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

IF 4.7 2区 地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-23 DOI:10.1109/JSTARS.2024.3485642
Huaqiao Xing;Yuqing Zhang;Linye Zhu;Na Xu;Xin Lan
{"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}
引用次数: 0

摘要

沿海湿地生态系统对碳封存至关重要,因此准确估算碳汇对其保护和管理至关重要。传统的碳汇估算方法忽视了潮湿土壤对稀疏植被的影响,导致对净初级生产力(NPP)的估算不准确,尤其是在湿地和植被混杂的沿海地区。为解决这一难题,本研究提出了一种改进的卡内基-梅斯-斯坦福法净初级生产力估算模型,该模型利用修正的土壤调整植被指数(MSAVI)来消除潮湿土壤的背景噪声,并计算光合有效辐射的部分。通过使用 MOD17A3 作为对比实验的参考数据,NPP 结果的准确性提高了 89.6 gC-m-2。随后,利用所提出的模型对山东沿海地区进行了碳汇估算和分析。结果表明首先,山东沿海地区的平均 NPPMSAVI 在 BIAS、相对偏差和均方根误差方面分别提高了 99.12 gC-m-2、36.17% 和 60.53 gC-m-2。其次,山东沿海地区生态系统净生产力(NEP)的空间分布为东高西低,东部平均值约为 210 gC-m-2,西部平均值约为 60 gC-m-2。不同土地类型的 NEP 季节性差异显著。第三,NEP 与气温、降水和太阳辐射有很强的相关性,平均 r 分别为 0.78、0.8 和 0.84。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
9.30
自引率
10.90%
发文量
563
审稿时长
4.7 months
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.
期刊最新文献
Are Mediators of Grief Reactions Better Predictors Than Risk Factors? A Study Testing the Role of Satisfaction With Rituals, Perceived Social Support, and Coping Strategies. Frontcover Unsupervised Domain Adaptative SAR Target Detection Based on Feature Decomposition and Uncertainty-Guided Self-Training Evaluation of Total Precipitable Water Trends From Reprocessed MiRS SNPP ATMS Observations, 2012–2021 Multiscale Attention-UNet-Based Near-Real-Time Precipitation Estimation From FY-4A/AGRI and Doppler Radar Observations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1