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The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This dataset focuses on ecological change observation over ten years of field observation at 134 plots within two sites that are located in Southwestern of Wyoming, USA from 2008-2018. At sites 1 and 3, 134 long-term field observation plots were measured annually from 2008 to 2018. General plot locations were selected in 2006 using segments and spectral clusters on QuickBird imagery to identify the best locations for representing the variability of the entire site (one QuickBird image). Ground measurements were conducted using ocular measurements with cover was estimated from...
Categories: Data;
Tags: Land Use Change,
Landsat Path/Row,
Landsat time-series,
Southwest Wyoming,
U.S.,
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...
This work centers on using remote-sensing tools and protocols for monitoring long-term changes in vegetation cover across the WLCI region. This information is crucial for understanding patterns of change within sagebrush habitats, including historical changes and potential trajectories of future changes. Our study targets five components of vegetation cover: all shrubs, sagebrush shrubs, herbaceous vegetation, litter, and bare ground, which we quantify by one-percent intervals. Based on samples collected both in the field and from satellite imagery, the USGS can evaluate and quantify the amount and distribution of long-term changes in the target components. This work and its associated products represent the operational...
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...
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...
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...
Monitoring rangelands by identifying the departure of contemporary conditions from long-term ecological potential allows for the disentanglement of natural biophysical gradients driving change from changes due to land uses and other disturbance types. We developed maps of ecological potential (EP) for shrub, sagebrush (Artemisia spp.), perennial herbaceous, litter, and bare ground fractional cover in Wyoming, USA. EP maps correspond to the potential natural vegetation cover expected by environmental conditions in the absence of anthropogenic and natural disturbance as represented by the best growing conditions and least disturbed period of the Landsat archive. EP was predicted using regression tree models with inputs...
In 'Predicted (1989-2015) and forecasted (2015-2114) rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA (ver. 2.0, January 2021)', we provide spatially- and temporally-explicit maps of predictions for the rate of change and time to recovery and percent recovery of sagebrush cover after 100 years (Monroe et al. 2020). The rasters beginning with "sage.rate" depict the predicted annual rate of change in sagebrush cover for each timestamp interval, across the Wyoming Landscape Conservation Initiative area (WLCI) in southwestern Wyoming, USA (1989-2015). The files 'time_to_recov_v2.0.tif' and 'perc_recov_v2.0.tif' are rasters for predicted time to recovery...
Work Accomplished in FY2009 and Findings Eight Landsat- and eight AWiFS-based habitat-component models were completed for the WLCI area, including estimates of cover percentage for shrub, herbs, litter, sagebrush, big 48 sagebrush, Wyoming sagebrush, and bare ground, and for shrub height. According to an independent accuracy assessment, primary root mean square error (RMSE) values for habitat components based on QuickBird (2.4-m resolution) ranged from 4.90 to 10.16; those based on Landsat (30-m resolution) ranged from 6.04 to 15.85; and those based on AWiFS (56-m resolution) ranged from 6.97 to 16.14. The models improved the state-wide characterization of categorical landcover classes by 8 percent over the National...
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