A linear physically-based model for remote sensing of soil moisture using short wave infrared bands
A linear physically-based model for remote sensing of soil moisture using short wave infrared bands
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DOI：
10.1016/j.rse.2015.04.007
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发表时间：
2015-07-01
影响因子：
13.5
通讯作者：
Philpot, William D.
中科院分区：
文献类型：
--
作者：
Sadeghi, Morteza;Jones, Scott B.;Philpot, William D.
卫星遥感技术的进步提供了各种技术，用于估算表层土壤含水量，这是许多环境研究中的一个关键变量。光学方法对于遥感土壤湿度特别有价值，因为反射的太阳辐射是卫星可获得的最强的无源信号，因此在光学波长上的观测能够提供高空间分辨率的数据。由于遥感器不直接测量土壤含水量，必须推导出描述测量信号与地表水含量之间联系的数学算法。在这里，我们提出了一个物理为基础的土壤水分反演模型在太阳域（350-2500 nm），是基于Kubelka-Munk双通量辐射传输理论。该模型的目的是描述漫反射从一个均匀的，光学厚，吸收和散射介质。该理论表明，在短波红外波段（如Landsat和MODIS卫星的波段7）的转换反射率和土壤含水量之间的线性关系，提供了一个易于使用的算法，在这些波段。利用实验室实测的不同土壤光谱反射率数据对模型的精度进行了检验和初步验证。利用光学卫星数据进一步研究这一模型在大规模应用方面的潜力和挑战仍然是一个正在进行的研究课题。(C)2015 Elsevier Inc. All rights reserved.
Technological advances in satellite remote sensing have offered a variety of techniques for estimating surface soil water content as a key variable in numerous environmental studies. Optical methods are particularly valuable for remote sensing of soil moisture since reflected solar radiation is the strongest passive signal available to satellites and thus observations at optical wavelengths are capable of providing high spatial resolution data. Since remote sensors do not measure soil water content directly, mathematical algorithms that describe the connection between the measured signal and surface water content must be derived. Here, we present a physically-based soil moisture retrieval model in the solar domain (350-2500 nm) that is based on the Kubelka-Munk two-flux radiative transfer theory. The model is designed to describe diffuse reflectance from a uniform, optically thick, absorbing and scattering medium. The theory suggests a linear relationship between a transformed reflectance and soil water content in the short wave infrared bands (e.g. band 7 of Landsat and MODIS satellites) providing an easy-to-use algorithm in these bands. Accuracy of this model was tested and preliminarily verified using laboratory-measured spectral reflectance data of different soils. Further studies on potentials and challenges of this model for large-scale application using optical satellites data remain a topic of ongoing research. (C) 2015 Elsevier Inc. All rights reserved.