Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data

Remotely sensed vegetation indices (VIs) have been widely used to estimate the aboveground biomass (AGB) carbon stock of coastal wetlands by establishing Vis-related linear models. However, these models always have high uncertainties due to the large spatial variation and fragmentation of coastal we...

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Autores principales: Shaobo Sun, Yafei Wang, Zhaoliang Song, Chu Chen, Yonggen Zhang, Xi Chen, Wei Chen, Wenping Yuan, Xiuchen Wu, Xiangbin Ran, Yidong Wang, Qiang Li, Lele Wu
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Publicado: MDPI AG 2021
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spelling oai:doaj.org-article:e4e7689eb95245d691de1287e873c5ec2021-11-11T18:53:52ZModelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data10.3390/rs132143212072-4292https://doaj.org/article/e4e7689eb95245d691de1287e873c5ec2021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4321https://doaj.org/toc/2072-4292Remotely sensed vegetation indices (VIs) have been widely used to estimate the aboveground biomass (AGB) carbon stock of coastal wetlands by establishing Vis-related linear models. However, these models always have high uncertainties due to the large spatial variation and fragmentation of coastal wetlands. In this paper, an efficient coastal wetland AGB model for the Bohami Rim coastal wetlands was presented based on multiple data sets. The model was developed statistically with 7 independent variables from 23 metrics derived from remote sensing, topography, and climate data. Compared to previous models, it had better performance, with a root mean square error and <i>r</i> value of 188.32 g m<sup>−2</sup> and 0.74, respectively. Using the model, we firstly generated a regional coastal wetland AGB map with a 10 m spatial resolution. Based on the AGB map, the AGB carbon stock of the Bohai Rim coastal wetland was 2.11 Tg C in 2019. The study demonstrated that integrating emerging high spatial resolution multi-remote sensing data and several auxiliary metrics can effectively improve VIs-based coastal wetland AGB models. Such models with emerging freely available data sets will allow for the rapid monitoring and better understanding of the special role that “blue carbon” plays in global carbon cycle.Shaobo SunYafei WangZhaoliang SongChu ChenYonggen ZhangXi ChenWei ChenWenping YuanXiuchen WuXiangbin RanYidong WangQiang LiLele WuMDPI AGarticleaboveground biomassANPPcoastal wetlandsremote sensingSentinel satellitecarbon stockScienceQENRemote Sensing, Vol 13, Iss 4321, p 4321 (2021)
institution DOAJ
collection DOAJ
language EN
topic aboveground biomass
ANPP
coastal wetlands
remote sensing
Sentinel satellite
carbon stock
Science
Q
spellingShingle aboveground biomass
ANPP
coastal wetlands
remote sensing
Sentinel satellite
carbon stock
Science
Q
Shaobo Sun
Yafei Wang
Zhaoliang Song
Chu Chen
Yonggen Zhang
Xi Chen
Wei Chen
Wenping Yuan
Xiuchen Wu
Xiangbin Ran
Yidong Wang
Qiang Li
Lele Wu
Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
description Remotely sensed vegetation indices (VIs) have been widely used to estimate the aboveground biomass (AGB) carbon stock of coastal wetlands by establishing Vis-related linear models. However, these models always have high uncertainties due to the large spatial variation and fragmentation of coastal wetlands. In this paper, an efficient coastal wetland AGB model for the Bohami Rim coastal wetlands was presented based on multiple data sets. The model was developed statistically with 7 independent variables from 23 metrics derived from remote sensing, topography, and climate data. Compared to previous models, it had better performance, with a root mean square error and <i>r</i> value of 188.32 g m<sup>−2</sup> and 0.74, respectively. Using the model, we firstly generated a regional coastal wetland AGB map with a 10 m spatial resolution. Based on the AGB map, the AGB carbon stock of the Bohai Rim coastal wetland was 2.11 Tg C in 2019. The study demonstrated that integrating emerging high spatial resolution multi-remote sensing data and several auxiliary metrics can effectively improve VIs-based coastal wetland AGB models. Such models with emerging freely available data sets will allow for the rapid monitoring and better understanding of the special role that “blue carbon” plays in global carbon cycle.
format article
author Shaobo Sun
Yafei Wang
Zhaoliang Song
Chu Chen
Yonggen Zhang
Xi Chen
Wei Chen
Wenping Yuan
Xiuchen Wu
Xiangbin Ran
Yidong Wang
Qiang Li
Lele Wu
author_facet Shaobo Sun
Yafei Wang
Zhaoliang Song
Chu Chen
Yonggen Zhang
Xi Chen
Wei Chen
Wenping Yuan
Xiuchen Wu
Xiangbin Ran
Yidong Wang
Qiang Li
Lele Wu
author_sort Shaobo Sun
title Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
title_short Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
title_full Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
title_fullStr Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
title_full_unstemmed Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
title_sort modelling aboveground biomass carbon stock of the bohai rim coastal wetlands by integrating remote sensing, terrain, and climate data
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/e4e7689eb95245d691de1287e873c5ec
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