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  • ABoVE: Alder Shrub Cover and Soil Properties, Alaska, 2019, V2

    https://cmr.earthdata.nasa.gov/search/concepts/C2840822238-ORNL_CLOUD.xml
    Description:

    This dataset holds measures of vegetative cover and soil characteristics for sites in interior Alaska, U.S., along the James W. Dalton Highway (Alaska Route 11). The field data were collected during August in 2018 and 2019 to study the expansion of shrub cover, particularly alders (Alnus spp.) in tundra ecosystems and the potential impact of shrubs on soil properties. Samples were measured along transects at 5- to 10-m intervals. Soil samples were collected and analyzed in the laboratory. Vegetation variables include percent cover of mosses, lichens, graminoid species, shrubs, alder, birch (Betula spp.), and willow (Salix spp.) along with the biomass, size, and age structure of alder. An allometric model to estimate alder biomass was developed. Soil metrics include moisture content, conductivity, bulk density, carbon and nitrogen content and isotope ratios. The data include the maximum annual Normalized Difference Vegetation Index (NDVI) for 2019 and the trend in maximum NDVI for 2000-2020. This is version 2 of this dataset.The data are provided in comma-separated values (CSV) format.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 66.34 -150.71 68.02 -149.71

    ORNL_CLOUD Short Name: Alder_Shrub_Soil_Alaska_V2_2300 Version ID: 2 Unique ID: C2840822238-ORNL_CLOUD

  • ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C2143402644-ORNL_CLOUD.xml
    Description:

    This dataset provides maps at 30-m resolution of landscape surface burn severity (surface litter and soil organic layers) from the 2014-2015 fires in the Northwest Territories and Northern Alberta, Canada. The maps were derived from Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) imagery and two separate multiple linear regression models trained with field data; one for the Plains and a second for the Shield ecoregion. Field observations were used to estimate area burned in each of five severity classes (unburned, singed, light, moderate, severely burned) in six stratified randomly selected plots of 10 x 10-m in size across a 1-ha site. Using this five class scale a burn severity index (BSI) for each 1-ha site was calculated using multiple weighted and averaged field parameters. Pre- and post-fire phenologically paired Landsat 8 images were used to model the five discrete severity classes using midpoints as breaks.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 58.29 -124.03 65.55 -108.83

    ORNL_CLOUD Short Name: NWT_Burn_Severity_Maps_1694 Version ID: 1 Unique ID: C2143402644-ORNL_CLOUD

  • ABoVE: Distribution Maps of Wildland Fire Fuel Components across Alaskan Tundra, 2015

    https://cmr.earthdata.nasa.gov/search/concepts/C2143402675-ORNL_CLOUD.xml
    Description:

    This dataset provides maps of the distribution of three major wildland fire fuel types at 30 m spatial resolution covering the Alaskan arctic tundra, circa 2015. The three fuel components include woody (evergreen and deciduous shrubs), herbaceous (sedges and grasses), and nonvascular species (mosses and lichens). Multi-seasonal and multispectral mosaics were first developed at 30 m resolution using Landsat 8 surface reflectance data collected from 2013 to 2017. The spectral information from Landsat mosaics was combined with field observations from representative tundra vegetation plots collected during multiple field trips to model the fractional cover of fuel type components. An improved vegetation mask for shrub and graminoid-dominated tundra was developed using random forest classification and is also included. The final fractional cover maps were developed using the trained model with the multi-seasonal and multi-spectral Landsat mosaics across the entire Alaskan tundra.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 57.39 -170.01 72.52 -132.49

    ORNL_CLOUD Short Name: Frac_FuelComponent_Maps_Tundra_1761 Version ID: 1 Unique ID: C2143402675-ORNL_CLOUD

  • ABoVE: Lake Growing Season Green Surface Reflectance Trends, AK and Canada, 1984-2019

    https://cmr.earthdata.nasa.gov/search/concepts/C2143401725-ORNL_CLOUD.xml
    Description:

    This dataset provides an annual time series of Landsat green surface reflectance and the derived annual trend during the growing season (June and July) for 472,890 lakes across the ABoVE Extended Study Domain from 1984 to 2019. The reflectance data are from Landsat-5, Landsat-7, and Landsat-8 sensors for the green band (center wavelength 560 nm). Over 270,000 Landsat scenes were evaluated and quality assured to be cloud-free and over water. Lakes were selected from HydroLAKES, a global database of lakes of at least 10 ha. Lake surface reflectance was extracted from a 3-by-3-pixel area centered on each lake centroid from the selected Landsat scenes determined from lake polygons. This dataset demonstrates changes in lake color over time in the arctic and boreal regions of North America. Color is relevant for understanding physical, ecological, and biogeochemical processes in some of the world’s highest concentrations of lakes where climate change may have significant impacts.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 49.54 -168.1 75 -81.23

    ORNL_CLOUD Short Name: ABoVE_GrowingSeason_Lake_Color_1866 Version ID: 1 Unique ID: C2143401725-ORNL_CLOUD

  • ABoVE: Landsat Tundra Greenness and Summer Air Temperatures, Arctic Tundra, 1985-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C2143401680-ORNL_CLOUD.xml
    Description:

    This dataset provides annual tundra greenness and summer air temperatures at a resolution of 50 km over the pan-Arctic tundra biome above 31.5 degrees over the time period 1985 to 2016. Annual tundra greenness was assessed using the maximum Normalized Difference Vegetation Index (NDVImax) derived from surface reflectance measured by sensors on the Landsat satellites. Summer air temperatures were quantified using the Summer Warmth Index (SWI) derived from an ensemble of five global temperature datasets. Tabular data include NDVImax, SWI, and estimates of uncertainty using Monte Carlo simulations at 45,334 vegetated sampling sites. Raster data provide (1) annual SWI from 1985 to 2016; (2) temporal trends in annual NDVImax and SWI from 1985 to 2016 and from 2000 to 2016; and (3) temporal correlations between annual NDVImax - SWI during these two periods. Each raster also includes estimates of uncertainty that were generated using Monte Carlo simulations. This dataset provides a new pan-Arctic product for assessing inter-annual variability in tundra using moderate resolution observations from the Landsat satellites.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 31.49 -180 90 180

    ORNL_CLOUD Short Name: Tundra_Greeness_Temp_Trends_1893 Version ID: 1 Unique ID: C2143401680-ORNL_CLOUD

  • ABoVE: Landsat Vegetation Greenness Trends, Boreal Forest Biome, 1985-2019

    https://cmr.earthdata.nasa.gov/search/concepts/C2262495772-ORNL_CLOUD.xml
    Description:

    This dataset provides information on interannual trends in annual maximum vegetation greenness from 1985 to 2019 for recently undisturbed areas in the boreal forest biome. Multi-decadal changes in remotely sensed vegetation greenness provide evidence of an emerging boreal biome shift driven by climate warming. Annual maximum vegetation greenness was assessed at about 100,000 random sample locations using an ensemble of spectral vegetation indices (NDVI, EVI2, kNDVI, and NIRv) derived from Landsat products. The dataset provides raster data summarizing vegetation greenness trends for sample locations stratified by Ecological Land Unit in GeoTIFF format. These raster data span the circum-hemispheric boreal forest biome between 45 to 70 degrees north at 300 m resolution. Estimates of uncertainty were generated using Monte Carlo simulations. Interannual trends in annual maximum vegetation greenness from 1985 to 2019 and 2000 to 2019 are provided for sample locations with adequate data for time series analysis; these data are in comma-separated values (CSV) format.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 45 -180 72 180

    ORNL_CLOUD Short Name: BorealForest_Greenness_Trends_2023 Version ID: 1 Unique ID: C2262495772-ORNL_CLOUD

  • ABoVE: Landsat-derived Burn Scar dNBR across Alaska and Canada, 1985-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C2111787144-ORNL_CLOUD.xml
    Description:

    This dataset contains differenced Normalized Burned Ratio (dNBR) at 30-m resolution calculated for burn scars from fires that occurred within the Arctic Boreal and Vulnerability Experiment (ABoVE) Project domain in Alaska and Canada during 1985-2015. The fire perimeters were obtained from the Alaskan Interagency Coordination Center (AICC) and the Natural Resources Canada (NRC) fire occurrence datasets. Only burns with an area larger than 200-ha were included. The dNBR for each burn scar at 30-m pixel resolution was derived from pre- and post-burn Landsat 5, 7, and 8 scenes within a 5-km buffered area surrounding each burn scar using Landsat LEDAPS surface reflection image pairs.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 50.25 -168.42 71.36 -101.74

    ORNL_CLOUD Short Name: ABoVE_Fire_Severity_dNBR_1564 Version ID: 1 Unique ID: C2111787144-ORNL_CLOUD

  • ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C2143403517-ORNL_CLOUD.xml
    Description:

    This dataset provides estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 62.9 -160.07 66.36 -142.99

    ORNL_CLOUD Short Name: River_Ice_Breakup_Freezeup_1697 Version ID: 1 Unique ID: C2143403517-ORNL_CLOUD

  • ABoVE: Riverbank Erosion and Vegetation Changes, Yukon River Basin, Alaska, 1984-2017

    https://cmr.earthdata.nasa.gov/search/concepts/C2162145546-ORNL_CLOUD.xml
    Description:

    This dataset provides a time series of riverbank erosion and vegetation colonization along reaches of the Yukon River (3 study areas), Tanana and Nenana Rivers (1 area), and Chandalar River (1 area) in interior Alaska over the period 1984-2017. The change data were derived from selected 30-m images from Landsat TM, Landsat ETM+, and Landsat Operational Land Imager (OLI) surface reflectance products. Image classification used the Normalized Differenced Vegetation Index (NDVI) with an NDVI threshold of 0.2 to differentiate vegetated from non-vegetated pixels. Images were assigned to one of seven or eight multiyear intervals, within the 1984-2017 overall range, for each study area. Time intervals vary by study site. Change detection identified shifts from one time interval to the next: changes from vegetated to non-vegetated classes were considered riverbank erosion and changes from non-vegetated to vegetated classes were considered vegetation colonization.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 61.91 -161.46 68.15 -143.3

    ORNL_CLOUD Short Name: Erosion_Vegetation_Yukon_1616 Version ID: 1 Unique ID: C2162145546-ORNL_CLOUD

  • ABoVE: Tree Canopy Cover and Stand Age from Landsat, Boreal Forest Biome, 1984-2020

    https://cmr.earthdata.nasa.gov/search/concepts/C2539841646-ORNL_CLOUD.xml
    Description:

    This dataset contains Landsat-derived locally-calibrated estimates of tree canopy cover (TCC) and forest stand age across global boreal forests from 1984-2020 in Cloud-Optimized GeoTIFF (*.tif) format. These raster data span the circum-hemispheric boreal forest biome between 47 to 73 degrees north at 30 m resolution. Machine learning models calibrated with data from the World Reference System 2 were used to predict TCC from Landsat data at 30-m spatial resolution at annual temporal resolution. Through analysis of TCC time series, forest change estimates of stand age from 1984-2020 were developed. The broad spatial and temporal coverage of these data provide insight into forest and carbon dynamics of the global boreal forest system. Boreal forests store a large proportion of global soil and biomass carbon and have experienced disproportionately high levels of warming over the past century.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 45 -180 73 180

    ORNL_CLOUD Short Name: Boreal_CanopyCover_StandAge_2012 Version ID: 1 Unique ID: C2539841646-ORNL_CLOUD