{"title":"用于估算沿海湿地碳汇的 MSAVI 增强型 CASA 模型:山东省案例研究","authors":"Huaqiao Xing;Yuqing Zhang;Linye Zhu;Na Xu;Xin Lan","doi":"10.1109/JSTARS.2024.3485642","DOIUrl":null,"url":null,"abstract":"Coastal wetland ecosystem is vital for carbon sequestration, making the accurate carbon sink estimation essential for its protection and management. Traditional carbon sink estimation methods have overlooked the influence of moist soil on sparse vegetation, resulting in the inaccurate estimation of net primary productivity (NPP), especially in coastal areas with mixed wetlands and vegetation. To address this challenge, this study proposed an improved Carnegie–Ames–Stanford approach model for NPP estimation, which utilizes the modified soil-adjusted vegetation index (MSAVI) to eliminate the background noise of moist soils and calculate the fraction of photosynthetically active radiation. By using MOD17A3 as reference data for comparative experiment, the accuracy of NPP results is improved by 89.6 gC·m\n<sup>−2</sup>\n. The proposed model was then used for carbon sink estimation and analysis of Shandong coastal area. The results indicate the following: First, the average NPP\n<sub>MSAVI</sub>\n across Shandong coastal area was improved by 99.12 gC·m\n<sup>−2</sup>\n, 36.17%, and 60.53 gC·m\n<sup>−2</sup>\n in BIAS, relative bias, and root-mean-square error, respectively. Second, the spatial distribution of net ecosystem productivity (NEP) in Shandong coastal area is higher in the east and lower in the west, with mean values of approximately 210 gC·m\n<sup>−2</sup>\n in the east and 60 gC·m\n<sup>−2</sup>\n in the west. The seasonal differences in NEP among different land types are significant. Third, NEP exhibits a strong correlation with temperature, precipitation, and solar radiation, with mean \n<italic>r</i>\n of 0.78, 0.8, and 0.84, respectively.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"19698-19712"},"PeriodicalIF":4.7000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10733757","citationCount":"0","resultStr":"{\"title\":\"MSAVI-Enhanced CASA Model for Estimating the Carbon Sink in Coastal Wetland Area: A Case Study of Shandong Province\",\"authors\":\"Huaqiao Xing;Yuqing Zhang;Linye Zhu;Na Xu;Xin Lan\",\"doi\":\"10.1109/JSTARS.2024.3485642\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coastal wetland ecosystem is vital for carbon sequestration, making the accurate carbon sink estimation essential for its protection and management. Traditional carbon sink estimation methods have overlooked the influence of moist soil on sparse vegetation, resulting in the inaccurate estimation of net primary productivity (NPP), especially in coastal areas with mixed wetlands and vegetation. To address this challenge, this study proposed an improved Carnegie–Ames–Stanford approach model for NPP estimation, which utilizes the modified soil-adjusted vegetation index (MSAVI) to eliminate the background noise of moist soils and calculate the fraction of photosynthetically active radiation. By using MOD17A3 as reference data for comparative experiment, the accuracy of NPP results is improved by 89.6 gC·m\\n<sup>−2</sup>\\n. The proposed model was then used for carbon sink estimation and analysis of Shandong coastal area. The results indicate the following: First, the average NPP\\n<sub>MSAVI</sub>\\n across Shandong coastal area was improved by 99.12 gC·m\\n<sup>−2</sup>\\n, 36.17%, and 60.53 gC·m\\n<sup>−2</sup>\\n in BIAS, relative bias, and root-mean-square error, respectively. Second, the spatial distribution of net ecosystem productivity (NEP) in Shandong coastal area is higher in the east and lower in the west, with mean values of approximately 210 gC·m\\n<sup>−2</sup>\\n in the east and 60 gC·m\\n<sup>−2</sup>\\n in the west. The seasonal differences in NEP among different land types are significant. Third, NEP exhibits a strong correlation with temperature, precipitation, and solar radiation, with mean \\n<italic>r</i>\\n of 0.78, 0.8, and 0.84, respectively.\",\"PeriodicalId\":13116,\"journal\":{\"name\":\"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing\",\"volume\":\"17 \",\"pages\":\"19698-19712\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10733757\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10733757/\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10733757/","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
MSAVI-Enhanced CASA Model for Estimating the Carbon Sink in Coastal Wetland Area: A Case Study of Shandong Province
Coastal wetland ecosystem is vital for carbon sequestration, making the accurate carbon sink estimation essential for its protection and management. Traditional carbon sink estimation methods have overlooked the influence of moist soil on sparse vegetation, resulting in the inaccurate estimation of net primary productivity (NPP), especially in coastal areas with mixed wetlands and vegetation. To address this challenge, this study proposed an improved Carnegie–Ames–Stanford approach model for NPP estimation, which utilizes the modified soil-adjusted vegetation index (MSAVI) to eliminate the background noise of moist soils and calculate the fraction of photosynthetically active radiation. By using MOD17A3 as reference data for comparative experiment, the accuracy of NPP results is improved by 89.6 gC·m
−2
. The proposed model was then used for carbon sink estimation and analysis of Shandong coastal area. The results indicate the following: First, the average NPP
MSAVI
across Shandong coastal area was improved by 99.12 gC·m
−2
, 36.17%, and 60.53 gC·m
−2
in BIAS, relative bias, and root-mean-square error, respectively. Second, the spatial distribution of net ecosystem productivity (NEP) in Shandong coastal area is higher in the east and lower in the west, with mean values of approximately 210 gC·m
−2
in the east and 60 gC·m
−2
in the west. The seasonal differences in NEP among different land types are significant. Third, NEP exhibits a strong correlation with temperature, precipitation, and solar radiation, with mean
r
of 0.78, 0.8, and 0.84, respectively.
期刊介绍:
The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.