OpenSearch

Using the NASA EOSDIS Common Metadata Repository

Collection Search

  • ABoVE: Burn Severity, Fire Progression, and Field Data, NWT, Canada, 2015-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1422976988-ORNL_DAAC.xml
    Description:

    This data set provides a fire progression map for year 2015 and measures of burn severity and vegetation community biophysical data collected from areas that were burned by wildfires in 2014 and 2015 in the Northwest Territories, Canada. Field data collected in 2016 include an estimate of burn severity, woody seedling/sprouting data, soil moisture, peat depth, thaw depth, and vegetation cover for selected sites.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 59.93 -135.54 68.33 -106.76

    ORNL_DAAC Short Name: Wildfires_NWT_Canada_1548 Version ID: 1 Unique ID: C1422976988-ORNL_DAAC

  • ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014

    https://cmr.earthdata.nasa.gov/search/concepts/C1248454748-ORNL_DAAC.xml
    Description:

    This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 60.33 -121.6 64.25 -110.68

    ORNL_DAAC Short Name: Wildfires_2014_NWT_Canada_1307 Version ID: 1 Unique ID: C1248454748-ORNL_DAAC

  • ABoVE: Corrected MODIS MAIAC Reflectance at Tower Sites, Alaska and Canada, 2000-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1627102549-ORNL_DAAC.xml
    Description:

    This dataset provides angular corrections of MODIS Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) surface reflectances by two methods at each of 62 flux tower sites (1 km x 1 km area) across the ABoVE domain in Alaska and western Canada from 2000 to 2015/2016. The original MAIAC reflectance data were corrected to consistent view and illumination angles (0 degree view zenith angle and 45 degree of sun zenith angle) using two independent algorithms: the first based on the original BRDF (Bidirectional Reflectance Distribution Function) parameters provided by the MAIAC team, and the second based on a machine learning approach (random forests). The corrected data preserve the original MAIAC data's sub-daily temporal resolution and 1 km spatial resolution with seven land bands (bands 1-7) and five ocean bands (bands 8-12). The resulting tower site sub-daily timeseries of angular corrected surface reflectances are suitable for long-term studies on patterns, processes, and dynamics of surface phenomena.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 42.64 -157.41 71.32 -74.04

    ORNL_DAAC Short Name: MODIS_MAIAC_Reflectance_1700 Version ID: 1 Unique ID: C1627102549-ORNL_DAAC

  • ABoVE: Environmental Conditions During Fall Moose Hunting Seasons, Alaska, 2000-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1692444819-ORNL_DAAC.xml
    Description:

    This dataset provides daily and annual air temperature, river water level, and leaf drop dates coincident with the moose (Alces alces) hunting season (September) for the area surrounding the rural communities of Nulato, Koyukuk, Kaltag, Galena, Ruby, Huslia, and Hughes in interior Alaska, USA, over the period 2000-2016. The main objective of the study was to assess how the environmental conditions impacted the success of hunters who rely on moose as a subsistence resource.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 64.55 -158.53 64.93 -156.66

    ORNL_DAAC Short Name: Effect_Environment_Moose_1739 Version ID: 1 Unique ID: C1692444819-ORNL_DAAC

  • ABoVE: Fractional Open Water Cover for Pan-Arctic and ABoVE-Domain Regions, 2002-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C1358859924-ORNL_DAAC.xml
    Description:

    This data set provides land surface fractional open water cover maps for two overlapping regions: the entire pan-Arctic region (latitude > 45 degrees) and the Arctic-Boreal Vulnerability Experiment (ABoVE) domain across Alaska and Canada. The data are a 10-day averaged time step at 5-km spatial resolution for the period 2002-2015. Data represent the aerial portion of a grid cell covered by open water. The data were produced using high frequency (89 GHz) brightness temperatures from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2), with other ancillary inputs from AMSR-E/AMSR2 25-km products and the Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting data record for fractional water is suitable for documenting open water patterns and inundation dynamics in boreal-Arctic ecosystems experiencing rapid climate change.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 39.38 -180 90 180

    ORNL_DAAC Short Name: ABoVE_Frac_Open_Water_1362 Version ID: 1 Unique ID: C1358859924-ORNL_DAAC

  • ABoVE: High Resolution Cloud-Free Snow Cover Extent and Snow Depth, Alaska, 2001-2017

    https://cmr.earthdata.nasa.gov/search/concepts/C1887537599-ORNL_DAAC.xml
    Description:

    This dataset provides estimates of maximum snow cover extent (SCE) and snow depth for each 8-day composite period from 2001 to 2017 at 1 km resolution across Alaska. The study area covers the majority land area of Alaska except for areas covered by perennial ice/snow or open water. A downscaling scheme was used in which Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis 0.5 degree snow depth data were interpolated to a finer 1 km spatial grid. In the methods used, the downscaling scheme incorporated MODIS SCE (MOD10A2) to better account for the influence of local topography on the 1km snow distribution patterns. For MODIS cloud-contaminated pixels, persistent and patchy cloud cover conditions were improved by applying an elevation-based spatial filtering algorithm to predict snow occurrence. Cloud-free MODIS SCE data were then used to downscale MERRA-2 snow depth data. For each snow-covered 1 km pixel indicated by the MODIS data, the snow depth was estimated based on the snow depth of the neighboring MERRA-2 0.5 grid cell, with weights predicted using a spatial filter.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 55.57 -179.18 71.42 -132.58

    ORNL_DAAC Short Name: Snow_Cover_Extent_and_Depth_1757 Version ID: 1 Unique ID: C1887537599-ORNL_DAAC

  • ABoVE: Ignitions, burned area and emissions of fires in AK, YT, and NWT, 2001-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C1400101586-ORNL_DAAC.xml
    Description:

    This data set provides estimates of daily burned area, carbon emissions and uncertainty, and daily fire ignition locations for boreal fires in Alaska, USA, and the Yukon and Northwest Territories, Canada. The data are at 500-m resolution for the period 2001 to 2015.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 59.99 -176.93 75.75 -100

    ORNL_DAAC Short Name: Alaskan_Wildfire_C_Emissions_1341 Version ID: 1 Unique ID: C1400101586-ORNL_DAAC

  • ABoVE: MODIS-derived Maximum NDVI, Northern Alaska and Yukon Territory for 2002-2017

    https://cmr.earthdata.nasa.gov/search/concepts/C1566856315-ORNL_DAAC.xml
    Description:

    This dataset provides the maximum Normalized Difference Vegetation Index (NDVI) at 1-km resolution over northern Alaska, USA and the Yukon Territory, Canada for each year from 2002-2017, as well as a 16 year maximum NDVI product. MODIS products MOD13Q1 and MYD13Q1 from Collection 6 were acquired at 250-m pixel size from June 1-August 30 of each year. Within each growing season from 2002-2017, the maximum NDVI was determined for each pixel. These maximum NDVI values were then aggregated to 1-km by selecting the maximum NDVI from the sixteen 250-m pixels values nested within each 1-km pixel. A long-term 16-year maximum NDVI was then derived from the time series of annual maximum NDVI values.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 52.17 -175.76 68.97 -97.93

    ORNL_DAAC Short Name: Alaska_Yukon_NDVI_1614 Version ID: 1 Unique ID: C1566856315-ORNL_DAAC

  • ABoVE: Rain-on-Snow Frequency and Distribution during Cold Seasons, Alaska, 2003-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1579375356-ORNL_DAAC.xml
    Description:

    This dataset provides maps of rain-on-snow (ROS) events across Alaska for the individual months of November to March 2002-2011 and November to March 2012-2016, and annual water year summary maps for 2003-2011 and 2013-2016. ROS events were defined as changes in passive microwave (PM) detection in surface snow wetness and isothermal states induced by atmospheric processes often associated with winter rainfall. The data are summations of the number of days with ROS events per pixel at 6-km spatial resolution per month or per 5-month water year. The daily ROS record encompassed the months when snowmelt from solar irradiance is minimal and snow cover is widespread and relatively consistent throughout the region. Daily ROS geospatial classification across Alaska was derived by combining snow cover and daily microwave brightness temperature retrievals sensitive to landscape freeze-thaw dynamics from overlapping (1) Moderate Resolution Imaging Spectroradiometer (MODIS) MOD10A2 eight-day maximum snow cover extent (SCE) product and (2) Advanced Microwave Scanning Radiometer for EOS (AMSR-E) (2002-2011) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) (2012-to present) Microwave Radiation Imager (MWRI) observations at 19 GHz and 37 GHz.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 48.62 -175.4 73.85 -111.54

    ORNL_DAAC Short Name: Rain-on-Snow_Data_1611 Version ID: 1 Unique ID: C1579375356-ORNL_DAAC

  • Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C2015954203-ORNL_DAAC.xml
    Description:

    This dataset provides gridded estimates of aboveground biomass (AGB) for live dry woody vegetation density in the form of both stock for the baseline year 2003 and annual change in stock from 2003 to 2016. Data are at a spatial resolution of approximately 500 m (463.31 m; 21.47 ha) for three geographies: the biogeographical limit of the Amazon Basin, the country of Mexico, and a Pantropical belt from 40 degrees North to 30 degrees South latitudes. Estimates were derived from a multi-step modeling approach that combined field measurements with co-located LiDAR data from NASA ICESat Geoscience Laser Altimeter System (GLAS) to calibrate a machine-learning (ML) algorithm that generated spatially explicit annual estimates of AGB density. ML inputs included a suite of satellite and ancillary spatial predictor variables compiled as wall-to-wall raster mosaics, including MODIS products, WorldClim climate variables reflecting current (1960-1990) climatic conditions, and SoilGrids soil variables. The 14-year time series was analyzed at the grid cell (~500 m) level with a change point-fitting algorithm to quantify annual losses and gains in AGB. Estimates of AGB and change can be used to derive total losses, gains, and the net change in aboveground carbon density over the study period as well as annual estimates of carbon stock.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -30 -180 40 180

    ORNL_DAAC Short Name: AGB_Pantropics_Amazon_Mexico_1824 Version ID: 1 Unique ID: C2015954203-ORNL_DAAC