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Bayesian inversion technique of olive tree biophysical properties using Sentinel-2 images

机译:利用Sentinel-2图像进行橄榄树生物物理特性的贝叶斯反演技术

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In this paper, we study the estimation of olive tree biophysical properties driven by Sentinel-2 (S2) image inversion. The latter is based on the forward/backward radiative transfer model (RTM). The forward step is done simulating the DART model on a realistic olive tree mock-up, whereas the backward is done based on a coupling between the Look UP Table (LUT) and the Markov Chain Monte Carlo (MCMC). The parameters Leaf area index (LAI), chlorophyll (Cab) water (Cw) contents and mesophyll structure (N) are therefore derived. Soil reflectance is pre-calculated based on an upscaling of the S2 resolution to 3m using Planet images. Moreover to obtain a significant representation of the local heterogeneity, S2 are upscaled to the 80m resolution. The estimation results are promising.
机译:在本文中,我们研究了由Sentinel-2(S2)图像反转驱动的橄榄树生物物理特性的估计。后者基于前/后辐射传递模型(RTM)。前进步骤是在真实的橄榄树模型上模拟DART模型,而后退步骤是基于查找表(LUT)与马尔可夫链蒙特卡洛(MCMC)之间的耦合完成的。因此得出参数叶面积指数(LAI),叶绿素(Cab)水(Cw)含量和叶肉结构(N)。土壤反射率是根据使用行星图像将S2分辨率提高到3m预先计算的。此外,为了获得局部异质性的显着表示,将S2放大到80m分辨率。估计结果很有希望。

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