Volume XL-7/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W1, 29-32, 2013
https://doi.org/10.5194/isprsarchives-XL-7-W1-29-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W1, 29-32, 2013
https://doi.org/10.5194/isprsarchives-XL-7-W1-29-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  12 Jul 2013

12 Jul 2013

A ROBUST PCT METHOD BASED ON COMPLEX LEAST SQUARES ADJUSTMENT METHOD

F. Haiqiang, Z. Jianjun, W. Changcheng, X. Qinghua, and Z. Rong F. Haiqiang et al.
  • Department of Survey Engineering and Geomatics, Central South University, Changsha 410083, Hunan, China

Keywords: Complex Least Squares, Polarimetric interferometric SAR (POLInSAR), Polarization Coherence Tomography (PCT), Vegetation height inversion

Abstract. Polarization Coherence Tomography (PCT) method has the good performance in deriving the vegetation vertical structure. However, Errors caused by temporal decorrelation and vegetation height and ground phase always propagate to the data analysis and contaminate the results. In order to overcome this disadvantage, we exploit Complex Least Squares Adjustment Method to compute vegetation height and ground phase based on Random Volume over Ground and Volume Temporal Decorrelation (RVoG + VTD) model. By the fusion of different polarimetric InSAR data, we can use more observations to obtain more robust estimations of temporal decorrelation and vegetation height, and then, we introduce them into PCT to acquire more accurate vegetation vertical structure. Finally the new approach is validated on E-SAR data of Oberpfaffenhofen, Germany. The results demonstrate that the robust method can greatly improve accusation of vegetation vertical structure.