Title :
Discriminating C3 and C4 plants from hyperspectral data
Author_Institution :
Center for Earth Obs. & Digital Earth, Chinese Acad. of Sci., Beijing, China
Abstract :
This study presents a novel passive-detection method to discriminate between the C3 and C4 plant functional types using the solar-induced ChlF. The solar-induced ChlF radiation was extracted from airborne hyperspectral data acquired by the 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 NDVI level. The spectral separation rate of the solar-induced ChlF was 1.31, but the maximum value of the spectral reflectance and NDVI was only 0.63 at the 750 nm band. A simple decision tree was built to discriminate between the C3 and C4 species based on the difference between their ChlF. An accuracy assessment indicated that the C3 and C4 species had been well classified, with an overall classification accuracy of 92% and a kappa coefficient of 0.84. Although it is quite challenging to classify the C3 and C4 species based on the reflectance signal, our results present a novel method for successfully discriminating between the C3 and C4 species.
Keywords :
decision trees; geophysical techniques; C3 plant functional; C3 species; C4 plant functional; C4 species; NDVI level; OMIS II instrument; accuracy assessment; airborne hyperspectral data; chlorophyll fluorescence; classification accuracy; decision tree; fluorescence signal; kappa coefficient; passive-detection method; reflectance signal; solar-induced ChlF radiation; spectral separation rate; Accuracy; Fluorescence; Hyperspectral imaging; Reflectivity; Vegetation mapping; Pant functional types; chlorophyll fluorescence; classification; hyperspectral;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5648994