首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >COSMO SKYMED AO PROJECTS -SOIL MOISTURE DETECTION FOR VEGETATION FIELDS BASED ON A MODIFIED WATER-CLOUD MODEL USING COSMO-SKYMED SAR DATA
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COSMO SKYMED AO PROJECTS -SOIL MOISTURE DETECTION FOR VEGETATION FIELDS BASED ON A MODIFIED WATER-CLOUD MODEL USING COSMO-SKYMED SAR DATA

机译:COSMO涉及使用COSMO-SKEDMED SAR数据的基于改进的水云模型的植被领域的水分检测

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In this study, we developed a soil moisture retrieval technique for vegetation fields using a modified water-cloud model. The water-cloud model has been a typical algorithm used to analyze scattering from vegetation fields for a long time, because it is simple to be used for retrieving a variety of information such as soil moisture and vegetation water mass. However, its accuracy has been questionable because the water-cloud model contains lots of approximations in the process of simplification. To improve the accuracy of the algorithm, we modified the water-cloud model with the estimation of parameters using a radiative transfer model. Soil moisture is retrieved from SAR images by the modified water-cloud model for vegetation fields and compared with in-situ measured ground truth data.
机译:在这项研究中,我们使用改进的水云模型开发了一种用于植被领域的土壤湿度检索技术。水云模型一直是一种典型的算法,用于分析长期从植被领域的散射,因为它很容易用于检索各种信息,如土壤水分和植被水量。然而,其准确性是可疑的,因为水云模型在简化过程中包含大量近似。为了提高算法的准确性,我们使用辐射转移模型估计参数估计水云模型。通过修改的植被领域的修改水云模型从SAR图像中检索土壤水分,与原位测量的地面真理数据相比。

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