Mapping C3 and C4 plant functional types using separated solar-induced chlorophyll fluorescence from hyperspectral data

引用方式: Liu LY, Cheng ZH. Mapping C3 and C4 plant functional types using separated solar-induced chlorophyll fluorescence from hyperspectral data. International Journal of Remote sensing, 2011, 32(24): 9171-9183.

文献信息
标题	Mapping C3 and C4 plant functional types using separated solar-induced chlorophyll fluorescence from hyperspectral data
年份	2011
出版社	International Journal of Remote Sensing
链接
语言	en
DOI	10.1080/01431161.2010.550646
摘要	Numerous researchers have described the chlorophyll fluorescence (ChlF) difference of C3 and C4 plants under different environmental conditions. This study presents a novel passive detection method to discriminate between the C3 and C4 plant functional types (PFTs) using solar-induced ChlF. The solar-induced ChlF radiation was extracted from airborne hyperspectral data acquired by the Operational Modular Imaging Spectrometer (OMIS) II instrument. Our results showed that the fluorescence signal of C4 species was about 2.2 times greater than that of C3 species at the same normalized difference vegetation index (NDVI) level. The average value of the relative ChlF for C4 species was 18.2 w m−2 μm−1 compared with 7.8 w m−2 μm−1 for C3 species. The classification potential of the solar-induced ChlF for C3 and C4 species was compared with the spectral reflectance and NDVI. The spectral separation rate of the solar-induced ChlF was 1.31, but the maximum value of the spectral reflectances was 0.63 at the 750 nm band, and the spectral separation rate of NDVI was only 0.04. (For Gaussian distributions, pairwise separation rates of 90% corresponded to a value of 1.5, whereas a value of 0.55 corresponded to a separation rate of about 70%.) A simple decision tree was built to discriminate between C3 and C4 species based on the difference between their ChlF. An accuracy assessment indicated that C3 and C4 species have been well classified; the overall classification accuracy was 92% and the kappa coefficient was 0.84. Therefore, although it is quite challenging to classify C3 and C4 species based on the reflectance signal, our results present a novel method for successfully discriminating between C3 and C4 species.
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Mapping C3 and C4 plant functional types using separated solar-induced chlorophyll fluorescence from hyperspectral data

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