A Spectral Unmixing Approach to Leaf Area Index (LAI) Estimation at the Alpine Treeline Ecotone

The objective of this research was to develop methods for mapping arboreal leaf area index (LAI) at the alpine treeline ecotone in Glacier National Park, Montana using Landsat Thematic Mapper (TM) imagery. A three-stage approach was tested for addressing the problem of mixed pixels in biophysical value estimation. This paper illustrates a proof of concept for this method. First, spectral unmixing was used to obtain estimates of the percentage of each pixel that was composed of tree, tundra, bare rock and shadow. Spectral signatures obtained through image interpretation were used for mixture modeling. The second step involved adjusting the pixel vegetation index (VI) values so that they represented the VI of the tree-only portion of the pixel, assuming an average VI for background components. Finally, the adjusted VI was regressed against leaf area index (LAI) measured in the field using a LiCor LAI-2000 and spatially referenced through differential GPS. Results using the adjusted VI values were compared with unadjusted VI, as were the results obtained using the normalized difference vegetation index (NDVI) and the simple ratio (SR).

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