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Mapping spiny aster infestations with QuickBird imagery
Authors:J H Everitt  C Yang  D L Drawe
Institution:1. USDA-ARS, Kika de la Garza Agricultural Research Center , 2413 E. Hwy 83, Weslaco, TX, 78596, USA jeveritt@weslaco.ars.usda.gov;3. USDA-ARS, Kika de la Garza Agricultural Research Center , 2413 E. Hwy 83, Weslaco, TX, 78596, USA;4. Welder Wildlife Foundation , P.O. Drawer 1400, Sinton, TX, 78387, USA
Abstract:QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.
Keywords:QuickBird satellite imagery  False colour imagery  Unsupervised and supervised image analysis  Accuracy assessment  Leucosyrus spinosus
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