Filters: Tags: bare ground (X) > partyWithName: Matthew B Rigge (X)
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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. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios...
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....
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...
Rangelands have immense inherent spatial and temporal variability, yet assessments of land condition and trends are often assessed relative to the condition of a limited number of representative points. Ecological Potential (EP) data are spatially comprehensive, quantitative, and needed as a baseline for comparison of current rangeland vegetation conditions, trends, and management targets. We define EP as the potential fractional cover of vegetation components bare ground, herbaceous, litter, shrub, and sagebrush represented in the least disturbed and most productive portion of the western U.S. This dataset enables: 1) setting realistic expectations for restoration and management targets at 30-meter resolution,...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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 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 the full sagebrush (Artemisia spp.) biome. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2018 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate...
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...
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...
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