Remote Sensing · 2022 · 27 citations · 88 references
Natural ResourcesLandscape EcologyEcological RestorationLandscape Change DetectionRestoration EcologyLand Cover Change DetectionLand Cover MappingMulti-temporal Image AnalysisRemote Sensing Change DetectionVegetation Change DetectionWetland Change DetectionCoastal Wetland RestorationLand Cover AnalysisMulti-temporal AnalysisObject-based Image AnalysisRandom Forest ClassificationRemote Sensing ClassificationRestoration Success AssessmentWetland Remote Sensing
Coastal wetlands are restored to regenerate lost ecosystem services. Accurate and frequent representations of the distribution and area of coastal wetland communities are critical for evaluating restoration success. Typically, such data are acquired through laborious, intensive and expensive field surveys or traditional remote sensing methods that can be erroneous. Recent advances in remote sensing techniques such as high-resolution sensors (<2 m resolution), object-based image analysis and shallow learning classifiers provide promising alternatives but have rarely been applied in a restoration context. We measured the changes to wetland communities at a 200 ha restoring coastal wetland in eastern Australia, using remotely sensed Worldview-2 imagery, object-based image analysis and random forest classification. Our approach used structural rasters (digital elevation and canopy height models) and a multi-temporal technique to distinguish between spectrally similar land cover. The accuracy of our land cover maps was high, with overall accuracies ranging between 91 and 95%, and this supported early detection of increases in the area of key ecosystems, including mixed she-oak and paperbark (10 ha), mangroves (0.91 ha) and saltmarsh (4.31 ha), over a 5-year monitoring period. Our approach provides coastal managers with an accurate and frequent method for quantifying early responses of coastal wetlands to restoration, which is essential for informing adaptive management in the regeneration of ecosystem services.
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Leo Breiman · Machine Learning · 2001 · 126.2K citations · Full text
RANDOM FORESTS FOR CLASSIFICATION IN ECOLOGY
D. Richard Cutler, Thomas C. Edwards, Karen H. Beard et al. · Ecology · 2007 · 4.8K citations
Development of a New England Salt Marsh
Alfred C. Redfield · Ecological Monographs · 1972 · 872 citations