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Article Abstract – Sims & Gamon (2003)

Title:

Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features

Authors and affiliations:

Daniel A. Sims, Department of Biology and Microbiology, California State University LA, Los Angeles, CA
John A. Gamon, Department of Biology and Microbiology, California State University LA, Los Angeles, CA

Citation:

Remote Sensing of Environment 84: 526-537 (2003)

Abstract:

Because of the high water content of vegetation, water absorption features dominate spectral reflectance of vegetation in the near-infrared region of the spectrum. In comparison to indices based on chlorophyll absorption features (such as the normalized difference vegetation index (NDVI)), indices based on the water absorption bands are expected to “see” more deeply into thick canopies and have a preferential sensitivity to thin as opposed to thick tissues. These predictions are based on the much lower absorption coefficients for water in the short wavelength water bands as compared to chlorophyll. Thus, the water bands may have advantages over NDVI for remote sensing of photosynthetic tissues. Previous studies have primarily related water band indices (WI) to leaf area index (LAI). Here we expand the definition of photosynthetic tissues to include thin green stems and fruits and measure a wide range of species to determine the influence of variable tissue morphologies and canopy structures on these relationships. As expected, indices based on reflectance in the water absorption bands in the near infrared were best correlated with the water content of thin tissues (less than 0.5-cm thickness). The choice of wavelength for a water index was much more important for thick than for thin canopies, and the best wavelengths were those where water absorptance was weak to moderate. We identified three wavelength regions (950-970, 1150-1260 and 1520-1540 nm) that produced the best overall correlations with water content. Comparison of these wavelength regions with the atmospheric “windows” where water vapor absorption is minimal suggests that the 1150-1260 and 1520-1540 nm regions would be the best wavelengths for satellite remote sensing of water content. We also developed and tested a new Canopy Structure Index (CSI) that combines the low absorptance water bands with the simple ratio vegetation index (SR) to produce an index with a wider range of sensitivity to photosynthetic tissue area at all canopy thicknesses. CSI was better than either WI or SR alone for prediction of total area of photosynthetic tissues. However, SR was best for prediction of leaf area when other green tissues were excluded. All of these relationships showed good generality across a wide range of species and functional types.

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