Spatiotemporal Dynamics of Wetland in Dongting Lake Based on Multi-Source Satellite Observation Data during Last Two Decades

Liwei Xing, Liang Chi, Shuqing Han, Jianzhai Wu, Jing Zhang, Cuicui Jiao and Xiangyang Zhou ()
Additional contact information
Liwei Xing: Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Liang Chi: Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Shuqing Han: Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jianzhai Wu: Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jing Zhang: Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Cuicui Jiao: College of Economics, Sichuan University of Science & Engineering, Zigong 643000, China
Xiangyang Zhou: Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China

IJERPH, 2022, vol. 19, issue 21, 1-17

Abstract: Monitoring the dynamics of wetland resources has practical value for wetland protection, restoration and sustainable utilization. Dongting Lake wetland reserves are well known for both their intra-annual and inter-annual dynamic changes due to the effects of natural or human factors. However, most wetland monitoring research has failed to consider the seasonal wetlands, which is the most fragile wetland type, requiring more attention. In this study, we used multi-source time series remote sensing data to monitor three Dongting Lake wetland reserves between 2000 and 2020, and the seasonal wetlands were separated from permanent wetlands. Multispectral and indices time series were generated at 30 m resolution using a two-month composition strategy; the optimal features were then selected using the extension of the Jeffries–Matusita distance (J Bh ) and random forest (RF) importance score; yearly wetland maps were identified using the optimal features and the RF classifier. Results showed that (1) the yearly wetland maps had good accuracy, and the overall accuracy and kappa coefficients of all wetland maps from 2000 to 2020 were above 89.6% and 0.86, respectively. Optimal features selected by J Bh can improve both computational efficiency and classification accuracy. (2) The acreage of seasonal wetlands varies greatly among multiple years due to inter-annual differences in precipitation and evaporation. (3) Although the total wetland area of the three Dongting Lake wetland reserves remained relatively stable between 2000 and 2020, the acreage of the natural wetland types still decreased by 197.0 km 2 , and the change from natural wetland to human-made wetland (paddy field) contributed the most to this decrease. From the perspective of the ecological community, the human-made wetland has lower ecological function value than natural wetlands, so the balance between economic development and ecological protection in the three Dongting Lake wetland reserves requires further evaluation. The outcomes of this study could improve the understanding of the trends and driving mechanisms of wetland dynamics, which has important scientific significance and application value for the protection and restoration of Dongting Lake wetland reserves.

Keywords: wetland; remote sensing; dynamic; random forest; J Bh extension (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/19/21/14180/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/21/14180/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:19:y:2022:i:21:p:14180-:d:957935

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().