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Rangeland Vegetation Map Products

The following is a curated list of vegetation map products (as of June 2021) that are most applicable to upland rangeland vegetation assessment and management applications within the state of Oregon (many are also available across the western US). More information on the broader suite of rangelandstools and resources can be found on the Rangeland Assessment and Management Tools resource page, including a guidance document for tips on how to approach the use of maps, steps for evaluating or choosing a product, and options for summarizing maps for an area of interest. 

Rangeland Analysis Platform (RAP)Image of rangeland analysis map viewer

Produced by: University of Montana, 2022
Description: This product provides continuous cover maps of major rangeland vegetation functional groups at yearly intervals from 1984 to 2021 across the western US. The mapping process merges machine learning and cloud-based computing with remote sensing and field data to provide continuous vegetation cover maps. RAP version 3 (available as of January 2022) incorporates updated plots and imagery and uses an improved algorithm to improve predictions.
Map product(s) available: Annual forbs and grasses, Perennial forbs and grasses, Shrubs, Trees, Bare ground. Other products include biomass maps (herbaceous, perennial and annual) at annual and 16-day intervals and fire probabilitey maps for the Great Basin.
Spatial extent: Western US.
Time frame: Yearly maps for all years from 1984-2019. Maps will be updated annually in the future.
Imagery source: Landsat satellite imagery.
Plot data source: Natural Resources Conservation Service (NRCS) Natural Resources Inventory (NRI) plots, Bureau of Land Management (BLM) Assessment Inventory and Monitoring (AIM) and Landscape Monitoring Framework (LMF) plots.
Web viewer: A web viewer allows users to view data layers in an interactive map and generate graphs of average values for each year across a user-defined area of interest. The main RAP page contains other tools and resources.
Data download: Data can be downloaded by year (rasters sizes are very large but there are instructions for how to clip data) or accessed through Google Earth Engine.
Notes: Error ranges are provided for each mapped functional group. RAP version 2 and 3 maps improve the distributional accuracy of predicted values substantially (better representing low and high cover values). In some years and some places, artifacts of the satellite imagery appear as stripes or gaps that do not reflect patterns on the ground.
Documentation: The RAP Support Page addresses many user questions in addition to documentation in the publication (below).
Publication: Allred, B.W., B.T. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M.C. Duniway, L.M. Ellsworth, T.A. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. McCord, D.E. Naugle, H.D. Starns, D. Twidwell, and D.R. Uden. 2021. Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty. Methods in Ecology and Evolution.

Rangeland Condition, Monitoring, Assessment and Projection (RCMAP)Screenshot of MLRC shrubland vegetation map

Produced by: Multi-Resolution Land Cover Characteristics (MRLC) Consortium, 2021
Description: The RCMAP (formerly 'NLCD Shrubland') products characterize shrubland vegetation across the Western United States by quantifying the proportion of shrub, sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, as well as the height of shrubs and sagebrush. Other products include projections of future vegetation, maps of land cover classes, and maps of site potential.
Map product(s) available: Map products include static maps of 2016 conditions: Fractional cover of shrub, sagebrush, big sagebrush, herbaceous, annual herbaceous, bare ground, litter, shrub height, and sagebrush height. Back-in-time (BIT) extend from 1985 to current.
Spatial extent: Western US rangelands.
Time frame: Static maps represent 2016 conditions. Back-in-time maps show fractional cover each year from 1985 - present.
Imagery source: WorldView-2 and Landsat 5, 7 and 8 imagery.
Plot data source: Independent training and validation plots collected.
Web viewer: The NLCD Interactive Viewer displays map products, including static maps, back-in-time maps from 1985-2018 and temporal trend maps.
Data download: Data are downloadable from the RCMAP Data page, and Time Series Trends and other related datasets are also available.
Notes: Error estimates for each mapped component can be found in the metadata. Values in the map represent modeled fractional cover of rangeland components in every pixel, which may vary from field-measured cover values. Maps should generally be interpreted on a relative scale (e.g., identifying areas with relatively high and low values) rather than an absolute scale (e.g., using maps to identify areas above a 10% cover threshold). Trend over time maps include a t-statistic that reflects confidence in change modeled in each pixel.
Documentation: Documentation, including information about the methodology and accuracy of the products, is in the metadata associated with each map.
Publication: A list of related publications is provided on the NLCD website. Primary citation: Rigge, M., H. Shi, C. Homer, P. Danielson, and B. Granneman. 2019. Long-term trajectories of fractional component change in the Northern Great Basin, USA. Ecosphere: e02762.

LandCARTScreenshot of LandCART

Produced by: University of California Los Angeles, 2022
Description: LandCART provides multiple tools for specific applications: 1. Cover Tool to calculate an indicator for a specific location, 2. Cover Change Tool to compare an indicator for an area at two different times, 3. Time Series Tool to calculate change over time, and 4. Spatial Compare Tool to compare an indicator for two different locations at the same time.
Map product(s) available: Maps of BLM AIM and LMF indicators.
Spatial extent: Western US rangelands.
Time frame: Multiple, depending on the tool.
Imagery source: Enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) imagery.
Plot data source: Independent training and validation plots collected.
Web viewer: Web viewing and summarization occurs within each of the four tools accessible through the main LandCART page.
Data download: Data can be downloaded from the web viewer for each tool.
Documentation: A User Guide documents each tool.
Publication: B Zhou, GS Okin, J. Zhang. 2020. Leveraging Google Earth Engine (GEE) and machine learning algorithms to incorporate in situ measurement from different times for rangelands monitoring. Remote Sens Environ, 236, Article 111521, 10.1016/j.rse.2019.111521.

Near-Real-Time Herbaceous Annual Cover in the Great BasinScreenshot of herbaceous annual cover map

Produced by: United States Geological Survey, 2018
Description: Maps provide near-real-time spatial estimates of herbaceous annual vegetation percent cover across the Great Basin at multiple time points each year based on Normalized Difference Vegetation Index (NDVI), which provides an estimate of vegetation greenness.
Map product(s) available: Herbaceous annual cover.
Spatial extent: Western US rangelands.
Time frame: Multiple maps of spring conditions for 2017-2018, and yearly spring maps for 2000-2016. Updates are planned each spring.
Imagery source: Enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) imagery.
Plot data source: Independent training and validation plots collected.
Web viewer: None.
Data download: Maps are accessible from a main webpage.
Notes: Values in the map represent relative abundances, which can vary from field-measured cover values, especially because . Maps should generally be interpreted on a relative scale (e.g., identifying areas with relatively high and low values) rather than an absolute scale (e.g., using maps to identify areas above a 10% cover threshold). The spatial resolution (cell size) is 250m, making it less suitable for landscapes with complex topographic or other spatial features. Comparing this dataset to others with different spatial resolutions (e.g., 30m pixels) may reveal substantial differences in pixel values.
Documentation: Documentation in the publication and Sciencebase.
Publication: Boyte, S.P, B.K. Wylie, and D.J. Major. 2016. Cheatgrass percent cover change: Comparing recent estimates to climate change-driven predictions in the northern Great Basin. Rangeland Ecology and Management 69:265-279.


Southeast Oregon NN Vegetation Composition Map  

Image of sage-grouse data viewer

Produced by: Institute for Natural Resources, 2018
Description: This product provides a wide range of mapped attributes depicting percent cover of vegetation components across the rangelands in Oregon. It uses a nearest neighbor (NN) imputation approach to join vegetation plot data (percent cover by species) to pixels based on remotely sensed imagery and other data layers such as soils, topography, and slope. This approach allows flexibility in how vegetation is summarized; for instance, grasses can be summarized into categories including perennial grasses, deep-rooted perennial grasses, invasive annual grasses, seeded non-native grasses, and others.
Map product(s) available: Primary maps include: Threat-based model ecostate map, Perennial grass cover, Invasive annual grass cover, Sagebrush cover, and Tree cover. Other mapped indicators are available with the full map package (e.g. Deep-rooted perennial grass cover, Early seral shrub cover, etc).
Spatial extent: All rangelands in Oregon.
Time frame: Single time frame representing 2012-2017. Update frequency is likely to be every 2-3 years.
Imagery source: Primarily Landsat satellite imagery with the addition of texture metrics derived from NAIP air photos (see Western juniper canopy cover in Oregon, below).
Plot data source: Most plots were from the Bureau of Land Management (BLM) Assessment Inventory and Monitoring (AIM) (years 2016-2017) and Landscape Monitoring Framework (LMF) (years 2011-2015), with a few other sources (listed in the documentation).
Web viewer: None
Data download: Map and documentation can be accessed through the direct data download link (note: this link automatically downloads a zip file).
Notes: This map may have lower spatial precision than other maps (i.e., may not reproduce fine-scale spatial patterns as well). However, the distribution of values is unbiased, meaning that the full range of data values are present in the map, and low and high cover values are both represented in appropriate proportions. This map should generally not be used at fine spatial scales (hundreds of acres or less), and accuracy levels vary widely depending on the variable being mapped. An accuracy assessments describing both precision and bias for all distributed variables are included with the documentation.
Documentation: Documentation and accuracy assessment is posted here and included with the full data download.
PublicationHenderson, E.B., Bell, D.M. and Gregory, M.J., 2019. Vegetation mapping to support greater sagegrouse habitat monitoring and management: multior univariate approach? Ecosphere, 10(8).

Oregon Sage-Grouse Threat Based Framework MappingImage of Sage-Grouse Threat Based Framework Map

Produced by: Open Range Consulting, 2018
Description: This product uses a proprietary process called Earth Sense Technology to create "ABCD maps" of ecological states from a threat-based model across 8 sage-grouse priority areas for conservation (PACs). Maps were developed based on photo points categorized into ABCD states (rather than continuous percent cover data used in many other products).
Map product(s) available: ABCD map for overall area, Individual ABCD maps for each of 8 sage-grouse PACs. Maps are categorical, with 11 categories.
Spatial extent: Covers roughly 2/3 of Oregon rangelands, excluding SE and NW portions.
Time frame: Single time frame representing 2016-2017. Update frequency is unknown.
Imagery source: 2014 and 2016 NAIP air photos.
Plot data source: No plot data, modeling was based on photo points.
Web viewer: None.
Data download: Layers are not currently available.
Notes: Maps for individual PACs were developed to have the best accuracies for each PAC and can be used separately for individual areas. The overall dataset was created to have seamless coverage across all PACs, but has lower accuracy over the larger area. Overall accuracy percentage for each area is provided in the documentation.
Documentation: Documentation provided as a PDF file with data.
Publication: Sant, E.D., Simonds, G.E., Ramsey, R.D and Larsen, R.T. 2014. Assessment of sagebrush cover using remote sensing at multiple spatial and temporal scales. Ecological Indicators 43: 297–305.

Western Juniper Canopy Cover in OregonScreenshot of juniper cover map

Produced by: Institute for Natural Resources, 2016
Description: A suite of juniper and tree mapping products have been developed for the state of Oregon using nested texture metrics derived from Natural Agricultural Imagery Program (NAIP) imagery. The Western juniper canopy cover dataset provides cover estimate for juniper over 7’ in height across eastern Oregon and may be particularly useful for characterizing juniper cover.
Map product(s) available: Western juniper canopy cover, Western juniper basal area, Western juniper estimated maximum age, Western juniper density (multiple maps for size classes), Tree cover within the range of western juniper, Western juniper presence, Southeast Oregon ancient juniper.
Spatial extent: Eastern Oregon.
Time frame: Single time frame representing 2012-2013.
Imagery source: NAIP air photos and Landsat 8 satellite imagery.
Plot data source:  US Forest Service Forest Inventory and Analysis (FIA) plot data and LiDAR height estimates, where available.
Web viewer: None.
Data download: The full list of juniper data can be downloaded through the Oregon Spatial Data Library. The Western juniper canopy cover layer for Oregon is linked directly here.
Notes: The Oregon juniper and tree maps have relatively high accuracy with low bias - see accuracy report. Other tree species are sometimes confused for juniper in the maps, and in some versions of the map other features (e.g. roads) may cause errors in the map.
Documentation: Documentation can be found on the Conservation Gateway site.
Publication: No peer-reviewed publication.

Tree Canopy Cover (Spatial Wavelet Analysis) In Rangelands

Screenshot of tree cover in rangelands map Produced by: Colorado State University, 2017
Description: High resolution maps of tree canopy cover (1 m resolution) were produced from Natural Agricultural Imagery Program (NAIP) imagery by using spatial wavelet analysis.
Map product(s) available: Tree canopy cover.
Spatial extent: Western US, including all Oregon rangelands.
Time frame: Single time frame representing 2012-2013.
Imagery source: NAIP air photos.
Plot data source: None.
Web viewer: Map is viewable in an interactive map through the Sage Grouse Initiative Data Viewer.
Data download: Data downloadable by state on the data download page.
Notes: Map accuracy is high, but the accuracy assessment is based on very few validation plots. The maps are targeting conifer cover but may detect non-conifers in some areas. The minimum tree detection size is 2-3m in diameter, meaning very small trees will not be detected.
Documentation: Documentation provided on the data download page and in the publication.
Publication: Falkowski et al. 2017. Mapping tree canopy cover in support of proactive prairie grouse conservation in western North America. Rangeland Ecology & Management 70:15-24.


This list was developed for the Oregon SageCon Partnership by the Institute for Natural Resources, and views represent the best understanding of the author for rangeland management applications within Oregon.

Other Resources for Rangeland Remote Sensing


Authored by Megan Creutzburg, Institute for Natural Resources, Oregon State University (2022)