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This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
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Geophysical measurements were collected by the U.S. Geological Survey (USGS) at five sites in Interior Alaska in September 2021 for the purposes of imaging permafrost structure and quantifying variations in subsurface moisture content in relation to thaw features. Borehole nuclear magnetic resonance (NMR) data were collected at two sites in order to determine liquid water content at depth in shallow boreholes. NMR data were collected in a 2.25 m-deep borehole at the North Star golf course adjacent to one of the ERT profiles, and in another two 1.625 m-deep boreholes adjacent to Big Trail Lake where previous NMR measurements were made in 2019 and 2020.
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
Exotic annual grasses [EAG] are one of the most damaging biological stressors in western North America. Despite numerous environmental and societal impacts associated with EAG there remains a need to enhance regional monitoring capabilities to better guide management and conservation efforts. Here we provide estimates of historic and potential future trends in EAG abundance that were developed using linear trend analysis and machine learning techniques at a 30-m spatial resolution. Specifically, these data represent historic (1985 to 2019) and potential future (2025-2040) rates of exotic annual grass change as estimated using Theil-Sen regression and a process-constrained, random forest model assuming only changes...
Exotic annual grasses are one of the most damaging biological stressors in western North America and increase the susceptibility of landscapes to wildfire occurrence. Here we couple estimates of long-term rangeland component fractions (e.g. exotic annual grasses) with remote sensing, climate data, and machine learning techniques to estimate the long-term (1985 to 2019) probability of wildfire occurrence (30-m spatial resolution) in sagebrush-dominated landscapes of the western United States.
Electrical resistivity tomography (ERT) measurements were collected by the U.S. Geological Survey (USGS) at two sites in Interior Alaska in September 2019 for the purposes of imaging permafrost structure and quantifying variations in subsurface moisture content in relation to thaw features. First, ERT data were collected at Big Trail Lake, a thermokarst lake outside of Fairbanks, Alaska, to quantify permafrost characteristics beneath the lake and across its shorelines. Three 222 m ERT survey lines were collected perpendicular to the North, East, and South shorelines, and two 110 m lines were collected parallel to the southeast and northeast shorelines. Models of electrical resistivity produced from these data revealed...
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Fire and hydrology can be significant drivers of permafrost change in boreal landscapes, altering the availability of soil carbon and nutrients that have important implications for future climate and ecological succession. However, not all landscapes are equally susceptible to disturbance. New methods are needed to understand the vulnerability and resilience of different landscapes to permafrost degradation. This project uses remote sensing, geophysical, and other field-based observations to reveal details of both near-surface (<1 m) and deeper (>1 m) permafrost characteristics over multiple scales. This LandCarbon project currently supports the NASA ABoVE project, 'Vulnerability of inland waters and the aquatic...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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The dryland ecosystems of the western United States have been invaded by exotic annual grasses, such as cheatgrass (Bromus tectorum L.), that has promoted increased fire activity and reduced biodiversity detrimental to socio-environmental systems. The use of remote sensing tools to monitor exotic annual grass cover and dynamics over large areas can support early detection and rapid response initiatives. This dataset was generated using in situ observations from Bureau of Land Management's (BLM) Assessment, Inventory, and Monitoring data (AIM) plots, weekly composites of harmonized Landsat and Sentinel-2 (HLS) data, relevant environmental, vegetation, remotely sensed, and geophysical factors and machine learning...
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These datasets provide early estimates of 2021 fractional cover for exotic annual grass (EAG) species and a native perennial grass predicted on July 1 using satellite observation data available no later than June 28th. Four fractional cover maps comprise this release, along with the corresponding confidence maps, for: 1) a group of 17 species of EAGs (i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus hordeaceus spp. hordeaceus, Bromus japonicus, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus tectorum L., Bromus texensis (Shear) Hitchc.,...
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
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The dataset provides a near real time estimation of 2020 herbaceous mostly annual fractional cover predicted on July 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P96PVZIF., Boyte et al. 2018 https://doi.org/10.5066/P9RIV03D.), but starting this year we are mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation,...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
In support of mapping ecological conditions (e.g. invasive annual grass) in sagebrush-dominated landscapes of the western United States, we developed weekly (starting from week 7 to week 42 and Week 1 starts January 1 or Day of the year 1 to 7, week 2 is from Day of year 8 to 14, and so on) 30-m cloud-free Normalized Difference Vegetation Index (NDVI) from 2016 to 2019. The data was generated with machine-learning techniques (i.e., regression tree [RT]) and harmonized Landsat and Sentinel -2 (HLS) data. The geographic coverage includes areas in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. This NDVI collection allows for local-scale detection and analysis such as, fuel breaks...
Geophysical measurements and related field data were collected by the U.S. Geological Survey (USGS) at the Alaska Peatland Experiment (APEX) site in Interior Alaska from 2018 to 2020 to characterize subsurface thermal and hydrologic conditions along a permafrost thaw gradient. The APEX site is managed by the Bonanza Creek LTER (Long Term Ecological Research). In July 2018, soil temperature and moisture sensors were installed at six out of the nine instrument locations (APEX1, APEX2, APEX3, APEX4, APEX7, APEX9). Thermistors (PS103J2, US Sensor, Orange, CA, USA) were placed at depths of 5, 30, 60, 120, and 180 centimeters (cm) with three replicates. Three sites (APEX1, APEX4, APEX9) contained an additional single...
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This dataset release provides historical (2016 - 2022) estimates of fractional cover for exotic annual grass (EAG) species and a native perennial bunch grass in the arid and semi-arid rangelands of the western United States. The dataset includes four fractional cover maps per year, accompanied by corresponding confidence maps, for a group of 16 species of EAGs, cheatgrass (Bromus tectorum); medusahead (Taeniatherum caput-medusae); and Sandberg bluegrass (Poa secunda). The data were generated using a combination of field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) plots; remotely sensed data from the Harmonized Landsat and Sentinel-2 (HLS) product (specifically Normalized...
Borehole nuclear magnetic resonance (NMR) data were collected by the U.S. Geological Survey (USGS) at Big Trail Lake, a thermokarst lake outside of Fairbanks, Alaska, to quantify unfrozen water content and soil properties at select sites in and around the lake edge. In September 2019, NMR data were collected within two 2.3 m deep boreholes adjacent to the East and North perpendicular electrical resistivity survey lines. Manual permafrost-probe measurements of thaw depths were also collected. These two boreholes were logged a second time in late March 2020. Additional one-time NMR measurements of liquid water content were collected in September 2019 within the lakebed sediments (0-25 cm depth) in approximately 2.5...
High-latitude regions are experiencing rapid and extensive changes in ecosystem composition and function as the result of increases in average air temperature. Increasing air temperatures have led to widespread thawing and degradation of permafrost, which in turn has affected ecosystems, socioeconomics, and the carbon cycle of high latitudes. Here we overcome complex interactions among surface and subsurface conditions to map near-surface permafrost through decision and regression tree approaches that statistically and spatially extend field observations using remotely sensed imagery, climatic data, and thematic maps of a wide range of surface and subsurface biophysical characteristics. The data fusion approach...
In support of mapping ecological conditions (e.g. invasive annual grass) in sagebrush-dominated landscapes of the western United States, we developed weekly (starting from week 7 to week 42 and Week 1 starts January 1 or Day of the year 1 to 7, week 2 is from Day of year 8 to 14, and so on) 30-m cloud-free Normalized Difference Vegetation Index (NDVI) from 2016 to 2019. The data was generated with machine-learning techniques (i.e., regression tree [RT]) and harmonized Landsat and Sentinel -2 (HLS) data. The geographic coverage includes areas in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. This NDVI collection allows for local-scale detection and analysis such as, fuel breaks...
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High-latitude regions are experiencing rapid and extensive changes in ecosystem composition and function as the result of increases in average air temperature. Increasing air temperatures have led to widespread thawing and degradation of permafrost, which in turn has affected ecosystems, socioeconomics, and the carbon cycle of high latitudes. Research shows that the distribution of permafrost is heterogeneous in nature and that permafrost responds to a wide range of ecological factors. Here we overcome complex interactions between surface and subsurface conditions to map near-surface permafrost using decision-tree models, field observations, remotely sensed and derived data, and climatic indices. The resultant dataset...


map background search result map search result map Probabilistic estimates of the distribution of near-surface permafrost in Alaska Alaska permafrost characterization Fractional estimates of exotic annual grass cover in dryland ecosystems of western United States (2016 – 2019) Weekly cloud free Harmonized Landsat Sentinel (HLS) Normalized Difference Vegetation Index (NDVI) estimates for western United States (2016 – 2019) Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Alaska permafrost characterization: Borehole Nuclear Magnetic Resonance Data & Models from 2019-2020 Alaska permafrost characterization: Electrical Resistivity Tomography Data & Models from 2019 APEX Soil Temperature and Moisture Data from 2018-2020 Modelled long-term wildfire occurrence probabilities in sagebrush-dominated ecosystems in the western US (1985 to 2019) Historic and future trends in exotic annual grass (%) cover in the western US (1985 to 2019 and 2025 to 2040) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022) Fractional Estimates of Multiple Exotic Annual Grass (EAG) Species and Sandberg bluegrass in the Sagebrush Biome, USA, 2016 - 2022 (ver. 3.0, July 2023) 3. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 4.0, June 3rd, 2022) 5. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 6.0, July 1st, 2022) Alaska permafrost characterization: Borehole Nuclear Magnetic Resonance (NMR) data collected in 2021 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 1.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 2.0, May 2023) Alaska permafrost characterization: Borehole Nuclear Magnetic Resonance Data & Models from 2019-2020 APEX Soil Temperature and Moisture Data from 2018-2020 Alaska permafrost characterization: Borehole Nuclear Magnetic Resonance (NMR) data collected in 2021 Alaska permafrost characterization: Electrical Resistivity Tomography Data & Models from 2019 Historic and future trends in exotic annual grass (%) cover in the western US (1985 to 2019 and 2025 to 2040) Modelled long-term wildfire occurrence probabilities in sagebrush-dominated ecosystems in the western US (1985 to 2019) Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Fractional estimates of exotic annual grass cover in dryland ecosystems of western United States (2016 – 2019) Weekly cloud free Harmonized Landsat Sentinel (HLS) Normalized Difference Vegetation Index (NDVI) estimates for western United States (2016 – 2019) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022) Fractional Estimates of Multiple Exotic Annual Grass (EAG) Species and Sandberg bluegrass in the Sagebrush Biome, USA, 2016 - 2022 (ver. 3.0, July 2023) 3. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 4.0, June 3rd, 2022) 5. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 6.0, July 1st, 2022) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 1.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 2.0, May 2023) Alaska permafrost characterization Probabilistic estimates of the distribution of near-surface permafrost in Alaska