Chang-Hua Ju;Yongchao Tian;Xia Yao;Weixing Cao;Yan Zhu;D. B. Hannawa

Jiangsu Key Laboratory for Information Agriculture, Key Laboratory of Crop Growth Regulation of Ministry of Agriculture, Nanjing Agricultural University, Nanjing 210095 (China);Department of Crop and Soil Science, College of Agricultural Sciences, Oregon State University, Corvallis, Oregon 97331-3002 (USA

res;red edge;lcc;simulated;nm;r67

Hyperspectral remote sensing makes it possible to non-destructively monitor leaf chlorophyll content (LCC). This study characterized the geometric patterns of the first derivative reflectance spectra in the red edge region of rapeseed (Brassica napus L.) and wheat (Triticum aestivum L.) crops. The ratio of the red edge area less than 718 nm to the entire red edge area was negatively correlated with LCC. This finding allowed the construction of a new red edge parameter, defined as red edge symmetry (RES). Compared to the commonly used red edge parameters (red edge position, red edge amplitude, and red edge area), RES was a better predictor of LCC. Furthermore, RES was easily calculated using the reflectance of red edge boundary wavebands at 675 and 755 nm (R-675 and R-755) and reflectance of red edge center wavelength at 718 nm (R-718), with the equation RES = (R-718 - R-675)/(R-755 - R-675). In addition, RES was simulated effectively with wide wavebands from the airborne hyperspectral sensor AVIRIS and satellite hyperspectral sensor Hyperion. The close relationships between the simulated RES and LCC indicated a high feasibility of estimating LCC with simulated RES from AVIRIS and Hyperion data. This made RES readily applicable to common airborne and satellite hyperspectral data derived from AVIRIS and Hyperion sources, as well as ground-based spectral reflectance data.