Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China

Wetlands, as the most essential ecosystem, are degraded throughout the world. Wetlands in Zhenlai county, with the Momoge National Nature Reserve, which was included on the Ramsar list, have degraded by nearly 30%. Wetland degradation is a long-term continuous process with annual or interannual chan...

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Autores principales:	Sixue Shi, Yu Chang, Yuehui Li, Yuanman Hu, Miao Liu, Jun Ma, Zaiping Xiong, Ding Wen, Binglun Li, Tingshuang Zhang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	wetland loss synthetic aperture radar optical remote sensing random forest classification land-use classification multitemporal remote sensing Science Q
Acceso en línea:	https://doaj.org/article/e41d01ccdad141baa2f0bf22c351b4ca
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spelling	oai:doaj.org-article:e41d01ccdad141baa2f0bf22c351b4ca2021-11-25T18:53:50ZUsing Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China10.3390/rs132245142072-4292https://doaj.org/article/e41d01ccdad141baa2f0bf22c351b4ca2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4514https://doaj.org/toc/2072-4292Wetlands, as the most essential ecosystem, are degraded throughout the world. Wetlands in Zhenlai county, with the Momoge National Nature Reserve, which was included on the Ramsar list, have degraded by nearly 30%. Wetland degradation is a long-term continuous process with annual or interannual changes in water area, water level, or vegetation presence and growth. Therefore, it requires sufficiently frequent and high-spatial-resolution data to represent its dynamics. This study mapped yearly land-use maps with 30-m resolution from 1985 to 2018 using Landsat data in Google Earth Engine (GEE) to explore the wetland degradation process and mapped 12-day interval land-use maps with 15-m resolution using the Sentinel-1B and Sentinel-2 data in GEE and other assistant platforms to study the characteristics of wetland dynamics in 2018. Four sets of maps were generated using Sentinel-1B (S1), Sentinel-2 (S2), the combination of Sentinel-1B and Sentinel-2 (S12), and S12 with multitemporal remote sensing (S12’). All of the classifications were performed in the Random Forest Classification (RFC) method using remote sensing indicators. The results indicate that S12’ was the most accurate. Then, the impact of the historic land-use degradation process on current wetland change dynamics was discussed. Stable, degradation, and restoration periods were identified according to the annual changes in wetlands. The degraded, stable, restored, and vulnerable zones were assessed based on the transformation characteristics among wetlands and other land-use types. The impact of historical land-use trajectories on wetland change characteristics nowadays is diverse in land-use types and distributions, and the ecological environment quality is the comprehensive result of the effect of historical land-use trajectories and the amount of rainfall and receding water from paddy fields. This study offers a new method to map high-spatiotemporal-resolution land-use (S12’) and addresses the relationship between historic wetland change characteristics and its status quo. The findings are also applicable to wetland research in other regions. This study could provide more detailed scientific guidance for wetland managers by quickly detecting wetland changes at a finer spatiotemporal resolution.Sixue ShiYu ChangYuehui LiYuanman HuMiao LiuJun MaZaiping XiongDing WenBinglun LiTingshuang ZhangMDPI AGarticlewetland losssynthetic aperture radaroptical remote sensingrandom forest classificationland-use classificationmultitemporal remote sensingScienceQENRemote Sensing, Vol 13, Iss 4514, p 4514 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	wetland loss synthetic aperture radar optical remote sensing random forest classification land-use classification multitemporal remote sensing Science Q
spellingShingle	wetland loss synthetic aperture radar optical remote sensing random forest classification land-use classification multitemporal remote sensing Science Q Sixue Shi Yu Chang Yuehui Li Yuanman Hu Miao Liu Jun Ma Zaiping Xiong Ding Wen Binglun Li Tingshuang Zhang Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China
description	Wetlands, as the most essential ecosystem, are degraded throughout the world. Wetlands in Zhenlai county, with the Momoge National Nature Reserve, which was included on the Ramsar list, have degraded by nearly 30%. Wetland degradation is a long-term continuous process with annual or interannual changes in water area, water level, or vegetation presence and growth. Therefore, it requires sufficiently frequent and high-spatial-resolution data to represent its dynamics. This study mapped yearly land-use maps with 30-m resolution from 1985 to 2018 using Landsat data in Google Earth Engine (GEE) to explore the wetland degradation process and mapped 12-day interval land-use maps with 15-m resolution using the Sentinel-1B and Sentinel-2 data in GEE and other assistant platforms to study the characteristics of wetland dynamics in 2018. Four sets of maps were generated using Sentinel-1B (S1), Sentinel-2 (S2), the combination of Sentinel-1B and Sentinel-2 (S12), and S12 with multitemporal remote sensing (S12’). All of the classifications were performed in the Random Forest Classification (RFC) method using remote sensing indicators. The results indicate that S12’ was the most accurate. Then, the impact of the historic land-use degradation process on current wetland change dynamics was discussed. Stable, degradation, and restoration periods were identified according to the annual changes in wetlands. The degraded, stable, restored, and vulnerable zones were assessed based on the transformation characteristics among wetlands and other land-use types. The impact of historical land-use trajectories on wetland change characteristics nowadays is diverse in land-use types and distributions, and the ecological environment quality is the comprehensive result of the effect of historical land-use trajectories and the amount of rainfall and receding water from paddy fields. This study offers a new method to map high-spatiotemporal-resolution land-use (S12’) and addresses the relationship between historic wetland change characteristics and its status quo. The findings are also applicable to wetland research in other regions. This study could provide more detailed scientific guidance for wetland managers by quickly detecting wetland changes at a finer spatiotemporal resolution.
format	article
author	Sixue Shi Yu Chang Yuehui Li Yuanman Hu Miao Liu Jun Ma Zaiping Xiong Ding Wen Binglun Li Tingshuang Zhang
author_facet	Sixue Shi Yu Chang Yuehui Li Yuanman Hu Miao Liu Jun Ma Zaiping Xiong Ding Wen Binglun Li Tingshuang Zhang
author_sort	Sixue Shi
title	Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China
title_short	Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China
title_full	Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China
title_fullStr	Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China
title_full_unstemmed	Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China
title_sort	using time series optical and sar data to assess the impact of historical wetland change on current wetland in zhenlai county, jilin province, china
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e41d01ccdad141baa2f0bf22c351b4ca
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Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China

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