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基于高时空分辨率融合影像的红树林总初级生产力遥感估算
引用本文:杨昊翔,张丽,闫敏,林光辉. 基于高时空分辨率融合影像的红树林总初级生产力遥感估算[J]. 遥感技术与应用, 2021, 36(2): 453-462. DOI: 10.11873/j.issn.1004-0323.2021.2.0453
作者姓名:杨昊翔  张丽  闫敏  林光辉
作者单位:1.中国科学院空天信息创新研究院 数字地球重点实验室,北京 100094;2.中国科学院大学,北京 100049;3.清华大学地球系统科学系暨东亚迁徙鸟类与栖息地生态学教育部野外观测研究站,北京 100084
基金项目:国家自然科学基金面上项目(41771392);国家自然科学基金重点项目(30930017);国家重点基础研究发展计划(973)项目(2013CB956600)
摘    要:红树林是热带与亚热带地区潮间带具备高植被生产力和高储碳量的滨海湿地植被类型,在维系全球碳平衡过程中扮演着重要的角色。目前通量站点尺度的红树林生产力研究已取得了一定的进展,然而由于受到遥感影像时空分辨率和红树林斑块分布的限制,区域尺度红树林总初级生产力(Gross Primary Production,GPP)估算仍少有涉及。基于影像融合算法获得的高时空分辨率植被指数数据集,结合红树林通量观测数据开展光能利用率模型的参数估计和模型验证研究,实现了区域尺度的红树林GPP估算,获取了一套2012年广东省高桥红树林GPP高时空分辨率数据集。数据验证得到的决定系数R2 = 0.64,较现有的MOD17A2和GLASS产品GPP估算精度提高了48.9%。实验结果显示:高桥红树林最大光能利用率为3.07 g C MJ-1,研究区内全年GPP均值为1 915.4 g C m-2 a-1。红树林季节平均GPP夏、秋季大于春、冬季。该方法和估算数据可为区域尺度红树林生产力研究和红树林保护提供高精度数据支持。

关 键 词:红树林  总初级生产力  遥感影像融合  光能利用率模型  
收稿时间:2019-12-18

Remote Sensing of Mangrove Gross Primary Production Estimation based on High Spatiotemporal Resolution Fused Images
Haoxiang Yang,Li Zhang,Min Yan,Guanghui Lin. Remote Sensing of Mangrove Gross Primary Production Estimation based on High Spatiotemporal Resolution Fused Images[J]. Remote Sensing Technology and Application, 2021, 36(2): 453-462. DOI: 10.11873/j.issn.1004-0323.2021.2.0453
Authors:Haoxiang Yang  Li Zhang  Min Yan  Guanghui Lin
Abstract:Mangrove forests are characterized as high productivity and high carbon storage coastal vegetation inhabited in the intertidal zone of tropical and subtropical region. They play a significant role in global carbon balance. Previous studies have made achievements in estimating and analyzing mangrove primary production on eddy flux tower site scale, however, rare experiments were conducted on the estimation of mangrove Gross Primary Production(GPP) on regional scale due to the limited remote sensing image resolution and patchy distribution of mangrove. In this study, we first combined high spatiotemporal resolution vegetation index datasets produced by data fusion technique and eddy flux data to calibrate and validate light use efficiency model, and then applied the model to estimate mangrove GPP in our study region. Based on our method, a high spatiotemporal resolution dataset of mangrove GPP in Gaoqiao, Guangdong province in 2012 was established. The overall accuracy of our dataset (R2=0.64) outperformed MOD17A2 and GLASS GPP product with the increase of 48.9%. Experiments results showed that the maximum light use efficiency of mangrove in Gaoqiao is 3.07 g C MJ-1, and annually average GPP is 1 915.4 g C m-2 a -1 in our study site. Besides, seasonally average GPP of Gaoqiao mangrove is higher in summer and autumn than spring and winter. Our method and dataset can be served for the regional-scale mangrove production research, as well as are effective support for mangrove protection.
Keywords:Mangrove  Gross primary production  Remote sensing image fusion  Light use efficiency model  
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