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Regional distribution of forest height and biomass from multisensor data fusionAuthor(s): Yifan Yu; Sassan Saatch; Linda S. Heath; Elizabeth LaPoint; Ranga Myneni; Yuri Knyazikhin
Source: Regional distribution of forest height and biomass from multisensor data fusion. Journal of Geophysical Research. 115: G00E12. doi: 10.1029/2009/JG000995. 16 p.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionElevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM‐NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass.
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CitationYu, Yifan; Saatch, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri. 2010. Regional distribution of forest height and biomass from multisensor data fusion. Journal of Geophysical Research. 115: G00E12, doi:10.1029/2009/JG000995. 16 p.
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