Vegetation Canopy Height Retrieval Using L1 and L5 Airborne GNSS-R
Vegetation Canopy Height Retrieval Using L1 and L5 Airborne GNSS-R
复制标题
利用L1和L5机载GNSS-R卫星反演植被冠层高度
DOI：
10.1109/lgrs.2021.3131263
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发表时间：
2022-01-01
影响因子：
4.8
通讯作者：
Monerris, A.
中科院分区：
文献类型：
--
作者：
Munoz-Martin, J. F.;Pascual, D.;Monerris, A.
植被冠层高度（CH）是与森林结构相关的重要遥感参数之一，它与森林生物量和碳储量有关。全球导航卫星系统反射计已证明能够使用L1 C/A信号从空间（20-65公里）以中等分辨率检索植被信息。在这项研究中，将机载微波干涉反射仪GNSS-R仪器在L1和L5处检索的数据与空间分辨率为30米的全球森林CH产品进行了比较。本文分析了在两个波段上测量的波形（WF），以及波形宽度和反射率值与CH产品的相关性。一个神经网络算法用于检索，示出的反射率和波形宽度的组合允许估计CH信息在一个非常高的分辨率，与均方根误差（RMSE）为4.25和4.07米，分别在L1和L5，这是一个错误约14%的实际CH。
Vegetation canopy height (CH) is one of the important remote-sensing parameters related to forests' structure, and it can be related to the biomass and the carbon stock. Global navigation satellite system-reflectometry (GNSS-R) has proved capable to retrieve vegetation information at a moderate resolution from space (20-65 km) using L1 C/A signals. In this study, data retrieved by the airborne microwave interferometric reflectometer (MIR) GNSS-R instrument at L1 and L5 are compared to the Global Forest CH product, with a spatial resolution of 30 m. This work analyzes the waveforms (WFs) measured at both bands, and the correlation of the waveform width and the reflectivity values to the CH product. A neural network algorithm is used for the retrieval, showing that the combination of the reflectivity and the waveform width allows to estimate the CH information at a very high resolution, with a root-mean-square error (RMSE) of 4.25 and 4.07 m at L1 and L5, respectively, which is an error about 14% of the actual CH.