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United States Department of Agriculture

Agricultural Research Service

Title: Mapping Giant Salvinia with Satellite Imagery and Image Analysis

Authors
item Everitt, James
item Fletcher, Reginald
item Elder, H.S. - TX PARKS&WLDLIF-JASPERTX
item Yang, Chenghai

Submitted to: Environmental Monitoring and Assessment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 20, 2007
Publication Date: March 15, 2008
Citation: Everitt, J.H., Fletcher, R.S., Elder, H., Yang, C. 2008. Mapping giant salvinia with satellite imagery and image analysis. Environmental Monitoring and Assessment. 139:35-40.

Interpretive Summary: Giant salvinia is an exotic, invasive aquatic fern that has invaded and clogged waterways in many areas of the world. A study was conducted to determine the potential of using QuickBird high resolution (2.4 m) satellite imagery coupled with unsupervised image analysis for distinguishing and mapping giant salvinia in an east Texas reservoir. Color-infrared (green, red, and near-infrared bands), normal color (blue, green, and red bands), and false color (blue, green, red, and near-infrared bands) composite images were subjected to image analysis. Accuracy assessments performed on classification maps of the images had producer’s and user’s accuracies for giant salvinia ranging from 87.8% to 93.5%. These findings should be of interest to wetland resource managers who are interested in locating infestations and controlling this aquatic weed.

Technical Abstract: QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands), normal color (blue, green and red bands), and false color (blue, green, red, and near-infrared bands) composite images were studied. Unsupervised image analysis was used to classify the imagery. Accuracy assessments performed on the classification maps of the three composite images had producer’s and user’s accuracies for giant salvinia ranging from 87.8% to 93.5%. Color-infrared, normal color, and false color satellite imagery were excellent for distinguishing giant salvinia in a complex field habitat.

Last Modified: 10/30/2014
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