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Modeling radar backscattering of complex terrain at the landscape scale for retrieving forest structure parameters

机译:在景观尺度上对复杂地形的雷达反向散射进行建模,以获取森林结构参数

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The forest aboveground biomass and its dynamics are essential for researches of carbon cycling. The estimation of forest aboveground biomass is an important topic in the application of remote sensing. However, the estimation accuracy is limited by the lack of forest structures. Recent progresses over the past decade in the estimation of forest biomass from remote sensing data was mainly due to the success in the extraction of related forest structure parameters[1]. For example, LiDAR data is widely used in the estimation of forest biomass at local scales because it can directly measure the vertical structure of forests [2, 3]. Polarimetric Interferometric SAR (PolInSAR) is a another promising technique for the estimation of forest height and biomass which employs the dependence of penetration depth of SAR on polarization [4]. However, spaceborne LiDAR system cannot acquire wall-to-wall data because it mainly worked by point sampling while airborne LiDAR system only worked on at local scaled due to its cost. The P-band PolInSAR system onboard European BIOMASS satellite which is suitable for retrieval of forest biomass is still under construction and scheduled to be launched around 2020 by European space agency (ESA).
机译:森林地上生物量及其动力学对碳循环研究至关重要。森林地上生物量的估计是遥感应用中的重要课题。但是,由于缺乏森林结构,估计准确性受到限制。过去十年来从遥感数据估算森林生物量方面的最新进展主要是由于成功提取了相关的森林结构参数[1]。例如,LiDAR数据由于可以直接测量森林的垂直结构而被广泛用于局部尺度的森林生物量估算[2,3]。极化干涉SAR(PolInSAR)是另一种有前途的估计森林高度和生物量的技术,它利用了SAR穿透深度对极化的依赖性[4]。但是,由于机载LiDAR系统主要通过点采样进行工作,因此机载LiDAR系统无法获取墙对墙数据,而机载LiDAR系统由于其成本而只能在局部范围内工作。适用于森林生物量回收的欧洲BIOMASS卫星上的P波段PolInSAR系统仍在建设中,计划由欧洲航天局(ESA)于2020年左右发射。

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