U.S. Geological Survey Matthew Rigge Brett Bunde Kory Postma 20241204 vector digital data Earth Resources Observation and Science Center, Sioux Falls, SD U.S. Geological Survey Rigge, M., Homer, C., Cleeves, L., Meyer, D.K., Bunde, B., Shi, H., Xian, G., Schell, S. and Bobo, M., 2020. Quantifying western US rangelands as fractional components with multi-resolution remote sensing and in situ data. Remote Sensing, 12(3), p.412. Xian, G., Homer, C., Rigge, M., Shi, H. and Meyer, D., 2015. Characterization of shrubland ecosystem components as continuous fields in the northwest United States. Remote Sensing of Environment, 168, pp.286-300. https://doi.org/10.5066/P13Y9PSG https://www.mrlc.gov/data Matthew Rigge Hua Shi Kory Postma Brett Bunde 20220805 Publication (Journal) GIScience and Remote Sensing 59:1, 1243-1265 https://doi.org/10.1080/15481603.2022.2104786 Rangeland ecosystems provide critical wildlife habitat (e.g., greater sage grouse, pronghorn, black-footed ferret), forage for livestock, carbon sequestration, provision of water resources, and recreational opportunities. At the same time, rangelands are vulnerable to climate change, fire, and anthropogenic disturbances. The arid-semiarid climate in most rangelands fluctuates widely, impacting livestock forage availability, wildlife habitat, and water resources. Many of these changes can be subtle or evolve over long time periods, responding to climate, anthropogenic, and disturbance driving forces. To understand vegetation change, scientists from the USGS and Bureau of Land Management (BLM) developed the Rangeland Condition Monitoring Assessment and Projection (RCMAP) project. RCMAP provides robust, long-term, and floristically detailed maps of vegetation cover at yearly time-steps, a critical reference to advancing science in the BLM and assessing Landscape Health standards. RCMAP quantifies the percent cover of ten rangeland components (annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree cover and shrub height) at yearly time-steps across the western U.S. using field training data, Landsat imagery, and machine learning. We utilize an ecologically comprehensive series of field-trained, high-resolution predictions of component cover and BLM Analysis Inventory and Monitoring (AIM) data to train machine learning models predicting component cover over the Landsat time-series. This dataset enables retrospective analysis of vegetation condition, impacts of weather variation and longer-term climatic change, and understanding of vegetation treatment and altered management practice effectiveness. RCMAP data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices. Component products can be downloaded https://www.mrlc.gov/data. Independent validation was our primary validation approach, consisting of field measurements of component cover at stratified-random locations. Independent validation point placement used a stratified random design, with two levels of stratified restrictions to simplify logistics of field sampling (Rigge et al. 2020, Xian et al. 2015). The first level of stratification randomly selected 15, 8 km in diameter, sites across each mapping region. First level sites excluded areas less than 30 km away from training sites and other validation sites. The second level stratification randomly placed 6–10 points within each 8 km diameter validation site (total n = 2,014 points at n = 229 sites). Only sites on public land, between 100 and 1000 m from the nearest road, and in rangeland vegetation cover within each site were considered. The random points within a site were evenly allocated to three NDVI thresholds from a leaf-on Landsat image (low, medium, and high). Sites with relatively high spatial variance within a 90 m by 90 m patch (3 × 3 Landsat pixels) were excluded to minimize plot-pixel locational error. Using NDVI as a stratum ensured plot locations were distributed across the range of validation site productivity. At each validation point, we measured component cover using the line point intercept method along 2, 30 m transects. Data were collected from the first hit perspective. The goal of RCMAP is to provide a Landsat imagery-based time series of rangeland fractional components across Western North America from 1985 to 2023. These data provide an inventory of land cover validated products with estimates of precision for western rangelands. Climate change, shifting fire regimes, and management practices are increasingly impacting the health of the ecosystem. This dataset contributes to improved monitoring of rangeland change at broad temporal and spatial extents. RCMAP components are defined as: Bare Ground is a continuous field component including exposed soil, sand, and rocks. Annual Herbaceous is a continuous field component including grasses and forbs whose life history is complete in one growing season. This component is primarily dominated by annual invasive species including Cheatgrass (Bromus tectorum), Medusahead (Taeniatherum caput-medusae), Red Brome (Bromus rubens), or annual mustards such as Tumble Mustard (Sisymbrium altissimum) and Tansy Mustard (Descurainia pinnata), but it may contain substantial native annual herbaceous vegetation at higher elevations and in California. This component is nested within Herbaceous as a secondary component. Herbaceous is a continuous field component consisting of grasses, forbs and cacti which were photosynthetically active at any point in the year of mapping. Non-sagebrush shrub is a continuous field component encompassing all shrub species not of the sagebrush (Artemisia spp.) genus. Shrubs, in general, are discriminated by the presence of woody stems and less than 6-m in height. Perennial herbaceous is a continuous field component consisting of grasses, forbs and cacti which were photosynthetically active at any point in the year of mapping and whose lifecycle includes more than one growing season (includes biennials). Litter is a continuous field component including dead standing woody vegetation, detached plant organic matter and biological soil crusts. Sagebrush is a continuous field component encompassing almost all species of Sagebrush (Artemisia spp.) including Big Sagebrush (A. tridentata spp.), Low Sagebrush (A. arbuscula), Black Sagebrush (A. nova), Three-tip Sagebrush (A. triparta) and Silver Sagebrush (A. cana). This component is nested within Shrub as a secondary component. Excludes the low stature prairie sage (A. frigida) and white sagebrush (A. ludoviciana). Shrub is a continuous field component encompassing all shrub species discriminated by the presence of woody stems and less than 6-m in height. Tree cover is defined as vegetation with persistent woody stems greater than 6m in height. Mature stand of pinyon (Pinus spp. and juniper (Juniperus spp.) are included regardless of height. Shrub height is the average height of all shrub in centimeters. This component only occurs where the shrub cover component is greater than 0% Height is given for the portion of pixel with shrubs present. For example, in a pixel where shrub cover is 10% and the average height of those shrubs is 100cm, height will be given as 100cm, not 100cm/10% cover as 10cm. Although this Federal Geographic Data Committee-compliant metadata file is intended to document the data set in nonproprietary form, as well as in Esri format, this metadata file may include some Esri-specific terminology. 2013 2023 publication date Complete As needed -128.0026 -99.6758 51.5761 26.5157 ISO 19115 Topic Category biota environment geoscientificInformation imageryBaseMapsEarthCover USGS Thesaurus shrubland ecosystems terrestrial ecosystems Alexandria Digital Library Feature Type Thesaurus shrublands time series back-in-time trends grassland change shrubland change vegetation change climate change rangeland management None shrub sagebrush big sagebrush herbaceous annual herbaceous litter grass vegetation bare ground rangeland shrubland shrub height vegetation height independent validation USGS Metadata Identifier USGS:673ce66ed34e6b795de6b4e1 Common geographic areas United States Washington Oregon Montana North Dakota South Dakota Wyoming Idaho Nebraska Nevada Utah California Colorado Arizona Texas New Mexico Plateau Desert Northern Great Salt Lake Desert Southern Great Salt Lake Desert North Plains Plains The Rockies Canada Alberta Saskatchewan None NM TX AZ CO CA UT NV NE ID WY SD ND MT OR WA Great Basin Arizona Plateau Black Hills Blue Mountains Chihuahuan Desert Colorado Plateau Columbia Plateau Grand Canyon Middle Rockies Rocky Mountains Gunnison Sonoran Desert Southwest Tablelands Three Forks Wasatch Western US Yellowstone Northern Mountainous Mediterranean California Northern Great Plains Northern Rocky Mountains Wyoming Basin Mojave Sonoran Chihuahuan Southern Rocky Mountains Sierra Nevada Mountains AB SK Prairie Provinces Any downloading and use of these data signifies a user's agreement to comprehension and compliance of the USGS Standard Disclaimer. Ensure all portions of metadata are read and clearly understood before using these data to protect both user and USGS interests. There is no guarantee of warranty concerning the accuracy of the data. Users should be aware that these data were developed from models which can contain some local error. Users should not use these data for critical applications without a full awareness of their limitations. Acknowledgement of the originating agencies would be appreciated in products derived from these data. Any user who modifies these data is obligated to describe the types of modifications they perform. User specifically agrees not to misrepresent the data, nor to imply that changes made were approved or endorsed by the U.S. Geological Survey. Please refer to https://www.usgs.gov/privacy.html for the USGS disclaimer. U.S. Geological Survey Customer Services Representative mailing

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Sioux Falls SD 57198-0001 U.S. 605-594-6151 605-594-6589 custserv@usgs.gov U.S. Geological Survey (USGS) Bureau of Land Management (BLM) Environment as of Metadata Creation: Microsoft [Unknown] Version 6.2 (Build 9200); Esri ArcGIS 10.6.1 (Build 9270) Service Pack N/A (Build N/A) Jeremy D. Maestas Steven B. Campbell Jeanne C. Chambers Mike Pellant Richard F. Miller 201606 publication https://www.sciencedirect.com/science/article/pii/S0190052816000109?via%3Dihub https://doi.org/10.1016/j.rala.2016.02.002 Jon E. Keeley Sterling C. Keeley 19810401 publication https://bsapubs.onlinelibrary.wiley.com/doi/abs/10.1002/j.1537-2197.1981.tb07796.x https://doi.org/10.1002/j.1537-2197.1981.tb07796.x Emanuel A. Storey Douglas A. Stow John F. O'Leary 20160915 publication https://www.sciencedirect.com/science/article/pii/S0034425716302176 https://doi.org/10.1016/j.rse.2016.05.018 Validation data were collected by trained field crews who frequently calibrated their measurements. Plot data were screened to ensure primary component (shrub, herbaceous, litter, bare ground, and tree) sums of ~100%. Data were screened to ensure plot sums were ~100% and component relationships were intact (e.g. shrub cover is greater than or equal to sagebrush cover). This independent validation set is the version dated 20241204. Data is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. A formal accuracy assessment of the horizontal positional information in the data set has not been conducted. A formal accuracy assessment of the vertical positional information in the data set has either not been conducted or is not applicable. Independent validation was our primary validation approach, consisting of field measurements of component cover at stratified-random locations. Independent validation point placement used a stratified random design, with two levels of stratified restrictions to simplify logistics of field sampling (Rigge et al. 2020, Xian et al. 2015). The first level of stratification randomly selected 15, 8 km in diameter, sites across each mapping region (Mediterranean California, Great Basin and Columbia Plateau, Northern Rocky Mountains, Northern Great Plains and Wyoming Basin, Warm Deserts [Mojave, Sonoran, and Chihuahuan], Southern Rocky Mountains and Sierra Nevada, Colorado Plateau and Southwest Tablelands), and Pacific Northwest. First level sites excluded areas less than 30 km away from training sites and other validation sites. The second level stratification randomly placed 6–10 points within each 8 km diameter validation site (total n = 2,014 points at n = 229 sites). Only sites on public land, between 100 and 1000 m from the nearest road, and in rangeland vegetation cover within each site were considered. The random points within a site were evenly allocated to three NDVI thresholds from a leaf-on Landsat image (low, medium, and high). Sites with relatively high spatial variance within a 90 m by 90 m patch (3 × 3 Landsat pixels) were excluded to minimize plot-pixel locational error. Using NDVI as a stratum ensured plot locations were distributed across the range of validation site productivity. At each validation point, we measured component cover using the line point intercept method along 2, 30 m transects. Data were collected from the first hit perspective. 2024 Vector Entity point 2014 Albers Conical Equal Area 29.5 45.5 -96.0 23.0 0.0 0.0 row and column 1.0 1.0 meters World Geodetic System 1984 (WGS 84) WGS_1984 6378140.0 298.257 RCMAP Independent Validation Attribute Table Table containing attribute information associated with the data set. Producer Defined FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. Point data. ESRI Coordinates defining the features. POINT_X Point X location. Producer Defined -2246674.686 -453933.5289 POINT_Y Point Y location. Producer Defined 710415.8971 3056043.733 DomVeg Dominant Vegetation. Producer Defined Example: sunflower Shrub Shrub cover value. Producer Defined 0.0 89.0 Sagebrush Sagebrush cover value. Producer Defined 0.0 69.0 BigSage Big Sagebrush cover value. Producer Defined 0.0 69.0 Herb Herbaceous cover value. Producer Defined 0.0 97.0 AnnHerb Annual Herbaceous cover value. Producer Defined 0.0 97.0 Litter Litter cover value. Producer Defined 0.0 85.0 Bare Bare ground cover value. Producer Defined 0.0 100.0 Tree Tree cover value. Producer Defined 0 40 ShrubHt Shrub height value (in cm). Producer Defined 0 450 SageHt Sagebrush height value (in cm). Producer Defined 0 150 Sum Primary component (shrub, herbaceous, litter, bare ground, tree) sum. Producer Defined 99.285714 100.3846154 Measure Measurement (year). Producer Defined 2013 2023 The entity and attribute information provided here describes the tabular data associated with the data set. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as fields/table entries of the data set. The entity and attribute information were generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information. U.S. Geological Survey GS ScienceBase mailing address

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Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Raster Digital Data Set https://doi.org/10.5066/P13Y9PSG None 20241204 U.S. Geological Survey Customer Services Representative mailing and physical

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Sioux Falls SD 57198-0001 U.S. 605-594-6151 605-594-6589 custserv@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998