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Zanskar Geothermal & Minerals

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This dataset contains public geothermal and geophysical data for the Great Basin region of the United States, including well and spring data, fault locations, volcanic centers, earthquake locations, gravity, conductance, magnetics, and depth to basement. It can be used for geothermal energy exploration, energy demand forecasting, earth science research, and environmental studies. The original publicly available data was originally compiled by the IN novative G eothermal E xploration through N ovel I nvestigations O f U ndiscovered S ystems (INGENIOUS) project by the Great Basin Center for Geothermal Energy (GBCGE), Nevada Bureau of Mines and Geology (NBMG), and University of Nevada, Reno (UNR). The original public data can be accessed at https://gdr.openei.org/submissions/1391 Note this is NOT the original data provided by INGENIOUS. This data has been mapped to a 1 km mesh grid to facilitate quick analysis and machine learning. The H3 features added by Zanskar Geothermal & Minerals allow the data to be quickly aggregated or joined with other datasets for use in geospatial machine learning. (See https://h3geo.org/ for more information.) This data share contains 11 geospatial tables useful for geothermal exploration: CONDUCTANCE_GRIDS_INGENIOUS DEPTH_TO_BASEMENT_GRID_INGENIOUS EARTHQUAKE_DENSITY_N100A15_GRID_INGENIOUS FAULT_GEOMETRY_INGENIOUS, GB_VENTS_INGENIOUS GEODETIC_GRIDS_INGENIOUS GRAVITY_HGM_GRID_INGENIOUS HEATFLOW_GRID_INGENIOUS INGENIOUS_SPRING_TEMPERATURE INGENIOUS_WELL_FEATURES MAGNETIC_RTP_HGM_GRID_INGENIOUS We also provide a grid with H3 blocks and the corresponding latitude and longitude of the grid center points. This table can be used to map additional features to the same grid. INGENIOUS_GRID_EXTENT Zanskar processing details: The data was sampled using an H3 grid resolution of 8, which has an average edge length of 0.531 km, for a full grid size of 679,826 cells. The distance to quaternary volcanic centers was calculated with Snowflake's k-ring distance transformation H3_GRID_DISK. Similarly, faults were buffered to a larger size also with H3_GRID_DISK. A k-ring distance of 10 km was used for faults and 20 for volcanic centers. For raster datasets, the publicly available geospatial tool QGIS was used to sample values onto the H3 grid. Point and line geometries were converted to H3 cells using Snowflake tools such as H3_COVERAGE_STRINGS and H3_LATLNG_TO_CELL_STRING, ensuring spatial alignment and consistency across datasets.

For more details on the data processing and how this data can help in geothermal exploration, please see https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2025/Grujic.pdf

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Intelligence Score
19/100
Your Rating
Platforms

1

Domain

zanskar.us

Data Quality SignalsD

Freshness

Single-source

API Status

No API

44Completeness

Compliance (vendor-reported)

SOC 2
ISO 27001
GDPR
CCPA

Quality Breakdown

Data Coverage
20
Documentation
75
Compliance
0
Pricing Clarity
0

Signal Analysis

Categories

GeospatialMachine Learning

Listed On

snowflake_marketplace
Intelligence Scores3/7 pillars scored
Market Presence
14
Integration
20
Business Maturity
3
Extended Analytics

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About Zanskar Geothermal & Minerals

Zanskar Geothermal & Minerals is an alternative data vendor. Zanskar Geothermal & Minerals specializes in geospatial, machine learning data. This vendor has a Vedex Intelligence Score of 19 out of 100, reflecting market presence, compliance posture, integration readiness, and business maturity.

Data Categories

Zanskar Geothermal & Minerals operates in the following alternative data categories.

GeospatialMachine Learning

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