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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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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 health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Western U.S. rangelands have been quantified as six fractional cover (0-100%) components over the Landsat archive (1985-2018) at 30-m resolution, termed the “Back-in-Time” (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. We leverage field data observed concurrently with HRS imagery over multiple years and locations in the Western U.S. to dramatically expand the spatial extent and sample size of validation analysis relative to a direct comparison to field observations and to previous work. We compare HRS and BIT data in the corresponding space and time. Our objectives were to evaluate the temporal and spatio-temporal relationships between HRS and BIT data, and to compare...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
Tags: AB, AZ, Alberta, Arizona, Arizona Plateau, All tags...
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Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. While a number of studies have projected the impacts of climate change using several modeling approaches, none has evaluated impacts to fractional component cover at a 30-m resolution across rangelands of the Western U.S. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2021 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Expanding human enterprise across remote environments impacts many wildlife species, including sage-grouse (Centrocercus urophasianus), an indicator species whose decline is at the center of national conservation strategies and land use policies. Anthropogenic resources provide subsidies for generalist predators, potentially leading to cascading effects on sensitive prey species at lower trophic levels. In semi-arid western ecosystems, common ravens (Corvus corax) are expanding in distribution and abundance, and may be negatively affecting sage-grouse reproductive success at broad spatial scales. Ravens are a common predator of sage-grouse nests, and potentially prey on chicks as well. This research aimed to address...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
Tags: AB, AZ, Alberta, Arizona, Arizona Plateau, All tags...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
Tags: AB, AZ, Alberta, Arizona, Arizona Plateau, All tags...
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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 health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
This presentation aired as part of the Great Basin LCC webinar series on November 29, 2017. The presentation was given by Bruce Roundy of Brigham Young University.In this webinar, Dr. Bruce Roundy of Brigham Young University discusses climatic conditions that favor cheatgrass and those that favor desirable perennial herbs. He explains why conditions that favor cheatgrass are associated with less resistance and those that favor perennial herbs are associated with more resilience. The presentation suggests ways to increase resistance to weeds and system resilience when planning fuel control treatments in sagebrush steppe.
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To map the baseline distribution of riparian forest and shrublands, we all included LANDFIRE Existing Vegetation Types (EVT) where the type contained the word "riparian", "woodland", "ravine" and "swamp". We also included aspen woodlands at elevations below 1524 m using ReGAP values, as these areas, upon inspection were found to be introduced vegetation and not aspen. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness,...
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This raster dataset quantifies the relative flow patterns of structural sagebrush connectivity in the sagebrush biome at 270-meter resolution. Connectivity was calculated using an omnidirectional circuit-based algorithm, with sources, targets, and conductance based on sagebrush fractional component from the RCMAP sagebrush products for 1985, 1990, 1995, 2000, 2005, 2010, 2015, and 2020. Normalized cumulative current density was used to represent relative flow of connectivity and binned into 3 relative flow classes (impeded, diffuse, and channelized flow). We calculated the relative flow temporal trends for channelization and impedance between 1985 and 2020 to identify areas that were becoming more channelized or...
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This raster dataset quantifies the structural sagebrush connectivity in the sagebrush biome at 270-meter resolution. Connectivity was calculated using an omnidirectional circuit-based algorithm, with sources, targets, and conductance based on sagebrush fractional component from the RCMAP sagebrush products for 1985, 1990, 1995, 2000, 2005, 2010, 2015, and 2020. Cumulative current density was used to represent connectivity and binned into 20 quantile-based classes.
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Categories: Data; Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...


map background search result map search result map Data from: Broad-scale occurrence of a subsidized avian predator: reducing impacts of ravens on sage-grouse and other sensitive prey BLM REA WYB 2011 Ch10 Riparian Temporal and Spatio-Temporal High-Resolution Satellite Data for the Validation of a Landsat Time-Series of Fractional Component Cover Across Western United States (U.S.) Rangelands Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Bare Ground Products for the Western U.S., 1985 - 2018 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Annual Herbaceous Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Litter Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Sagebrush Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Shrub Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Trends Rangeland Condition Monitoring Assessment and Projection (RCMAP) Annual Herbaceous Fractional Component Time-Series Across the Western U.S. 1985-2021 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Sagebrush Fractional Component Time-Series Across the Western U.S. 1985-2021 Time series of circuit-based relative flow patterns for sagebrush structural connectivity from 1985 to 2020 Time series of circuit-based sagebrush structural connectivity from 1985 to 2020 Projections of Rangeland Fractional Component Cover Across Western US Rangelands for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across Western North America from 1985-2023 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Herbaceous Fractional Component Time-Series Across Western North America from 1985-2023 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Trends Fractional Component Time-Series Across Western North America from 1985-2023 Temporal and Spatio-Temporal High-Resolution Satellite Data for the Validation of a Landsat Time-Series of Fractional Component Cover Across Western United States (U.S.) Rangelands Data from: Broad-scale occurrence of a subsidized avian predator: reducing impacts of ravens on sage-grouse and other sensitive prey BLM REA WYB 2011 Ch10 Riparian Time series of circuit-based relative flow patterns for sagebrush structural connectivity from 1985 to 2020 Time series of circuit-based sagebrush structural connectivity from 1985 to 2020 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across Western North America from 1985-2023 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Herbaceous Fractional Component Time-Series Across Western North America from 1985-2023 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Trends Fractional Component Time-Series Across Western North America from 1985-2023 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Annual Herbaceous Fractional Component Time-Series Across the Western U.S. 1985-2021 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Sagebrush Fractional Component Time-Series Across the Western U.S. 1985-2021 Projections of Rangeland Fractional Component Cover Across Western US Rangelands for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Bare Ground Products for the Western U.S., 1985 - 2018 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Annual Herbaceous Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Litter Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Sagebrush Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Shrub Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 - Trends