DocumentCode :
762344
Title :
Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and a spaceborne (Hyperion) sensor
Author :
Smith, Marie-Louise ; Martin, Mary E. ; Plourde, Lucie ; Ollinger, Scott V.
Author_Institution :
Northeastern Res. Station, U.S. Dept. of Agric. Forest Service, Durham, NH, USA
Volume :
41
Issue :
6
fYear :
2003
fDate :
6/1/2003 12:00:00 AM
Firstpage :
1332
Lastpage :
1337
Abstract :
Field studies among diverse biomes demonstrate that mass-based nitrogen concentration at leaf and canopy scales is strongly related to carbon uptake and cycling. Combined field and airborne imaging spectrometry studies demonstrate the capacity for accurate empirical estimation of forest canopy N concentration and other biochemical constituents at scales from forest stands to small landscapes. In this paper, we report on the utility of the first space-based imaging spectrometer, Hyperion, for estimation of temperate forest canopy N concentration as compared to that achieved with the airborne high-altitude imaging spectrometer, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Overall accuracy of Hyperion estimates of forest canopy N concentration, as compared with field measurements, were within 0.25% dry mass, and AVIRIS-based estimates were within 0.19% dry mass, each well within the accuracy required to distinguish among forested ecosystems in nitrogen status.
Keywords :
forestry; geophysical techniques; vegetation mapping; 400 to 2500 nm; AVIRIS; Abies balsamea; Acer rubrum; Acer saccharum; American beech; Betula alleghaniensis; Betula papyrifera; Fagus grandifolia; Fraxinus americana; Hyperion; IR; N; New Hampshire; Picea rubens; Pinus strobus; Tsuga; USA; United States; airborne method; balsam fir; biochemical constituents; biochemistry; canopy; chemical composition; eastern hemlock; empirical estimation; foliage; forest; forestry; geophysical measurement technique; hyperspectral remote sensing; infrared; leaf; paper birch; red maple; red spruce; satellite remote sensing; sugar maple; temperate forest; vegetation mapping; visible; white ash; white pine; Biosensors; Data analysis; Ecosystems; Hyperspectral imaging; Hyperspectral sensors; Infrared imaging; Infrared spectra; Nitrogen; Optical imaging; Spectroscopy;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2003.813128
Filename :
1220240
Link To Document :
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