Skip to main content
ARS Home » Research » Publications at this Location » Publication #168977
Title: REMOTE SENSING OF GIANT REED WITH QUICKBIRD SATELLITE IMAGERY

Author
item Everitt, James
item YANG, CHENGHAI - TX A&M EXP'T. STN-WESLACO
item Deloach Jr, Culver

Submitted to: Journal of Aquatic Plant Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/1/2005
Publication Date: 6/15/2006
Citation: Everitt, J.H., Yang, C., Deloach Jr., C.J. 2006. Remote sensing of giant reed with QuickBird satellite imagery. Journal of Aquatic Plant Management. 43:81-85.

Interpretive Summary: The invasion and spread of undesirable plant species present serious problems for resource managers. Giant reed is an invasive perennial grass that invades wetlands and 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 to evaluate the potential of high resolution QuickBird satellite imagery for detecting giant reed infestations. Results showed that both false color-infrared and normal color satellite imagery could be used successfully to distinguish giant reed infestations. Accuracy assessments performed on computer classification maps showed that giant reed had both producer's and user's accuracies that ranged from 86% to 100%. The results should be of interest to weed specialists' and wetland resource managers.

Technical Abstract: QuickBird high resolution (2.8 m) satellite imagery was evaluated for distinguishing giant reed (Arundo donax L.) infestations along the Rio Grande in southwest Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Four subsets of the satellite image were extracted and used as study sites. Unsupervised classification techniques were used to classify false color (green, red, and near-infrared bands) and normal color (blue, green, and red bands) composite images of each site. Accuracy assessments performed on the classification maps of the four sites had producer's and user's accuracies for giant reed that ranged from 86% to 100%. Both false color and normal color satellite imagery did an excellent job in distinguishing giant reed infestations.