It is difficult to make an inventory of vertical profiles of forest structure parameters in field measurements.However,analysis and understanding of forest backscattering characteristics contribute to estimation and detection of forest vertical structure because of the close relationships between backscattering characteristics and structure parameters.The vertical structure function in the complex interferometric coherence definition,which represents the vertical variation of microwave scattering with the penetration depth at a point in the 2-D radar image and can be used to analyze the forest backscattering characteristics,can be reconstructed from polarization coherence tomography(PCT).Based on PCT,the paper analyzes the forest backscattering characteristics and explores the inherent relationship between the result of PCT and the forest structure parameters from numerical simulation of Random Volume over Ground model(RVoG),Polarimetric SAR interferometry(PolInSAR)simulation of forest scene and PolInSAR data at L-band of the test site Traunstein.Firstly,the effects of the extinction coefficient and surface-to-volume scattering ratio in RVoG model on vertical backscattering characteristics are analyzed by means of numerical simulation.Secondly,by applying PCT to L-band POLInSAR simulations of forest scene,different variations of vertical backscattering due to different extinction coefficients and the ratios of surface-to-volume scattering resulting from different polarizations,forest types and densities are displayed and analyzed.Then a concept of relative average backscattering intensity is presented,and the factors which affect its vertical distribution are also discussed.Preliminary results show that there is high sensitivity of the vertical distribution of forest relative average backscattering intensity to the polarization,forest type and density.Finally,based on repeat pass DLR E-SAR L-band airborne POLInSAR data,the capability of PCT technology for detection of forest layer,type and density is discussed. It is difficult to make an inventory of vertical profiles of forest structure parameters in field measurements. However, analysis and understanding of forest backscattering characteristics contribute to estimation and detection of forest vertical structure because of close relationship between backscattering characteristics and structure parameters. structure function in the complex interferometric coherence definition, which represents the vertical variation of microwave scattering with the penetration depth at a point in the 2-D radar image and can be used to analyze the forest backscattering characteristics, can be reconstructed from polarization coherence tomography ( PCT). Based on PCT, the paper analyzes the forest backscattering characteristics and explores the inherent relationship between the result of PCT and the forest structure parameters from numerical simulation of Random Volume over Ground model (RVoG), Polarimetric SAR interferometry (PolInSAR) simulation of forest scene and PolInSAR data at L-band of the test site Traunstein. Firstly, the effects of the extinction coefficient and surface-to-volume scattering ratio in RVoG model on vertical backscattering characteristics are analyzed by means of numerical simulation. Secondarily, by applying PCT to L-band POLInSAR simulations of forest scenes, different variations of vertical backscattering due to different extinction coefficients and the ratios of surface-to-volume scattering resulting from different polarizations, forest types and densities are displayed and analyzed. Now a concept of relative average backscattering intensity is presented, and the factors which affect its vertical distribution are also discussed. Preliminary results show that there is high sensitivity of the vertical distribution of forest relative average backscattering intensity to the polarization, forest type and density. Finally, based on repeat pass DLR E-SAR L-band airborne POLInSAR data, the capability of PCT technology for detectionof forest layer, type and density is discussed.