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Proceedings Paper

The spectral characteristics of Stellera chamaejasme L. with varied coverage in Qilian of China
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Paper Abstract

Stellera chamaejasme L.(Stellera) is a poisonous weed that widely distributed in grassland ecosystems of Western China. Field reflectance measurements were performed for the Stellera with varied coverage in Qilian county of China. The spectral characteristics of some main species were analyzed. The result indicated that the reflectance of the corolla of Stellera was greater than that of other species over the full range of wavelengths. The best time to distinguish Stellera is the full bloom period of the Stellera. Three groups of spectral measurements were performed for the Stellera with varied coverage. The first experiment indicated that the reflectance increased with the increased densities in near-infrared wavelengths, but no obvious regular pattern existed in visible bands. On the contrary, in the full bloom period of the Stellera, there is an obviously increasing trend of reflectance both in visible and near-infrared bands with the increased densities. No distinct trend was found in the third experiment that conducted after the full bloom period. A clear linear relationship exited in analyzing the correlation between Stellera with varied density and their spectral characteristics. Thus, the density of Stellera could be quantitatively estimated based on the spectral characteristics from hyperspectral remote sensing images.

Paper Details

Date Published: 18 September 2009
PDF: 11 pages
Proc. SPIE 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, 74721U (18 September 2009); doi: 10.1117/12.830346
Show Author Affiliations
Haibo Wang, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Jinbo Qian, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Mingguo Ma, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Xufeng Wang, Cold and Arid Regions Environmental and Engineering Research Institute (China)


Published in SPIE Proceedings Vol. 7472:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XI
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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