Leaf Area Index (LAI) is a key parameter controlling biophysical processes of the vegetation canopy. LAI helps to estimate productivity of agriculture and forest canopies, which can then serve as input to crop modelling. LAI can be measured using different approaches such as destructive sampling, optical ground-based instruments and optical imagery. Hyperspectral data has the advantage of distinguishing different target types within a pixel using spectral unmixing analysis as a tool to separate such spectral signatures. This paper investigates the relationship between ground-based effective LAI (eLAI) measurements estimated with the LI-COR LAI-2000 and eLAI values derived from Probe-1 hyperspectral surface reflectance data. This data were collected together with ground-based eLAI data during the summer of 1999 in Clinton, an agricultural area in South Western Ontario, Canada. The crops investigated for this study are corn and white beans. Correlations between ground eLAI and eLAI values derived from hyperspectral data produced encouraging results. Correlations were not strong when analysis was done on a single crop type. However, correlation results are good (r = 0.91) when data from all canopies are considered.
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