|Ge, Shaokui - UC BERKELEY|
|Gong, Peng - UC BERKELEY|
Submitted to: Environmental Monitoring and Assessment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 22, 2005
Publication Date: January 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 phonological assessment of an invasive weed. Environmental Monitoring and Assessment. p. 1-18 Interpretive Summary: Remote sensing can be used to help detect and quantify the distribution and abundance of invasive weeds in complex canopies. This scientific article describes the process by which one such weed, yellow starthistle, was evaluated using a special remote sensing device, a hyperspectral imager, to allow its detection in rangeland habitats. The device uses different wave-lengths of light to determine a “spectral signature” for different plants based on identifiable plant parts such as characteristic flower color and reflectance patterns given off by the shape and structure of the species including its leaf and stem architecture. Quantifying invasive plants like yellow starthistle is important to rangeland managers as this plant can be toxic to horses and also degrades the quality of range and the amount of forage that can be grazed upon by both livestock and wildlife. These new remote sensing tools are now being used to make area-wide assessments of yellow starthistle density and its impact to western rangelands.
Technical Abstract: Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers of yellow starthistle (Centaurea solstitialis)) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios (AFR) 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 postflowers). 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 NIR plateau from 730 nm to 950 nm. For airborne CASI data, only the red absorption region and NIR 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.