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• W2080116978 abstract "Nonnative plant species are causing enormous ecological and environmental impacts from local to global scale. Remote sensing images have had mixed success in providing spatial information on land cover characteristics to land managers that increase effective management of invasions into native habitats. However, there has been limited evaluation of the use of hyperspectral data and processing techniques for mapping specific invasive species based on their spectral characteristics. This research evaluated three different methods of processing hyperspectral imagery: minimum noise fraction (MNF), continuum removal, and band ratio indices for mapping iceplant (Carpobrotus edulis) and jubata grass (Cortaderia jubata) in California's coastal habitat. Validation with field sampling data showed high mapping accuracies for all methods for identifying presence or absence of iceplant (97%), with the MNF procedure producing the highest accuracy (55%) when the classes were divided into four different densities of iceplant." @default.
• W2080116978 created "2016-06-24" @default.
• W2080116978 creator A5024053964 @default.
• W2080116978 date "2003-07-30" @default.
• W2080116978 modified "2023-10-14" @default.
• W2080116978 title "Mapping nonnative plants using hyperspectral imagery" @default.
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• W2080116978 doi "https://doi.org/10.1016/s0034-4257(03)00096-8" @default.
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