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

Haibo Wang; Jinbo Qian; Mingguo Ma; Xufeng Wang

doi:10.1117/12.830346

18 September 2009 The spectral characteristics of Stellera chamaejasme L. with varied coverage in Qilian of China

Haibo Wang, Jinbo Qian, Mingguo Ma, Xufeng Wang

Proceedings Volume 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI; 74721U (2009) https://doi.org/10.1117/12.830346
Event: SPIE Remote Sensing, 2009, Berlin, Germany

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.

Citation Download Citation

Haibo Wang, Jinbo Qian, Mingguo Ma, and Xufeng Wang "The spectral characteristics of Stellera chamaejasme L. with varied coverage in Qilian of China", Proc. SPIE 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, 74721U (18 September 2009); https://doi.org/10.1117/12.830346

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