MARMIT: A multilayer radiative transfer model of soil reflectance to estimate surface soil moisture content in the solar domain (400-2500 nm)
MARMIT: A multilayer radiative transfer model of soil reflectance to estimate surface soil moisture content in the solar domain (400-2500 nm)
复制标题
DOI：
10.1016/j.rse.2018.07.031
复制
发表时间：
2018-11-01
影响因子：
13.5
通讯作者：
Tian, J.
中科院分区：
文献类型：
--
作者：
Bablet, A.;Vu, P. V. H.;Tian, J.
已知地表土壤水分含量（SMC）会影响太阳光谱所有波长处的土壤反射率。因此，许多半经验方法的目的是推断SMC从土壤反射率，但很少依赖于物理为基础的模型。本文提出了一种基于质量的土壤反射率多层辐射传输模型MARMIT（Multiple Radiation Transfer Model of Soil Reflectivity），并给出了一种由土壤反射率光谱估算土壤反射率的方法MARMIT forSMC。该模型将湿润土壤描述为覆盖有水薄膜的干燥土壤。它用于评估从文献中收集的七个独立实验室数据集的SMC。需要一个学习阶段来将水膜的厚度与SMC联系起来。为此，S形函数，其参数与土壤的物理和化学性质，如孔隙度，粒度和矿物组成，是适合的。如果学习步骤是逐土应用的，则可以以良好的精度（RMSE近似为3%）推断SMC。SMC和水厚度之间的联系实际上取决于土壤质地和化学成分。如果将土壤划分为类，并且如果将学习阶段应用于类，则RMSE略微增加至5%。最后，MARMITforSMC提供比任何其他现有的半经验或基于物理的方法更低的RMSE。
Surface soil moisture content (SMC) is known to impact soil reflectance at all wavelengths of the solar spectrum. As a consequence, many semi-empirical methods aim at inferring SMC from soil reflectance, but very few rely on physically-based models. This article presents a multilayer radiative transfer model of soil reflectance called MARMIT (multilayer radiative transfer model of soil reflectance) as a function of SMC given on a mass basis and a method called MARMITforSMC to estimate it from soil reflectance spectra. This model depicts a wet soil as a dry soil covered with a thin film of water. It is used to assess SMC over seven independent laboratory datasets gathered from the literature. A learning phase is required to link the thickness of the water film with the SMC. For that purpose, a sigmoid function, the parameters of which are related to soil physical and chemical properties such as porosity, grain size and mineralogy composition, is fitted. SMC can be inferred with good accuracy (RMSE approximate to 3%) if the learning step is applied soil by soil. The link between SMC and water thickness actually depends on soil texture and chemical composition. If the soils are divided into classes and if the learning phase is applied to a class, the RMSE slightly increases up to 5%. Finally, MARMITforSMC provides lower RMSE than any other existing semi-empirical or physically-based method.