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林业科学 ›› 2017, Vol. 53 ›› Issue (11): 85-93.doi: 10.11707/j.1001-7488.20171110

• 论文与研究报告 • 上一篇    下一篇

森林地上生物量的多基线InSAR层析估测方法

李兰, 陈尔学, 李增元, 任冲, 赵磊, 谷鑫志   

  1. 中国林业科学研究院资源信息研究所 国家林业局遥感与信息技术重点开放性实验室 北京 100091
  • 收稿日期:2016-03-01 修回日期:2017-01-15 出版日期:2017-11-25 发布日期:2017-12-13
  • 基金资助:
    国家973计划"复杂地表遥感信息动态分析与建模"(2013CB733404)。

Forest Above-Ground Biomass Estimation Based on Multi-Baseline InSAR Tomography

Li Lan, Chen Erxue, Li Zengyuan, Ren Chong, Zhao Lei, Gu Xinzhi   

  1. Key Laboratory of Remote Sensing and Information Technology, State Forestry Administration Research Institute of Forest Resource Information Techniques, CAF Beijing 100091
  • Received:2016-03-01 Revised:2017-01-15 Online:2017-11-25 Published:2017-12-13

摘要: [目的]发展一种森林地上生物量(AGB)的多基线干涉合成孔径雷达(InSAR)层析估测方法,解决热带雨林森林AGB遥感估测常规方法的信号"饱和"问题,为区域及全球森林生物量估测和碳储量研究提供关键技术支撑。[方法]以法属圭亚那巴拉库(Paracou)热带雨林为研究对象,以TropiSAR 2009 P-波段多基线机载SAR数据和85块样地调查数据为主要数据源。首先,根据HH极化层析相对反射率的三维分布信息提取林下地表高度,对HV极化多基线InSAR数据进行地形相位去除;然后,对HV极化多基线InSAR数据进行三维成像,并对其进行地理编码,得到地理坐标空间层析相对反射率的三维分布信息;最后,利用样地调查数据,分析不同高度处层析相对反射率与森林AGB的相关性,进而建立以层析相对反射率为输入特征的森林AGB估测模型,同时采用留一交叉验证法(LOOCV)对其估测模型进行精度评价。[结果]20 m以下各高度处层析相对反射率与森林AGB呈不同程度的负相关关系,以5 m高度处层析相对反射率与森林AGB的负相关性最强(相关系数达到-0.58);20 m以上各高度处层析相对反射率与森林AGB呈不同程度的正相关关系,以25 m高度处层析相对反射率与森林AGB的正相关性最强(相关系数达到0.63)。采用5 m高度处层析相对反射率构建模型的估测精度为88.44%,均方根误差为49.85 t·hm-2(相对均方根误差为13.56%);采用25 m高度处层析相对反射率构建模型的估测精度为88.82%,均方根误差为47.30 t·hm-2(相对均方根误差为12.87%);同时采用5 m和25 m高度处层析相对反射率联合构建模型的估测结果最优,估测精度为89.17%,均方根误差为46.45 t·hm-2(相对均方根误差为12.63%)。[结论]通过多基线InSAR层析技术得到的层析相对反射率信息有效解决了热带雨林森林AGB遥感估测常规方法的信号"饱和"问题。采用5 m和25 m高度处层析相对反射率可反演得到高精度的森林AGB,表明多基线InSAR层析技术得到的特定高度处层析相对反射率对热带雨林森林AGB具有良好的指示作用;同时利用5 m和25 m高度处层析相对反射率进行联合估测可进一步提高森林AGB的估测精度,说明充分利用不同层次的森林垂直结构信息可进一步提高复杂森林空间结构条件下的森林AGB估测精度。

关键词: 多基线InSAR, 层析技术, 森林垂直结构, 森林地上生物量, 热带雨林

Abstract: [Objective] This paper developed a method of forest above-ground biomass(AGB) estimation based on the technology of multi-baseline InSAR tomography, aiming to solve the problem of saturation effect and support mapping global forest biomass.[Method] The experiments were carried out over the site of Paracou, French Guiana. The tropiSAR 2009 P-band multi-baseline airborne InSAR data and 85 forest plot investigation data were used as the key data sources. Firstly, three-dimension distribution information of the tomographic relative reflectivity for HH polarization was obtained. Accordingly, the ground elevation was retrieved, and the terrain topography was removed from HV polarization data. Secondly, three-dimension distribution information of the tomographic relative reflectivity for HV polarization was obtained and converted to ground geometry by geocoding. Finally, correlation analysis between in situ AGB measurements and the extracted tomographic relative reflectivity at different heights (5 m interval) were implemented. The forest AGB estimation model was built and assessed by leave-one-out cross-validation.[Result] Negative correlations were found for the layers of tomographic relative reflectivity at the height below 20 m, with the best correlation of -0.58 for the 5 m layer. Positive correlations were found for the layers of tomographic relative reflectivity at the height above 20 m, with the best correlation of 0.63 for the 25 m layer. The 5 m layer made the accuracy of the forest AGB estimation model to be on the order of 88.44% with RMSE of 49.85 t·hm-2 (RRMSE of 13.56%). The 25 m layer made the accuracy of the forest AGB estimation model to be on the order of 88.82% with RMSE of 47.30 t·hm-2 (RRMSE of 12.87%). The forest AGB estimation model could be refined by combining the 5 m layer and the 25 m layer, with the accuracy of 89.17% and RMSE of 46.45 t·hm-2 (RRMSE of 12.63%).[Conclusion] The saturation effect in tropical forest would be solved based on the technology of multi-baseline InSAR tomography. High-precision forest AGB could be retrieved either with the 5 m layer or with the 25 m layer, which demonstrated that tomographic relative reflectivity within forest was an effective indicator to forest AGB. The forest AGB estimation model could be refined by combining different layers, which demonstrated that making the best of the forest vertical structure information may further improve the accuracy of forest AGB estimation.

Key words: multi-baseline InSAR, tomography technology, forest vertical structure, forest above-ground biomass, tropical rainforest

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