文献类型：期刊文献

中文题名：森林地上生物量的极化干涉SAR相干层析估测方法

英文题名：Forest Above-Ground Biomass Estimation Using Polarimetric Interferometry SAR Coherence Tomography

作者：李文梅[1] 陈尔学[1] 李增元[1] 赵磊[1]

第一作者：李文梅

机构：[1]中国林业科学研究院资源信息研究所林业遥感与信息技术实验室,北京100091

年份：2014

卷号：50

期号：2

起止页码：70-77

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：国家973计划项目(2013CB733404);863计划重点项目(2011AA120402)

语种：中文

中文关键词：极化相干层析;森林地上生物量;林分层析测量高;polarization;coherence;tomography;(PCT)

外文关键词：polarization coherence tomography （PCT）; forest above ground biomass; TomH in forest stand scale; polarimetric interferometry synthetic aperture radar

分类号：S757

摘要：应用机载单基线极化干涉SAR(Pol-InSAR)数据,基于极化相干层析(PCT)技术提出了一种反演森林地上生物量的新方法。首先采用单基线PCT提取每个像元的森林相对反射率垂直分布,然后按林分统计得到森林平均相对反射率垂直分布;再次对森林平均相对反射率垂直分布进行高斯函数拟合,提取林分层析测量高;最后以通过样地调查统计得到的20个林分的地上生物量为参考数据,采用交叉验证方法建立和评价基于层析测量树高的地上生物量估测模型,并与基于经典三阶段反演的林分优势木平均树高估测地上生物量的方法进行对比。结果表明:基于层析测量高的反演模型决定系数(R2)为0.822,均方根误差(RMSE)为53.14 t·hm-2,比基于经典三阶段反演算法的林分地上生物量估测方法具有更高的估测精度。该反演方法简单易行,能够有效提高森林地上生物量估测精度,在该研究区未出现信号饱和现象。
A new forest method for retrieving above ground biomass （AGB） was developed based on Polarization Coherence Tomograhpy （PCT） technique using airborne single baseline polarimetric interferometric SAR （Pol-InSAR） data. First of all, forest vertical distribution of relative reflectivity （FVDRR） for each pixel was extracted using single baseline PCT technique. Then, the mean FVDRR for each forest stand was calculated from the FVDRR of all the pixels inside each corresponding forest stand. Thirdly, the mean FVDRR of each stand was fitted to Gaussion function and the forest canopy height, here defined as tomography canopy height （TomH）, was extracted. Finally, regression analysis method and cross-validation approach were applied to build and assess forest AGB estimation model based on TomH using 20 in-situ forest stand AGB as reference. The result showed that the determination coefficient R2 was 0. 822 and RMSE was 53.14 t·hm-2 of the forest AGB retrieval model based on TomH. ToraH had a higher correlation with in-situ forest AGB than that of three-stage inversed forest height. This approach is simple and easy to implement, and it can improve the accuracy of forest AGB estimation. Moreover, there was no signal saturation in our study area.