4 Model Code: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Data e Risorse
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Original MetadataXML
The metadata original format
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Digital DataXML
Landing page for access to the data
| Campo | Valore |
|---|---|
| accessLevel | public |
| bureauCode | {010:12} |
| catalog_@context | https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld |
| catalog_conformsTo | https://project-open-data.cio.gov/v1.1/schema |
| catalog_describedBy | https://project-open-data.cio.gov/v1.1/schema/catalog.json |
| identifier | USGS:6084cb16d34eadd49d31aead |
| metadata_type | geospatial |
| modified | 20210927 |
| old-spatial | -124.138658984335, 29.1524975232233, -67.8714112090545, 49.0018341836332 |
| publisher | U.S. Geological Survey |
| publisher_hierarchy | Department of the Interior > U.S. Geological Survey |
| resource-type | Dataset |
| source_datajson_identifier | true |
| source_hash | 17056b98a744b5da909d827dc47c7dd1fb84b004 |
| source_schema_version | 1.1 |
| spatial | {"type": "Polygon", "coordinates": [[[-124.138658984335, 29.1524975232233], [-124.138658984335, 49.0018341836332], [ -67.8714112090545, 49.0018341836332], [ -67.8714112090545, 29.1524975232233], [-124.138658984335, 29.1524975232233]]]} |
| theme | {geospatial} |
| Gruppi |
|
| Tag |
|
| isopen | False |
| license_id | notspecified |
| license_title | License not specified |
| maintainer | Farshid Rahmani |
| maintainer_email | fzr5082@psu.edu |
| metadata_created | 2025-11-22T03:08:00.754097 |
| metadata_modified | 2025-11-22T03:08:00.754102 |
| notes | <p>This data release component contains model code and configurations for the LSTM models used to predict stream temperature.</p> |
| num_resources | 2 |
| num_tags | 110 |
| title | 4 Model Code: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins |