospatial dataDOE Project Details
Project Name Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning
Project Lead Mike Weathers
Project Number EE0008760
