Object-Based Wetland Vegetation Classification Using Multi-Feature Selection of Unoccupied Aerial Vehicle RGB Imagery

Wetland vegetation is an important component of wetland ecosystems and plays a crucial role in the ecological functions of wetland environments. Accurate distribution mapping and dynamic change monitoring of vegetation are essential for wetland conservation and restoration. The development of unoccu...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 13; no. 23; p. 4910
Main Authors:	Zhou, Rui, Yang, Chao, Li, Enhua, Cai, Xiaobin, Yang, Jiao, Xia, Ying
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.12.2021
Subjects:	Accuracy Algorithms Aquatic ecosystems Bayesian analysis Biodiversity Cameras Classification Coefficients cost effectiveness decision support systems Decision trees Ecological function Environmental restoration Feasibility studies Feature selection geometry Image analysis Image processing Learning algorithms Machine learning machine learning algorithms Mapping Monitoring multi-feature Nature conservation Neural networks object-based image analysis (OBIA) Performance evaluation recursive feature elimination algorithm (RFE) Remote sensing Sensors Species classification Spectra Support vector machines Texture Unmanned aerial vehicles unoccupied aerial vehicles (UAVs) Vegetation Vegetation mapping wetland conservation wetland vegetation classification Wetlands
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
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