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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING AND GIS FOR DETECTING AND MAPPING INVASIVE WEEDS IN RIPARIAN AND WETLAND ECOSYSTEMS Title: Comparison of QuickBird and SPOT 5 Satellite Imagery for Mapping Giant Reed

Authors
item Everitt, James
item YANG, CHENGHAI
item FLETCHER, REGINALD
item Deloach Jr, Culver

Submitted to: Journal of Aquatic Plant Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 19, 2007
Publication Date: January 30, 2008
Citation: Everitt, J.H., Yang, C., Fletcher, R.S., Deloach Jr, C.J. 2007. Comparison of QuickBird and SPOT 5 satellite imagery for mapping giant reed. Journal of Aquatic Plant Management. 46:77-82.

Interpretive Summary: Giant reed is an invasive perennial grass that invades riparian sites in many areas of the world. It displaces native plants and animals, consumes excessive amounts of water, and alters river channel morphology by retaining sediments and constricting flows. A study was conducted along the Rio Grande in southwest Texas comparing QuickBird (2.4 m resolution) and SPOT 5 (10 m resolution) multispectral satellite imagery for mapping giant reed infestations. Results showed that both QuickBird and SPOT 5 imagery could be used successfully to map giant reed. Accuracy assessments performed on QuickBird classification maps had producer’s and user’s accuracies for giant reed of 95% and 98%, respectively. Accuracy assessments performed on SPOT 5 classification maps had mean producer’s and user’s accuracies for giant reed of 80% and 88%, respectively. The lower accuracies of the SPOT 5 imagery were attributed to it lower spatial resolution. These results should be of interest to weed scientists and riparian resource managers.

Technical Abstract: QuickBird (2.4 m resolution) and SPOT 5 (10 m resolution) multi-spectral satellite imagery were compared for mapping the invasive grass, giant reed (Arundo donax L.), along the Rio Grande in southwest Texas. The imagery had three bands (green, red, and near-infrared). Three subsets from both the QuickBird and SPOT 5 images were extracted and used as study sites. The same subsets were extracted from both images. The images were subjected to supervised image analysis. Accuracy assessments performed on QuickBird classification maps from the three sites had producer’s and user’s accuracies for giant reed that ranged from 92% to 100%. Accuracy assessments performed on SPOT 5 classification maps from the three sites had producer’s and user’s accuracies for giant reed ranging from 75.7% to 93.3%. The lower accuracies of the SPOT 5 image classifications were attributed to its coarser resolution.

Last Modified: 9/10/2014
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