Abstract
Leaf area index (LAI) is a key variable in crop growth models. The derivation of reliable LAI maps from satellite imagery would provide a means of spatially extrapolating these models. During the 2004 and 2005 growing seasons, hyperspectral data from the Compact High Resolution Imaging Spectrometer (CHRIS) sensor were acquired over a wheat crop in southern Alberta. The ability to obtain reliable LAI estimates from CHRIS data was investigated using a preexisting relationship between LAI and the modified transformed vegetation index (MTVI2). The performance of the recently develop MTVI2 in estimating LAI was compared to that of the more commonly used normalized difference vegetation index (NDVI). Both narrow and broad bands simulated from the CHRIS data were used in calculating the NDVI. All vegetation indices provided good relationships with LAI (R2 = 0.70–0.90). The errors in the estimated LAI values varied with vegetation index and were dependent on growth stage. The MTVI2 performed better than the NDVI at full canopy closure. Confirming previous reports in the literature, the NDVI tended to saturate at LAI values of 37–4, which resulted in an underestimation of LAI at full canopy closure. There was no benefit to using narrow spectral bands in the NDVI. Estimation of LAI using the MTVI2 was underestimated late in the season during the seed-filling period.
Published Version
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