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  • 1
    Publication Date: 2019-07-18
    Description: To explicate the sources of uncertainty in the prediction of biophysical variables over space, consider the general equation: where z is a variable with values on some nominal, ordinal, interval or ratio scale; y is a vector of input variables; u is the spatial support of y and z ; x and u are the spatial locations of y and z , respectively; f is a model and B is the vector of the parameters of this model. Any y or z has a value and a spatial extent which is called its support. Viewed in this way, categories of uncertainty are from variable (e.g. measurement), parameter, positional. support and model (e.g. structural) sources. The prediction of Leaf Area Index (LAI) and the fraction of absorbed photosynthetically active radiation (fPAR) are examples of z variables predicted using model(s) as a function of y variables and spatially constant parameters. The MOD15 algorithm is an example of f, called f(sub 1), with parameters including those defined by one of six biome types and solar and view angles. The Leaf Canopy Model (LCM)2, a nested model that combines leaf radiative transfer with a full canopy reflectance model through the phase function, is a simpler though similar radiative transfer approach to f(sub 1). In a previous study, MOD15 and LCM2 gave similar results for the broadleaf forest biome. Differences between these two models can be used to consider the structural uncertainty in prediction results. In an effort to quantify each of the five sources of uncertainty and rank their relative importance for the LAI/fPAR prediction problem, we used recent data for an EOS Core Validation Site in the broadleaf biome with coincident surface reflectance, vegetation index, fPAR and LAI products from the Moderate Resolution Imaging Spectrometer (MODIS). Uncertainty due to support on the input reflectance variable was characterized using Landsat ETM+ data. Input uncertainties were propagated through the LCM2 model and compared with published uncertainties from the MOD15 algorithm.
    Keywords: Earth Resources and Remote Sensing
    Type: American Geophysical Union Fall Meeting; Dec 06, 2002 - Dec 10, 2002; San Francisco, CA; United States
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  • 2
    Publication Date: 2019-07-13
    Description: The NSIDC at the University of Colorado has successfully completed the tasks outlined in its proposal 0999.08.1216B, the 'Global Land Ice Measurements from Space' grant funded by NASA under NAG5-9722. The Global Land Ice Measurements from Space (GLIMS) grant reported on here is one of the first completed elements of the overall GLIMS project that continues with separate funding from NASA, the United States Geological Survey (USGS), and internationally by many national agencies and universities. The primary goals of GLIMS are to survey significant numbers of the world's 160,000 glaciers with data collected by the ASTER (Advanced Spaceborne Thermal Emission and reflection Radiometer) instrument aboard the EOS Terra spacecraft, and Landsat ETM+ (Enhanced Thematic Mapper Plus) and to make these data available to users in a common and easily usable format. GLIMS participants include: NSIDC as developer of the GLIMS database, USGS Flagstaff as the GLIMS Coordination Center, USGS EROS Data Center (EDC) as the archive for satellite imagery used in GLIMS analyses (NASA funding for GLIMS also includes the Flagstaff group and EDC through the related ASTER Science Team and Land Processes Distributed Active Archive Center [LP DAAC] activities), and approximately twenty two Regional Centers (RCs). RCs are funded by the national agencies of participating countries to analyze satellite imagery for a specified set of glaciological parameters and provide the results to NSIDC for archive and distribution to the public.
    Keywords: Earth Resources and Remote Sensing
    Format: application/pdf
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  • 3
    Publication Date: 2019-07-10
    Description: Canadian AES personnel collected and processed data related to surface atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from one READAC meteorology station in Hudson Bay, Saskatchewan. Parameters include day, time, type of report, sky condition, visibility, mean sea level pressure, temperature, dewpoint, wind, altimeter, opacity, minimum and maximum visibility, station pressure, minimum and maximum air temperature, a wind group, precipitation, and precipitation in the last hour. The data were collected non-continuously from 24-May-1994 to 20-Sep-1994. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.
    Keywords: Earth Resources and Remote Sensing
    Type: NASA/TM-2000-209891/VOL119 , Rept-2000-03136-0/VOL119 , NAS 1.15:209891/VOL119
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  • 4
    Publication Date: 2019-07-10
    Description: Canadian AES personnel collected several data sets related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from six MARSII meteorology stations in the BOREAS region in Canada. Parameters include site, time, temperature, dewpoint, visibility, wind speed, wind gust, wind direction, two cloud groups, precipitation, and station pressure. Temporally, the data cover the period of May to September 1994. Geo-graphically, the stations are spread across the provinces of Saskatchewan and Manitoba. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.
    Keywords: Earth Resources and Remote Sensing
    Type: NASA/TM-2000-209891/VOL118 , Rept-2000-03136-0/VOL118 , NAS 1.15:209891/VOL118
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  • 5
    Publication Date: 2019-07-10
    Description: The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-4 work was focused on collecting data during the winter focused field campaign (FFC-W) to improve the understanding of winter processes within the boreal forest. Knowledge of snow cover and its variability in the boreal forest is fundamental if BOREAS is to achieve its goals of understanding the processes and states involved in the exchange of energy and water. The development and validation of remote sensing algorithms will provide the means to extend the knowledge of these processes and states from the local to the regional scale. A specific thrust of the research is the development and validation of snow cover algorithms from airborne passive microwave measurements. Snow surveys were conducted at special snow courses throughout the 1993/94, 1994/95, 1995/96, and 1996/97 winter seasons. These snow courses were located in different boreal forest land cover types (i.e., old aspen, old black spruce, young jack pine, forest clearing, etc.) to document snow cover variations throughout the season as a function of different land cover. Measurements of snow depth, density, and water equivalent were acquired on or near the first and fifteenth of each month during the snow cover season. The data are provided in tabular ASCII files. The HYD-4 standard snow course data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
    Keywords: Earth Resources and Remote Sensing
    Type: NASA/TM-2000-209891/VOL27 , Rept-2000-03136-0/VOL27 , NAS 1.15:209891/VOL27
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  • 6
    Publication Date: 2019-07-10
    Description: The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-4 team focused on collecting data during the 1994 winter focused field campaign (FFCW) to improve the understanding of winter processes within the boreal forest. Knowledge of snow cover and its variability in the boreal forest is fundamental if BOREAS is to achieve its goals of understanding the processes and states involved in the exchange of energy and water. The development and validation of remote sensing algorithms will provide the means to extend the knowledge of these processes and states from the local to the regional scale. A specific thrust of the hydrology research is the development and validation of snow cover algorithms from airborne passive microwave measurements. Airborne remote sensing data (gamma, passive microwave) were acquired along a series of flight lines established in the vicinity of the BOREAS study areas. Ground snow surveys were conducted along selected sections of these aircraft flight lines. These calibration segments were typically 10-20 km in length, and ground data were collected at one to two kilometer intervals. The data are provided in tabular ASCII files. The HYD-04 areal snow course data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
    Keywords: Earth Resources and Remote Sensing
    Type: NASA/TM-2000-209891/VOL26 , Rept-2000-03136-0/VOL26 , NAS 1.15:209891/VOL26
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  • 7
    Publication Date: 2019-07-10
    Description: The Saskatchewan Forest Fire Control Centre (SFFCC) provided surface meteorological data to BOREAS from its archive. This data set contains hourly surface meteorological data from 18 of the Meteorological stations located across Saskatchewan. Included in these data are parameters of date, time, temperature, relative humidity, wind direction, wind speed, and precipitation. Temporally, the data cover the period of May through September of 1994 and 1995. The data are provided in comma-delimited ASCII files, and are classified as AFM-Staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
    Keywords: Earth Resources and Remote Sensing
    Type: NASA/TM-2000-209891/VOL123 , NAS 1.15:209891/VOL123 , Rept-2000-03136-0
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