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• W2567495574 abstract "In coastal wetlands of the Gulf of Mexico, the invasive plant species Phragmites australis (common reed) rapidly alters the ecology of a site by shifting plant communities from heterogeneous mixtures of plant species to homogenous stands of Phragmites. Phragmites grows in very dense stands at an average height of 4.6 m and outcompetes native plants for resources. To restore affected wetlands, resource managers require an accurate map of Phragmites locations. Previous studies have used satellite and manned aircraft-based remote-sensing images to map Phragmites in relatively large areas at a coarse scale; however, low-altitude high-spatial-resolution pixel-based classification approaches would improve the mapping accuracy. This study explores the supervised classification methods to accurately map Phragmites in the coastal wetlands at the delta of the Pearl River in Louisiana and Mississippi, USA, using high-resolution (8 cm ground sample distance; GSD) multispectral imagery collected from a small unmanned aerial system platform at an altitude of 120 m. We create a map through pixel-based Support Vector Machines (SVM) classification using blue, green, red, red edge, and near-infrared spectral bands along with a digital surface model (DSM), vegetation indices, and morphological attribute profiles (MAPs) as features. This study also demonstrates the effects of different features and their usefulness in generating an accurate map of Phragmites locations. Accuracy assessment based on a) a subset of training/testing samples (to show classifier performance) and b) the entire ground reference (GR) map (to show the quality of mapping) is demonstrated. Kappa, overall accuracy (OA), class accuracies, and their confidence intervals (CIs) are reported. An OA of 91% and kappa of 63 is achieved. The results of this study indicate that features such as MAPs are very useful in accurately mapping invasive Phragmites compared with existing region-based approaches." @default.
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• W2567495574 date "2016-12-21" @default.
• W2567495574 modified "2023-09-28" @default.
• W2567495574 title "Mapping of invasive phragmites (common reed) in Gulf of Mexico coastal wetlands using multispectral imagery and small unmanned aerial systems" @default.
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• W2567495574 doi "https://doi.org/10.1080/01431161.2016.1271480" @default.
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