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A subset of fires sampled from the GNLCC Large Fire Database within both the United States and Canada. Each sub-folder is named for the numeric identifier of the fire in the GNLCC Large Fire Database, and the name of the fire if the fire has a name. Within the folder for the fire, is a zip folder named with the numeric identifier of the fire. Each zip folder contains 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of the Tiff is Band 7 (SWIR) of Landsat 2....
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the folder there are 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of...
To assess the North American high-latitude vegetation response to the rising temperature, we derived NDVI trend for 91.2% of the non-water, non-snow land area of Canada and Alaska using the peak-summer Landsat surface reflectance data of 1984–2012. Our analysis indicated that 29.4% and 2.9% of the land area of Canada and Alaska showed statistically significant positive (greening) and negative (browning) trends respectively, at significance level p < 0.01, after burned forest areas were masked out. The area with greening trend dominated over that with browning trend for all land cover types. The greening occurred primarily in the tundra of western Alaska, along the north coast of Canada and in northeastern Canada;...
In this study we present a technique to discriminate between climate or human-induced dryland degradation, based on evaluations of AVHRR NDVI data and rainfall data. Since dryland areas typically have high inter-annual rainfall variations and rainfall has a dominant role in determining vegetation growth, minor biomass trends imposed by human influences are difficult to verify. By performing many linear regression calculations between different periods of accumulated precipitation and the annual NDVImax, we identify the rainfall period that is best related to the NDVImax and by this the proportion of biomass triggered by rainfall. Positive or negative deviations in biomass from this relationship, expressed in the...
Categories: Publication;
Types: Citation,
Journal Citation;
Tags: AVHRR,
Climate,
Degradation,
Desertification,
Dryland,
Management and disturbances have significant effects on grassland forage production. When using satellite remote sensing to monitor climate impacts such as drought stress on annual forage production, minimizing these effects provides a clearer climate signal in the productivity data. The use of an ecosystem performance approach for assessment of seasonal and interannual climate impacts on forage production in semi-arid grasslands proved to be a successful method in a case study covering the Nebraska Sandhills. In this study we developed a time series (2000-2018) of the Expected Ecosystem Performance (EEP), which serves as a proxy for annual forage production after accounting for non-climatic influences, while minimizing...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Land Use Change,
NDVI,
USGS Science Data Catalog (SDC),
United States,
biomass,
Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors...
Categories: Data,
Publication;
Types: Citation;
Tags: Complementary relationship,
Completed,
Cross-sensor,
EARTH SCIENCE > LAND SURFACE > LANDSCAPE,
Evaporative demand,
The polygons in this shapefile accompany the paper, “Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions,” by Sadinski et al. (submitted). The paper describes relations between climate dynamics and key ecological conditions and processes on wetland-upland landscapes in > 30 sites distributed across four study areas in the midwestern United States. The variables studied included both ground- and satellite-based measures. The polygons in this shapefile pertain to the latter and provide the boundaries of 4-km2 blocks that subsume the field sites and provide a landscape perspective for the...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Evapotranspiration,
Integrated monitoring,
Landscape,
MODIS,
Midwest Region,
Global wind energy has expanded 5-fold since 2010 and is predicted to expand another 8–10-fold over the next 30 years. Wakes generated by wind turbines can alter downwind microclimates and potentially downwind vegetation. However, the design of past studies has made it difficult to isolate the impact of wake effects on vegetation from land cover change. We used hourly wind data to model wake and non-wake zones around 17 wind facilities across the U.S. and compared remotely-sensed vegetation greenness in wake and non-wake zones before and after construction. We located sampling sites only in the dominant vegetation type and in areas that were not disturbed before or after construction. We found evidence for wake...
Categories: Data;
Tags: Ecology,
Energy Resources,
Land Use Change,
NDVI,
USGS Science Data Catalog (SDC),
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,
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the folder there are 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of...
Landslide-generated tsunamis pose significant hazards, but developing models to assess these hazards presents unique challenges. George and others (2017) present a new methodology in which a depth-averaged two-phase landslide model (D-Claw) is used to simulate all stages of landslide dynamics and subsequent tsunami generation, propagation, and inundation. Because the model describes the evolution of solid and fluid volume fractions, it treats both landslides and tsunamis as special cases of a more general class of phenomena. Therefore, the landslide and tsunami can be seamlessly and efficiently simulated as a single-layer continuum with evolving solid-grain concentrations, and with wave generation via mass displacement...
This dataset provides a near-real-time estimate of 2017 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through June 19, 2017. This is the second iteration of an early estimate of herbaceous annual cover for 2017 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/F7445JZ9). The pixel values for this most recent estimate ranged from 0 to100% with...
These operational land imager (OLI) value added data sets, maps, and associated ancillary data were compiled as part of an ongoing research aimed at quantifying the riparian vegetation greenness and water use in the lower Colorado River Delta in Mexico. In order to create trend and anomaly maps that characterize these ecosystems Vegetation Index (NDVI) time series imagery from Landsat OLI were acquired and processed over time and space along seven predefined reaches that capture different natural states and management conditions. We used Landsat OLI 30m data as an improvement upon past studies that were based on coarser remote sensing data from the NASA MODIS sensor (250 m). The OLI 30m images provide better characterization...
These data were compiled for evaluating river-reach level plant water use, or evapotranspiration (ET), and vegetation greenness, or Normalized Difference Vegetation Index (NDVI), in the riparian corridor of the Colorado River delta as specified under Minute 319 of the 1944 Water Treaty. The seven reach areas from the Northerly International Boundary (NIB) to the end of the delta at the Sea of Cortez were defined for research activities. Also, these seven reaches are being monitored under Minute 323 of the 1944 Water Treaty. Additionally, these data were compiled for evaluating restoration-level evapotranspiration and vegetation greenness data in Reach 2 and Reach 4, as specified under Minute 323 of the 1944 Water...
The dataset provides an estimate of 2017 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The pixel values range from 0 to100 with an overall mean value of 7.1 and a standard deviation of +/-10.5. The model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. This dataset was generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied...
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,
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 Release - Revised;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Improving the quality of habitat for western big-game species, such as elk and mule deer, was identified as a priority by the Department of the Interior in 2018. Maintaining healthy herds not only supports the ecosystems where these species are found, but also the hunting and wildlife watching communities. For example, in Wyoming, big game hunting contributed over $300 million to the state’s economy in 2015. Yet as climate conditions change, the quantity, quality, and timing of vegetation available to mule deer, elk, and other ungulates, known as forage, could shift. It’s possible that these changes could have cascading impacts on the behavior and population sizes of many species. A key strategy used by managers...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2018,
CASC,
Completed,
EVI,
IRG,
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the folder there are 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of...
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