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Remote Sens. 2019, 11(8), 894;

Theoretical Evaluation of Water Cloud Model Vegetation Parameters

Department of Geoinformation Engineering, Sejong University, Seoul 05006, Korea
Avionics RADAR Team, Hanwha Systems, Yongin-si, Gyeonggi-do, 17121, Korea
Author to whom correspondence should be addressed.
Received: 12 March 2019 / Revised: 7 April 2019 / Accepted: 9 April 2019 / Published: 12 April 2019
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
PDF [4206 KB, uploaded 12 April 2019]


The advantage of implementing the Water Cloud Model (WCM) is in being able to express complex scattering characteristics in a vegetated area with simple bulk vegetation descriptors. However, there has been a lack of understanding or consensus about the optimal set of vegetation descriptors. In this paper, the original and improved expressions of WCM are evaluated and the optimal vegetation descriptors are presented by examining the relationship between WCM vegetation parameters and the theoretical scattering model predictions. In addition, the condition-specific regression relationship between bulk vegetation descriptors and theoretical scattering and attenuation coefficients, expressed by the A and B parameters in the WCM, is analyzed in relation to the shape, size, and orientation distribution of the scatterer. Furthermore, the influence of radar observation conditions on the parameterization of the WCM is presented. The results show that the particle moisture content and the vegetation water content can be the optimal vegetation descriptors, denoted by the V1 and V2 variables in the WCM, respectively.
Keywords: SAR; vegetation scattering; water cloud model; soil moisture SAR; vegetation scattering; water cloud model; soil moisture
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Park, S.-E.; Jung, Y.T.; Cho, J.-H.; Moon, H.; Han, S.-H. Theoretical Evaluation of Water Cloud Model Vegetation Parameters. Remote Sens. 2019, 11, 894.

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