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自然资源遥感  2025, Vol. 37 Issue (2): 220-227    DOI: 10.6046/zrzyyg.2023368
  海岸带空间资源及生态健康遥感监测专栏 本期目录 | 过刊浏览 | 高级检索 |
基于GEE平台多源遥感数据的海南岛红树林碳储量估算
李尉尉(), 薛志泳, 朱建华(), 田震
国家海洋技术中心,天津 300112
Estimating the carbon stocks of mangrove forests in Hainan Island based on multisource remote sensing data and Google Earth Engine
LI Weiwei(), XUE Zhiyong, ZHU Jianhua(), TIAN Zhen
National Ocean Technology Center, Tianjin 300112, China
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摘要 碳储量变化是碳库功能的一个重要指标,有效准确评估碳储量对区域碳循环和碳源/汇研究、减缓气候变化和维持区域可持续发展具有重要意义。该文基于多时序遥感影像数据(Sentinel-1、Sentinel-2)和谷歌地球引擎(Google Earth Engine,GEE)云计算平台,匹配ICESat-2植被冠层的光子点数据反演红树林树高,通过大范围尺度的红树林“树高-生物量”模型反演生物量,最终得到海南岛红树林树高、地上生物量和碳储量估算结果,从而分析其分布及变化情况。结果显示: 海南岛红树林2016年、2019年和2022年平均高度分别为6.99 m,7.26 m和7.71 m,其中各区域红树林树高整体均呈上升趋势; 2016年、2019年和2022年海南岛红树林地上生物量总量分别为400 939.48 t,411 928.64 t和458 759.02 t,平均地上生物量分别为110.23 t/hm2,114.61 t/hm2和120.02 t/hm2,海南岛东北部的东寨港和八门湾区域地上生物量占总量的80%; 红树林植被碳储量的增长率在1%~4.45%之间,其中东寨港、八门湾的红树林植被碳储量增长率最大,分别为4.45%和3.17%。研究成果可为大范围尺度红树林碳储量核算提供基础数据和方法参考,作为海南岛红树林管理和保护的重要参数数据。
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关键词 红树林碳储量生物量Google Earth Engine海南岛    
Abstract

The change in carbon stocks is recognized as an important indicator of the carbon pool function. The effective, accurate assessment of carbon stocks is of great significance for research on regional carbon cycle and carbon source/sink dynamics, climate change mitigation, and regional sustainable development. Based on multi-time series remote sensing images (Sentinel-1 and Sentinel-2) and the Google Earth Engine (GEE) cloud computing platform, this study matched the photon point data of ICESat-2-derived vegetation canopy for the inversion of mangrove forest heights. Then, the inversion of the biomass of mangrove forests was conducted using a large-scale tree height-biomass model. Consequently, the heights, above-ground biomass, and carbon stocks of mangrove forests in Hainan Island were obtained, and their distribution and variations were further analyzed. The results indicate that in 2016, 2019, and 2022, mangrove forests in Hainan Island exhibited average heights of 6.99 m, 7.26 m, and 7.71 m, respectively, with an increasing trend observed in the highlights across all regions in the three years. Their total above-ground biomass was 400 939.48 t, 411 928.64 t, and 458 759.02 t, respectively, with average densities of 110.23 t/hm2, 114.61 t/hm2, and 120.02 t/hm2, respectively. The above-ground biomass of Dongzhai Port and the Bamenwan area, both located in the northeastern part of Hainan, accounted for about 80% of the total. The carbon stocks of mangrove forests exhibited rates of increase ranging from 1% to 4.45% over the three years, with the top two growth rates occurring in Dongzhai Port and the Bamenwan area, respectively (4.45% and 3.17%). The results of this study can provide foundational data and a methodological reference for assessing carbon stocks of large-scale mangrove forests and serve as important parameters for mangrove forest management and protection in Hainan Island, holding THE value of widespread applications.

Key wordsmangrove forest    carbon stock    biomass    Google Earth Engine    Hainan Island
收稿日期: 2023-12-04      出版日期: 2025-05-09
ZTFLH:  TP79  
  TP753  
基金资助:海南省重点研发计划资助项目“南海珊瑚礁空天地海一体化监测关键技术研究与应用示范”(ZDYF2023GXJS023)
通讯作者: 朱建华(1977-),男,硕士,研究员,主要从事定标检验与遥感应用研究。Email: besmile@263.net
作者简介: 李尉尉(1985-),女,硕士,工程师,主要从事海洋遥感应用研究。Email: rikki0909@163.com
引用本文:   
李尉尉, 薛志泳, 朱建华, 田震. 基于GEE平台多源遥感数据的海南岛红树林碳储量估算[J]. 自然资源遥感, 2025, 37(2): 220-227.
LI Weiwei, XUE Zhiyong, ZHU Jianhua, TIAN Zhen. Estimating the carbon stocks of mangrove forests in Hainan Island based on multisource remote sensing data and Google Earth Engine. Remote Sensing for Natural Resources, 2025, 37(2): 220-227.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023368      或      https://www.gtzyyg.com/CN/Y2025/V37/I2/220
Fig.1  研究区域示意图
Fig.2  技术路线图
Fig.3  反演植被高度结果精度评价
Fig.4  海南岛红树林主要分布区域2016年、2019年、2022年红树林树高分布
Fig.5  海南岛红树林主要分布区域2016年、2019年、2022年红树林地上生物量分布
区域 2016年 2019年 2022年
东寨港 199 271.30 219 478.22 258 811.84
八门湾 86 243.73 87 071.20 104 017.41
新英湾 37 282.54 33 981.76 39 778.56
花场湾 25 147.34 23 679.41 29 617.70
新盈港 23 761.44 21 411.70 27 759.74
Tab.1  海南岛红树林重点研究区域2016年、2019年和2022年地上生物量
区域 2016年 2019年 2022年 年均变化率/%
东寨港 99 635.65 109 739.11 129 405.92 4.45
八门湾 43 121.86 43 535.60 52 008.71 3.17
新英湾 18 641.27 16 990.88 19 889.28 1.09
花场湾 12 573.67 11 839.71 14 808.85 2.76
新盈港 11 880.72 10 705.85 13 879.87 2.62
Tab.2  海南岛红树林重点研究区域2016年、2019年、2022年植被碳储量变化
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