Vegetation Species Composition and Canopy Architecture Information Expressed in Leaf Water.pdfVIP

Vegetation Species Composition and Canopy Architecture Information Expressed in Leaf Water.pdf

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Vegetation Species Composition and Canopy Architecture Information Expressed in Leaf Water

.Vegetation Species Composi t ion and Canopy Arch i tecture Information Expressed in Leaf Water Absorption Measured in the 1000 nm and 2200 nm Spectral Region by an Imaging Spectrometer: Robert O. Greenl,2 and Dar A. Roberts2 1 Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA 91109 2University California, Santa Barbara, CA 93106 INTRODUCTION Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local, to regional and even synoptic scales (e.g. Wessman 1992). Classical approaches rely on vegetation indices, such as the Normalized Difference Vegetation I n d e x (NDVI) to es t ima te biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine- scale information about specific sites to larger areas of similar composition, Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some o f t h i s capab i l i t y has been demonstrated through improved discrimination of vegetation (e.g. Roberts et al,, 1992,1 993a), estimates of canopy biochemistry (e.g. Wessman et al,, 1988) and liquid water estimates from vegetation (Green et al., 1991, 1993 and Roberts et al., 1993 b,1994). In this paper we investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from

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