Scene classification using high spatial resolution multispectral data
Garner, Jamada J.
Olsen, Richard C.
MetadataShow full item record
Spectral imagery has traditionally been an important tool for terrain categorization (TERCAT). High-spatial resolution (8-meter), 4-color MSI data from IKONOS provide a new tool for scene classification. The utility of these data are studied for the purpose of classifying the Elkhorn Slough and surrounding wetlands in central California. The specific goal was to determine to what degree an existing classification map could be replicated using the 4-color imagery. The existing map was used as an input to a supervised classification process. Errors in that map required development of revised exemplar spectra sets, eliminating mixed classes. Classification was done using a spectral angle mapper and maximum likelihood classifier. Results were compared to the original classification map. Confusion matrix calculations showed agreement at the 10-20% level. This lack of agreement is attributed to errors in the original map at the relatively high resolution of IKONOS.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Showing items related by title, author, creator and subject.
Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R. (SPIE, 2013);Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were ...
Costica, Yinon (Monterey, California. Naval Postgraduate School, 2010-12);The intelligence making process, often described as the intelligence cycle, consists of phases. Congestion may be experienced in phases that require time consuming tasks such as translation, processing and analysis. To ...
Karo, Ciril. (Monterey, California. Naval Postgraduate School, 1998-09);Nearest Neighbor (NN) classification is a non-parametric discrimination and classification technique. In NN classification a test item is compared by some similarity measure of its multiple variables (usually a distance ...