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Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...
Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. The analysis was performed using ENVI's Target Detection process against USGS library spectra for Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite...
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-proces...
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 ar...
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 (po...
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
This layer contains the weakened basement rocks. Isostatic gravity was utilized to identify structural basin areas, characterized by gravity low values reflecting weakened basement rocks. Together interpreted regional fault zones and basin outlines define geothermal "exploration f...
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas.
This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.
The data is associated to the Fallon FORGE project and includes LiDAR from the Navy GPO. Also included are geologic maps from the USGS and Nevada Bureau of Mines and Geology for the Fallon, NV area.
Light Detection and Ranging (LiDAR) data for the Maui study area in South Maui, collected by Watershed Sciences, Inc. (WS) on October 29th, 2011 and from November 7th, 2011 to November 10th, 2011.
This data set includes Light Detection and Ranging (LiDAR) data, a remote sensing processing report, and a geologic map of the Glass Buttes study area for ORMAT.
The total area flown for the LiDAR remote sensing was 86,631 acres to fully encompass the area of interest (84,849 ac...
Shallow temperature surveys are useful in early-stage geothermal exploration to delineate surface outflow zones, with the intent to identify the source of upwelling, usually a fault. Detailed descriptions of the 2-meter survey method and equipment design can be found in Coolbaugh ...
This layer contains the areas identified as areas of anomalous surface temperature from ASTER satellite imagery. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. Areas that had temperature greater than 2o, and ar...
This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the greater th...
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
This layer contains areas of anomalous surface temperature in Archuleta County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming ...
This layer contains areas of anomalous surface temperature in Dolores County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming so...
This layer contains areas of anomalous surface temperature in Garfield County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming s...
This layer contains areas of anomalous surface temperature in Routt County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming sola...
This layer contains areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. ...
Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the grea...
Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the grea...
Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the grea...
This layer contains the areas identified as areas of anomalous surface temperature from Landsat satellite imagery in Western Colorado. Data was obtained for two different dates. The digital numbers of each Landsat scene were converted to radiance and the temperature was calculated...
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