Abstract
Mangrove forests, as important ecological and economic resources, have suffered a loss in the area due to natural and human activities. Monitoring the distribution of and obtaining accurate information on mangrove species is necessary for ameliorating the damage and protecting and restoring mangrove forests. In this study, we compared the performance of UAV Rikola hyperspectral images, WorldView-2 (WV-2) satellite-based multispectral images, and a fusion of data from both in the classification of mangrove species. We first used recursive feature elimination‒random forest (RFE-RF) to select the vegetation’s spectral and texture feature variables, and then implemented random forest (RF) and support vector machine (SVM) algorithms as classifiers. The results showed that the accuracy of the combined data was higher than that of UAV and WV-2 data; the vegetation index features of UAV hyperspectral data and texture index of WV-2 data played dominant roles; the overall accuracy of the RF algorithm was 95.89% with a Kappa coefficient of 0.95, which is more accurate and efficient than SVM. The use of combined data and RF methods for the classification of mangrove species could be useful in biomass estimation and breeding cultivation.
Highlights
Published: 15 April 2021Ecosystems are the natural environmental conditions on which all organisms in the natural world depend, rendering many important services and continuously maintaining species and genetic diversity [1]
The results showed that the combined data accuracy (95.89%) is higher than that of Unmanned aerial vehicle (UAV)
random forest (RF) algorithm was applied to the combined data with the highest accuracy (95.89%) and outperformed the support vector machine (SVM) algorithm in terms of stability and adaptability
Summary
Ecosystems are the natural environmental conditions on which all organisms in the natural world depend, rendering many important services and continuously maintaining species and genetic diversity [1]. The mangrove ecosystem is one of the most important subsystems of global wetland ecosystems and one of the most biologically rich ecosystems on Earth, so it plays a highly important function in shallow wetland ecosystems [2,3]. Mangroves are tidal wetland woody biomes consisting of evergreen shrubs or trees with mangrove plants growing in tropical and subtropical coastal intertidal zones, and are globally recognized as carbon stock-rich ecosystems that provide irreplaceable social, economic, environmental, and ecological services to humans and coastal organisms [4,5]. The unique biochemical properties of mangroves enable them to produce a variety of unique natural
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