Literature DB >> 17516139

Mapping giant salvinia with satellite imagery and image analysis.

J H Everitt1, R S Fletcher, H S Elder, C Yang.   

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 four-band composite (blue, green, red, and near-infrared bands) 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 four-band satellite imagery were excellent for distinguishing giant salvinia in a complex field habitat.

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Year:  2007        PMID: 17516139     DOI: 10.1007/s10661-007-9807-y

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  1 in total

1.  Weed mapping in cotton using ground-based sensors and GIS.

Authors:  Antonis V Papadopoulos; Vaya Kati; Demosthenis Chachalis; Vasileios Kotoulas; Stamatis Stamatiadis
Journal:  Environ Monit Assess       Date:  2018-09-30       Impact factor: 2.513

  1 in total

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