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Title: HYPERSPECTRAL CHARACTERISTICS OF CANOPY COMPONENTS AND STRUCTURE FOR PHENOLOGICAL ASSESSMENT OF AN INVASIVE WEED

Author
item GE, SHAOKUI - UNIV OF CA-BERKELEY
item Everitt, James
item Carruthers, Raymond
item GONG, PENG - UNIV OF CA-BERKELEY
item Anderson, Gerald

Submitted to: Environmental Monitoring and Assessment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/22/2005
Publication Date: 12/1/2006
Citation: Ge, S., Everitt, J.H., Carruthers, R.I., Gong, P., Anderson, G.L. 2006. Hyperspectral characteristics of canopy components and structure for phenological assessment of an invasive weed. Environmental Monitoring and Assessment. 120:109-126

Interpretive Summary: The invasion and spread of noxious weeds in rangelands is a major deterrent to management of these areas. Yellow starthistle is an exotic, invasive weed that is widely distributed in rangeland and wildland areas of the Western United States, especially California, Idaho, and Oregon. A study was conducted in California utilizing hyperspectral reflectance measurements to determine the spectral characteristics of four canopy components (stems, buds, opening flowers, and post-flowers) of yellow starthistle. The canopy components were combined to simulate flowering stages. Results showed that hyperspectral data could be used to characterize canopy components and identify different flowering stages. Canopy measurements showed that the blue, red, and near-infrared spectral bands were optimum for differentiating among flowering stages. Airborne hyperspectral imagery showed that only the red and near-infrared bands could be used to identify flowering stages in the field. These findings should be of interest to rangeland and wildland managers interested in using remote sensing techniques to distinguish invasive weeds.

Technical Abstract: Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers) of yellow starthistle (Centaurea solistitialis) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios of 10%, 40%, 70%, and 90%, respectively. Spectral dissimilarity and spectral angles were calculated to quantitatively identify spectral differences among canopy components and characteristic patterns of these flowering stages. This study demonstrated the ability of hyperspectral data to characterize canopy components, and identify different flowering stages. Stems had a typical spectral profile of green vegetation, which produced a spectral dissimilarity with three reproduction organs (buds, opening flowers, and post-flowers). Quantitative differences between simulated flower stages depended on spectral regions and phenological stages examined. Using full-range canopy spectra, the initial flowering stage could be separated from the early peak, peak, and late flowering stages by three spectral regions, i.e. the blue absorption (around 480 nm) and red absorption (around 650 nm) regions and near-infrared plateau from 730 nm to 950 nm. For airborne hyperspectral CASI data, only the red absorption region and near-infrared plateau could be used to identify the flowering stages in the field. This study also revealed that the peak flowering stage was more easily recognized than any of the other three stages.