基于光学梯形模型(OPTRAM)的土壤水分和水体遥感研究

IF 5.7 Q1 ENVIRONMENTAL SCIENCES Science of Remote Sensing Pub Date : 2023-10-11 DOI:10.1016/j.srs.2023.100105
Morteza Sadeghi , Neda Mohamadzadeh , Lan Liang , Uditha Bandara , Marcellus M. Caldas , Tyler Hatch
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摘要

近年来,光学梯形模型(OPTRAM)作为利用光学卫星数据进行地表土壤水分高分辨率制图的一种手段得到了广泛的应用。在本文中,我们提出了一种新的OPTRAM变体,它不仅可以绘制土壤湿度,还可以绘制湖泊和河流等水体。利用实验室实验数据和Landsat-8反射率观测对提出的变体进行了测试。结果表明,新的OPTRAM变体在分离陆地和水像元方面比原始变体具有更高的技巧。此外,新变体对模型参数的敏感性较低,因此对用户的依赖性较低。为了定量地检验模型的用户依赖性,我们基于加州的Landsat-8卫星图像分析了OPTRAM土壤湿度,我们在一个合理的范围内改变了模型参数。两组参数之间的R2相关性在原始变异的0.47-0.52和新变异的0.67-0.76之间。由于一些OPTRAM参数可能非常不确定,特别是在潮湿地区,降低的灵敏度保证了在参数选择范围内更一致的土壤湿度估计。
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A new variant of the optical trapezoid model (OPTRAM) for remote sensing of soil moisture and water bodies

Over the past few years, the Optical Trapezoid Model (OPTRAM) has been widely used as a means for high-resolution mapping of surface soil moisture using optical satellite data. In this paper, we propose a new variant of OPTRAM that can map not only soil moisture, but also water bodies such as lakes and rivers. The proposed variant was tested using laboratory experimental data as well as Landsat-8 reflectance observations. Results showed the new OPTRAM variant has greater skill than the original variant in separating land and water pixels. In addition, the new variant showed less sensitivity to the model parameters, and hence, is less user dependent. To quantitatively examine the user-dependency of the model, we analyzed OPTRAM soil moisture based on Landsat-8 satellite images in California, where we varied the model parameters in a plausible range. The correlations of the resulting maps in terms of R2 between two largely different sets of parameters were found in the range of 0.47-0.52 for the original variant and 0.67-0.76 for the new variant. Because some OPTRAM parameters can be quite uncertain, particularly in wet regions, the reduced sensitivity promises more consistent soil moisture estimates across the range of parameter choices.

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