Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval Over Irrigated Grasslands
Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval Over Irrigated Grasslands
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DOI：
10.1109/jstars.2015.2464698
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发表时间：
2016-03-01
影响因子：
5.5
通讯作者：
Fayad, Ibrahim
中科院分区：
文献类型：
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作者：
Baghdadi, Nicolas N.;El Hajj, Mohamad;Fayad, Ibrahim
本研究的目的是开发一种方法来估计土壤水分和植被参数灌溉草地耦合C波段极化合成孔径雷达（SAR）和光学数据。利用从雷达卫星2号和陆地卫星7/8号获得的大量卫星图像数据集和现场测量结果评估了几种反演配置的相关性。神经网络（NN）反演技术。这项研究的方法是利用雷达卫星2号和陆地卫星7/8号图像，研究综合利用新的合成孔径雷达传感器SENTINEL-1和新的光学传感器LANDSAT-8和SENTINEL-2的新数据的可能性。首先，SAR极化（单，双，和全极化配置）和归一化差分植被指数（NDVI）从光学数据计算的土壤水分和植被参数的估计误差的影响进行了研究。其次，分析了极化参数（香农熵和泡利分量）对反演技术的影响。最后，还测试了使用原位测量的吸收光合有效辐射的分数（FAPAR）和绿色植被覆盖的分数（FCover）的配置。结果表明，HH极化是SAR极化最相关的土壤水分估计。土壤湿度估计值的均方根误差（RMSE）约为6vol. %即使是在茂密的草原上也能得到。使用原位FAPAR和FCover仅改善了叶面积指数（LAI）的估计，RMSE约为0.37 m（2）/m（2）。极化参数的使用并没有改善土壤水分和植被参数的估计。对于生物量（BIO）和植被含水量（VWC）的估算，当BIO和VWC值分别低于2和1.5 kg/m（2）时，获得了良好的结果（BIO的RMSE为0.38 kg/m（2），VWC的RMSE为0.32 kg/m（2））。此外，观察到BIO和VWC分别高于2和1.5 kg/m2的高度低估（BIO估计值的偏差为-0.65 kg/m2，VWC估计值的偏差为-0.49 kg/m2）。最后，植被高度（VEH）的估计进行了RMSE为13.45厘米。
The objective of this study was to develop an approach for estimating soil moisture and vegetation parameters in irrigated grasslands by coupling C-band polarimetric synthetic aperture radar (SAR) and optical data. A huge data set of satellite images acquired from RADARSAT-2 and LANDSAT-7/8, and in situ measurements were used to assess the relevance of several inversion configurations. A neural network (NN) inversion technique was used. The approach for this study was to use RADARSAT-2 and LANDSAT-7/8 images to investigate the potential for the combined use of new data from the new SAR sensor SENTINEL-1 and the new optical sensors LANDSAT-8 and SENTINEL-2. First, the impact of SAR polarization (mono-, dual-, and full-polarizations configurations) and the normalized difference vegetation index (NDVI) calculated from optical data for the estimation error of soil moisture and vegetation parameters was studied. Next, the effect of some polarimetric parameters [Shannon entropy (SE) and Pauli components] on the inversion technique was also analyzed. Finally, configurations using in situ measurements of the fraction of absorbed photosynthetically active radiation (FAPAR) and the fraction of green vegetation cover (FCover) were also tested. The results showed that HH polarization is the SAR polarization most relevant to soil moisture estimates. A root-mean-square error (RMSE) for soil moisture estimates of approximately 6 vol.% was obtained even for dense grassland cover. The use of in situ FAPAR and FCover only improved the estimate of the leaf area index (LAI) with an RMSE of approximately 0.37 m(2)/m(2). The use of polarimetric parameters did not improve the estimate of soil moisture and vegetation parameters. Good results were obtained for the biomass (BIO) and vegetation water content (VWC) estimates for BIO and VWC values lower than 2 and 1.5 kg/m(2), respectively (RMSE is of 0.38 kg/m(2) for BIO and 0.32 kg/m(2) for VWC). In addition, a high underestimate was observed for BIO and VWC higher than 2 and 1.5 kg/m(2), respectively, (a bias of -0.65 kg/m(2) on BIO estimates and -0.49 kg/m(2) on VWC estimates). Finally, the estimation of vegetation height (VEH) was carried out with an RMSE of 13.45 cm.