Description
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model:
- brady_som_output.gri, brady_som_output.grd, brady_som_output.
- desert_som_output.gri, desert_som_output.grd, desert_som_output.
The data corresponds to two sites: Brady Hot Springs and Desert Peak, both located near Fallon, NV.
Input layers include:
- Geothermal: Labeled data (0: Non-geothermal; 1: Geothermal)
- Minerals: Hydrothermal mineral alterations, as a result of spectral analysis using Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite
- Temperature: Land surface temperature (% of times a pixel was classified as "Hot" by K-Means)
- Faults: Fault density with a 300mradius
- Subsidence: PSInSAR results showing subsidence displacement of more than 5mm
- Uplift: PSInSAR results showing subsidence displacement of more than 5mm
Also, the results of the classification using Brady and Desert Peak to build 2 Convolutional Neural Networks. These were applied to the training site as well as the other site, the results are in GeoTiff format.
- brady_classification: Results of classification of the Brady-trained model
- desert_classification: Results of classification of the Desert Peak-trained model
- b2d_classification: Results of classification of Desert Peak using the Brady-trained model
- d2b_classification: Results of classification of Brady using the Desert Peak-trained model
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| AI-Geothermal_InputFiles.zip | ZIP | Compressed file with all input files for training and testing the AI | Open resource |
| b2d_classification.tif | TIFF | Results of machine learning classification of Desert Peak using the Brady-trained model | Open resource |
| brady_classification.tif | TIFF | Results of machine learning classification of the Brady Springs-trained model | Open resource |
| brady_som_output.grd | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| brady_som_output.grd.aux.xml | XML | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| brady_som_output.grd.xml | XML | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| brady_som_output.gri | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| brady_som_output.hdr | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| brady_som_output.stx | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| d2b_classification.tif | TIFF | Results of machine learning classification of Brady using the Desert Peak-trained model | Open resource |
| desert_classification.tif | TIFF | Results of machine learning classification of the Desert Peak-trained model | Open resource |
| desert_som_output.grd | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| desert_som_output.gri | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| desert_som_output.gri.aux.xml | XML | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| desert_som_output.gri.ovr | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |
| desert_som_output.hdr | Unknown | Labeled dataset, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model | Open resource |