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Federal
BLM Natl AIM Riparian and Wetland Indicators Hub
Department of the Interior —
This feature class includes monitoring data collected nationally to understand the status, condition, and trend of resources on BLM lands. Data are collected in... -
Federal
BLM Natl WesternUS GRSG ROD HabitatMgmtAreas Feb 2026
Department of the Interior —
This dataset represents the consolidated submissions of Greater Sage-Grouse habitat management areas from each individual BLM 2025 Greater Sage-Grouse Approved... -
Federal
Theodore Roosevelt National Park Small-Scale Base GIS Data
Department of the Interior —
This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2021
Department of the Interior —
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using... -
Federal
BLM Natl AIM Terrestrial Species Indicators Public
Department of the Interior —
Species indicator data from AIM Terrestrial datasets TerrADat and LMF. AIM Terrestrial includes monitoring data collected nationally to understand the status,... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across Western North America from 1985-2023
Department of the Interior —
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021
Department of the Interior —
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using... -
Federal
Data release: Process-based predictions of lake water temperature in the Midwest US
Department of the Interior —
Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give... -
Federal
National Assessment of Oil and Gas Project - Williston Basin Province (031) Boundary
Department of the Interior —
The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces.... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Annual Herbaceous Fractional Component Time-Series Across the Western U.S. 1985-2021
Department of the Interior —
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020
Department of the Interior —
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using... -
Federal
Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018
Department of the Interior —
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Litter Fractional Component Time-Series Across Western North America from 1985-2023
Department of the Interior —
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using... -
Federal
Process-based water temperature predictions in the Midwest US: 5 Model prediction data
Department of the Interior —
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin.... -
Federal
Rangeland Condition Monitoring Assessment and Projection (RCMAP) Independent Validation Data
Department of the Interior —
Rangeland ecosystems provide critical wildlife habitat (e.g., greater sage grouse, pronghorn, black-footed ferret), forage for livestock, carbon sequestration,... -
Federal
Process-based water temperature predictions in the Midwest US: 4 Model inputs (meteorological inputs and ice flags)
Department of the Interior —
This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and is part of a larger data release of lake temperature model inputs and... -
Federal
Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Sagebrush Products for the Western U.S., 1985 - 2018
Department of the Interior —
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem... -
Federal
Shapefiles and Historical Aerial Photographs, Little Missouri River, 1982
Department of the Interior —
4 aerial photographs were taken along the Little Missouri River in 1982. All images were geo-referenced to the 1995 digital orthophoto quarter quadrangles as... -
Federal
5 Model Predictions: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release item contains water temperature predictions for 455 river sites across the U.S. Predictions are from the models described by Rahmani et al. (2021b). -
Federal
BLM Natl AIM TerrADat Hub
Department of the Interior —
This feature class includes monitoring data collected nationally to understand the status, condition, and trend of resources on BLM lands. It focuses on the BLM...