In this article, we present a multipolarimetric estimation approach for two model-based vegetation structure parameters (shape ${A}_{P}$ and orientation distribution ${\psi }$ of the main canopy elements). The approach is based on a reduced observation set of three incoherent (no phase information) polarimetric backscatter intensities ( $| {S}_{\mathrm{ HH}} |^{2}$ , $| {S}_{\mathrm{ HV}} |^{2}$ , and $| {S}_{\mathrm{ VV}} |^{2}$ ) combined with a two-parameter ( ${A}_{P}$ and ${\psi }$ ) discrete scatterer model of vegetation. The objective is to understand whether this confined set of observations contains enough information to estimate the two vegetation structure parameters from the L-band radar signals. In order to disentangle soil and vegetation scattering influences on these signals and ultimately perform a vegetation-only retrieval of vegetation shape ${A}_{P}$ and orientation distribution ${\psi }$ , we use the subpixel spatial heterogeneity expressed by the covariation of co- and cross-polarized backscatter ${\Gamma }_{{{\mathrm{PP-PQ}}}}$ of the neighboring cells and assume it is indicative for the amount of a vegetation-only co-to-cross-polarized backscatter ratio ${\mu }_{{{\mathrm{PP-PQ}}}}$ . The ratio-based retrieval approach enables a relative (no absolute backscatter) estimation of the vegetation structure parameters which is more robust compared to retrievals with absolute terms. The application of the developed algorithm on global L-band Soil Moisture Active Passive (SMAP) radar data acquired from April to July 2015 indicates the potential and limitations of estimating these two parameters when no fully polarimetric data are available. A focus study on six different regions of interest, spanning land cover from barren land to tropical rainforest, shows a steady increase in orientation distribution toward randomly oriented volumes and a continuous decrease in shape arriving at dipoles for tropical vegetation. A comparison with independent data sets of vegetation height and above-ground biomass confirms this consistent and meaningful retrieval of ${A}_{P}$ and ${\psi }$ . The retrieved shapes and orientation distributions represent the main vegetation elements matching the literature results from model-based decompositions of fully polarimetric L-band data at the SMAP spatial resolution. Based on our findings, ${A}_{P}$ and ${\psi }$ can be directly applied for parameterizing the vegetation scattering component of model-based polarimetric decompositions. This should facilitate decomposition into ground and vegetation scattering components and improve the retrieval of soil parameters (moisture and roughness) under vegetation.

中文翻译：

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根据SMAP雷达强度观测值估算植被结构参数

在本文中，我们针对基于模型的两个植被结构参数（形状 $ {A} _ {P} $ 和方向分布 $ {\ psi} $ 主篷元素）。该方法基于三个非相干（无相位信息）极化背向散射强度（ $ | {S} _ {\ mathrm {HH}} | ^ {2} $ ， $ | {S} _ {\ mathrm {HV}} | ^ {2} $ 和 $ | {S} _ {\ mathrm {VV}} | ^ {2} $ ）与两个参数（ $ {A} _ {P} $ 和 $ {\ psi} $ ）植被的离散散射模型。目的是了解这组狭窄的观测值是否包含足够的信息，以根据L波段雷达信号估算两个植被结构参数。为了消除土壤和植被散射对这些信号的影响，并最终执行仅植被恢复的植被形状 $ {A} _ {P} $ 和方向分布 $ {\ psi} $ ，我们使用由共极化和交叉极化背向散射的协方差表示的亚像素空间异质性 $ {\ Gamma} _ {{{\ mathrm {PP-PQ}}}} $ 并假设它指示了仅植被共同极化交叉散射的反向散射比的数量 $ {\ mu} _ {{{\ mathrm {PP-PQ}}}} $ 。基于比率的检索方法可以对植被结构参数进行相对（无绝对反向散射）估计，与使用绝对项进行检索相比，该估计更加可靠。所开发算法在2015年4月至2015年7月获取的全球L波段土壤水分主动无源（SMAP）雷达数据中的应用表明，在没有完全极化数据的情况下，估算这两个参数的潜力和局限性。一项针对六个不同感兴趣区域的重点研究涵盖了从荒芜土地到热带雨林的土地覆盖，显示定向分布向着随机定向的体积稳定增加，并且到达热带植被偶极子的形状不断减小。 $ {A} _ {P} $ 和 $ {\ psi} $ 。检索到的形状和方向分布代表与植被文献相符的主要植被要素，这些文献是基于SMAP空间分辨率的全极化L波段数据基于模型的分解得出的。根据我们的发现， $ {A} _ {P} $ 和 $ {\ psi} $ 可以直接用于参数化基于模型的极化分解的植被散射分量。这应有助于分解成地面和植被的散射成分，并改善植被下土壤参数（水分和粗糙度）的获取。