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  • 唐亮东,张威,邓淞文,王英辉.基于组合植被指数的红树林树种遥感分类与生物碳储量变化研究[J].广西科学,2024,31(3):541-553.    [点击复制]
  • TANG Liangdong,ZHANG Wei,DENG Songwen,WANG Yinghui.Identification and Carbon Stock Change Measurement of Mangrove Species Based on Combined Vegetation Indices[J].Guangxi Sciences,2024,31(3):541-553.   [点击复制]
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基于组合植被指数的红树林树种遥感分类与生物碳储量变化研究
唐亮东1, 张威2, 邓淞文2, 王英辉1,2
0
(1.广西壮族自治区产业技术研究院, 广西 南宁 530201;2.广西大学海洋学院, 广西 南宁 530004)
摘要:
红树林的物种结构对红树林生物碳储量有极大的影响,红树林生物碳储量是核算红树林碳汇能力的重要指标。本研究基于Sentinel-2多光谱影像,构建11种植被指数组合,针对茅尾海地区红树林优势种无瓣海桑(Sonneratia apetala)和桐花树(Aegiceras corniculatum)训练了基于支持向量机(SVR)的分类模型,并使用InVEST模型计算了2019-2023年研究区红树林生物碳储量的变化情况。结果显示,红树林识别指数(MRI)与其他植被指数进行组合后能够显著提高无瓣海桑和桐花树的分类精度;2019-2023年,研究区无瓣海桑和桐花树的总生物碳储量持续增加,年均增长率为3.02%。由于光学影像无法准确区分无瓣海桑群落和无瓣海桑-桐花树混交群落,本研究结果对红树林混交群落中桐花树群落面积存在一定程度的低估;而在平陆运河工程建设过程中,应对茅尾海地区红树林采取必要的保护措施,并以其他省份红树林蓝碳碳汇交易项目为参考,促进广西蓝碳碳汇的开发利用。
关键词:  红树林  遥感  组合植被指数  物种分类  生物碳储量  InVEST模型
DOI:10.13656/j.cnki.gxkx.20240910.015
投稿时间:2024-02-28修订日期:2024-05-28
基金项目:广西科技重大专项“无固废与近零碳运河关键技术研发项目”(桂科AA23062054)和广西高校中青年教师科研基础能力提升项目(2021KY0013)资助
Identification and Carbon Stock Change Measurement of Mangrove Species Based on Combined Vegetation Indices
TANG Liangdong1, ZHANG Wei2, DENG Songwen2, WANG Yinghui1,2
(1.GuangxiInstitute ofIndustrial Technology, Nanning, Guangxi, 530201, China;2.School of Marine Sciences, Guangxi University, Nanning, Guangxi, 530004, China)
Abstract:
The species composition of mangrove forests significantly affects the biomass carbon stock of mangrove ecosystems,and thus the change in biomass carbon stock serves as an important indicator for assessing mangrove carbon sequestration.Utilizing Sentinel-2 multispectral imagery,this study constructed 11 vegetation index combinations.A Support Vector Regression(SVR)-based classifier was trained for the dominant mangrove species, Sonneratia apetala and Aegiceras corniculatum, in the Maowei Sea area.Subsequently,the InVEST model was employed to calculate the changes in biomass carbon stock of mangroves in the study area from 2019 to 2023.The results indicated that the combination of Mangrove Recognition Index(MRI)with other vegetation indices significantly improved the identification accuracy for S.apetala and A.corniculatum.Furthermore,from 2019 to 2023,the overall biomass carbon stock of S.apetala and A.corniculatum in the study area kept increasing,with an average annual growth rate of 3.02%.Due to the limitations of optical imagery in accurately distinguishing between pure S.apetala stands and mixed S.apetala-A.corniculatum communities,this study may have underestimated the actual area occupied by A.corniculatum within mixed mangrove communities.Therefore,it is recommended that appropriate protective measures be implemented for the mangrove forests in the Maowei Sea area during the construction of the Pinglu Canal project.Furthermore,drawing on the experience of blue carbon offset trading projects in other provinces can facilitate the development and utilization of blue carbon sequestration in Guangxi.
Key words:  mangrove  remote sensing  combined vegetation indices  species identification  biomass carbon stock  InVEST model

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