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      High Spectral Resolution Remote Sensing of Forest Canopy Lingnin, Nitrogen and Ecosystem Processes
      Remote sensing of foliar chemistry has been recognized as an important element in producing large-scale, spatially explicit estimates of forest ecosystem function. This study was designed to determine whether data from NASA’s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) could be used to determine forest canopy chemistry at a spatial resolution of 20 m, and if so, to use that information to drive an ecosystem productivity model.

      Mary E. Martin, John D. Aber (1997)

      Complex Systems Research Center, Morse Hall, University of New Hampshire, Durham, New Hampshire 03824 USA

      Received: October 23, 1995; Accepted: January 20, 1996; Final version received: April 26, 1996
      Ecological Applications: Vol. 7, No. 2, pp. 431-443

       

      Abstract

      Remote sensing of foliar chemistry has been recognized as an important element in producing large-scale, spatially explicit estimates of forest ecosystem function. This study was designed to determine whether data from NASA’s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) could be used to determine forest canopy chemistry at a spatial resolution of 20 m, and if so, to use that information to drive an ecosystem productivity model. Foliage and leaf litter were sampled on 40 plots at Blackhawk Island, Wisconsin, and Harvard Forest, Massachusetts, to determine canopy-level nitrogen and lignin concentrations. At the time of the field sampling, AVIRIS data were acquired for both study areas. Calibration equations were developed, relating nitrogen and lignin to selected first-difference spectral bands (R2 = 0.87 and 0.77, respectively). Calibration equations were evaluated on the basis of inter- and intrasite statistics. These equations were applied to all image pixels to make spatially explicit estimates of canopy nitrogen and lignin for both study sites. These estimates of nitrogen and lignin concentrations were then used with existing models to predict net ecosystem productivity at Harvard Forest and nitrogen mineralization rates at Blackhawk Island.

      High spectral resolution remote sensing of forest canopy lignin, nitroget, and ecoysystem processes (full article)

      full article
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