Exploring Wetland Dynamics in Large River Floodplain Systems with Unsupervised Machine Learning: A Case Study of the Dongting Lake, China

Large river floodplain systems (LRFS) are among the most diverse and dynamic ecosystems. Accurately monitoring the dynamics of LRFS over long time series is fundamental and essential for their sustainable development. However, challenges remain because the spatial distribution of LRFS is never stati...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 12; no. 18; p. 2995
Main Authors:	Jing, Lei, Zhou, Yan, Zeng, Qing, Liu, Shuguang, Lei, Guangchun, Lu, Cai, Wen, Li
Format:	Journal Article
Language:	English
Published:	MDPI AG 01.09.2020
Subjects:	accuracy administrative management algorithms artificial intelligence assets case studies China cost effectiveness dynamics ecological function ecosystems environmental factors floodplains k-medoids algorithm (PAM) lakes large river floodplain system long-term dynamics meadows migratory behavior moderate resolution imaging spectroradiometer monitoring remediation remote sensing rivers spatial distribution sustainable development time series analysis unsupervised machine-learning algorithm (UMLA) vegetation index water birds wetlands wintering grounds China
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
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