Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content
  • Feedback

    • Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

    Metadata Updated: January 20, 2025

    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

    Access & Use Information

    Public: This dataset is intended for public access and use. License: Creative Commons Attribution

    Downloads & Resources

    Dates

    Metadata Created Date January 11, 2025
    Metadata Updated Date January 20, 2025

    Metadata Source

    Harvested from OpenEI data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date January 11, 2025
    Metadata Updated Date January 20, 2025
    Publisher Colorado School of Mines
    Maintainer
    Doi 10.15121/1773692
    Identifier https://data.openei.org/submissions/7406
    Data First Published 2020-09-01T06:00:00Z
    Data Last Modified 2021-05-17T16:03:00Z
    Public Access Level public
    Bureau Code 019:20
    Metadata Context https://openei.org/data.json
    Metadata Catalog ID https://openei.org/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Data Quality True
    Datagov Dedupe Retained 20250120155001
    Harvest Object Id 22f906db-eead-44ce-a957-75a82056779f
    Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
    Harvest Source Title OpenEI data.json
    Homepage URL https://gdr.openei.org/submissions/1288
    License https://creativecommons.org/licenses/by/4.0/
    Old Spatial {"type":"Polygon","coordinates":-119.2167,39.55,-118.75,39.55,-118.75,39.9883,-119.2167,39.9883,-119.2167,39.55}
    Program Code 019:006
    Projectlead Mike Weathers
    Projectnumber EE0008760
    Projecttitle Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning
    Source Datajson Identifier True
    Source Hash a9e3bef81411ac88339efedaee621a6cd853cff9cdb0bbfc6143c594af48ce55
    Source Schema Version 1.1
    Spatial {"type":"Polygon","coordinates":-119.2167,39.55,-118.75,39.55,-118.75,39.9883,-119.2167,39.9883,-119.2167,39.55}

    Didn't find what you're looking for? Suggest a dataset here.