Filters: Contacts: Neal J Pastick (X)
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This release contains Active Layer Thickness (ALT) and Organic Layer Thickness (OLT) measurements measured along transects in Alaska, 2015. Site condition information in terms of wildfire burns is also included.
Categories: Data;
Types: Citation;
Tags: Active layer,
Active layer thickness,
Alaska,
Borehole nuclear magnetic resonance,
Chatanika,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Alaska permafrost characterization: Borehole Nuclear Magnetic Resonance (NMR) data collected in 2021
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.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Active layer thickness,
Alaska,
Bonanza Creek,
Borehole nuclear magnetic resonance,
Disturbance,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Ecology,
Exotic annual grasses, cheatgrass, remote sensing,
Exotic annual grasses, cheatgrass, remote sensing,
Land Use Change,
Remote Sensing,
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...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Active layer thickness,
Alaska,
Big Trail Lake,
Bonanza Creek Experimental Forest,
Disturbance,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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...
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Idaho,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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.,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Fire can be a significant driver 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 fire-induced change. As fire frequency is expected to increase in the high latitudes, methods to understand the vulnerability and resilience of different landscapes to permafrost degradation are needed. Geophysical and other field observations reveal details of both near-surface (<1 m) and deeper (>1 m) impacts of fire on permafrost along 11 transects that span burned-unburned boundaries in different landscape settings within interior Alaska. Data collected...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Alaska,
City of Fairbanks,
Disturbance,
Fire,
Geophysics,
This release contains plant species cover measured along transects in Alaska, 2015. Site condition information in terms of wildfire burns is also included.
Categories: Data;
Types: Citation;
Tags: Active layer,
Active layer thickness,
Alaska,
Borehole nuclear magnetic resonance,
Chatanika,
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...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Alaska,
Bonanza Creek,
Disturbance,
Fairbanks North Star,
GGGSC,
This dataset release provides historical (2016 - 2023) 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 (five for 2023) 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). Field Brome (Bromus arvensis) is added as individual map species in 2023. The data were generated using a combination of field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) plots; remotely...
Categories: Data,
Data Release - Revised;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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...
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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