Forest Vertical Structure Parameters Estimation Using Polarimetric Interferometric Tomography SAR

With the development of forest remote sensing technology, Synthetic Aperture Radar(SAR) obtains a lot of important research results in forest resource classification and biologicalparameters extraction with its unique advantage. For the past few years, Polarimetric SyntheticAperture Readar (PolSAR), Interferometric Synthetic Aperture Radar (InSAR), PolarimetricInterferometric Synthetic Aperture Radar (Pol-InSAR) and Tomographic Synthetic ApertureRadar (TomSAR) have been the important means for forest scattering mechnicham separation,understory topography extraction, forest height estimation, forest above ground biomass (AGB)estimation and backscattering power profile extraction and so on. However, forest researchmainly concentrates on forest height, volume and forest AGB estimation based onbackscattering coefficients, InSAR coherence and Pol-InSAR, there is few studies on verticaldistribution of radar backscattered power using TomoSAR. Vertical distribution of radarbackscattered power in forest is the response of vertical distribution of scatterers, and it ishelpful for understanding radar scattering mechanism of complex forest vertical structrue. Itmake possible to inverse forest3-dimension(3D) information, and it helps to improve theestimation accuracy of forest height, volume, forest AGB and other forest structure parameters.TomSAR is the major technique for forest vertical structure information extraction, it containsthree tomographic approach: Polarization Coherence Tomogragphy (PCT), Multi-baselineInSAR Tomography (MBInSAR Tomo) and Multi-baseline Pol-InSAR Tomography(MBPol-InSAR Tomo). Hence, we used these three tomographic SAR techniques to extractvertical distributions of backscattering power and analyze the applications of these information.There are three main research contents:(1) Forest vertical structure information extraction using single baseline PCTWe proposed a new method for forest AGB estimaion using object-based PCT techniqueby applying L-band single baseline Pol-InSAR data, and the data was acquired by E-SAR in Traunstein test site in Germany in2003. Based on the study of Luo (Luo, Chen et al.2011), wecontinued to improve the forest AGB estimation model, applied Pol-InSAR separation andobject-orientated segmentation techniques to make the forest coverage areas divide into severalhomogenous polygons, and extended the forest AGB estimation model to the polygons.Tomography canopy height (TomH) is the most important parameter for forest AGB estimaion,and all the parameters were extracted from vertical structure profile. TomH corresponds to thelargest relative reflectivity in canopy, and it co uld represent forest AGB in some degree. It isdiscovered that vertical structure profile in forest stand level relates with forest AGB or volume,and this result is agreed with that of Luo(2011) and Cloude(2009). Backward step-wiseregression method was used to establish estmation model using profile parameters and in-situforest AGB in forest stand scale. The coefficient of determination R2is0.883, Root MeanSquare Error (RMSE) is39.98tons/hm2, and relative RMSE (RRMSE) is13.15%.The results indicate that TomH extracted from profile produced by PCT has less accuracythan forest height estimated using classical three-stage inversion approach, but it has higherprecision in forest AGB estimation. Parameters extracted from vertical profiles could describethe overall geometric characteristics of vertical structure profile and some of them were used tobuild forest AGB inversion model. It is feasible to parametrize vertical structure profile andused these parameters to estimate forest AGB by multivariant analysis method and the modelcould be extended to other regions outside of the measured forest stands. It is worth noting thatestimated forest AGB does not saturate using the approach we proposed. The estimation modelstill valid even the biomass up to500tons/hm2.(2) Forest vertical structure information extraction by MBInSAR TomoThe airborne L-and P-band multi-baseline InSAR data was applied to extract verticaldistribution of backscattering power, and the data was acquired by E-SAR in Raminstorp testtest in Swenden from March to May in2007BioSAR campaign with repeat track mode. Forestheight was estimated using empirical method, the feasibility of forest AGB estimation usingbackscattering power was analyzed, and the impacts of baseline numbers, temporal baseline and wavelength on forest vertical structure information extraction were analyzed. It isdiscovered that R2is0.65,0.55,0.34, RMSE is2.35m,3.27m,5.13m and correlationcoeddicient (R) is0.80,0.74,0.58between the estimated forest height using HH, HV andpolarimetric MBInSAR Tomo and Lidar H80, respectively.The results show that Capon method could accurately obtain the target singal in high noiseenvironment, but is has less noise immunity, and it is suitable for forest vertical structure andcanopy height information extraction. Baseline numbers, temporal baseline and wavelength hassome influences on forest vertical structure extraction, respectively. For the P-band data, morebaselines extracte more forest vertical structure information and31days temporal baseline haslittle effect on P-band data and the distribution of backscattered power scattered, meanwhilebackscatterd power obtained using shorter temporal baseline concentrates on ground. Thebackscattering power spectrum extracted using L-band data has strong randomness, it coulddescribe the variant of vertical structure but could not effectively identify the surface andcanopy, and that extracted from P-band data is more stable, it could distinguish surface andcanopy features, which aids to forest vertical structure extraction. The precision of forest heightestimated using P-band HH polarimetric MBInSAR Tomo is able to meet the demand of forestapplication in some degree. However, extracted backscattered power at certain heighte ofP-band HH/HV/VV MBInSAR Tomo contributes little to forest AGB estimation in coniferousforest.(3) Forest vertical structure information extraction by MBPol-InSAR TomoThe data is the same with that of (2) besides it contains polarimetric information, that ismean multi-baseline Pol-InSAR data was used. MBPol-InSAR Tomo technique was applied toextract vertical distribution of backscattering power, polarization angle, estimate forestheight and analyze the feasibility of backscattering power for forest AGB estimation.Meanwhile, the effects of baseline number, temporal baseline and wavelength on forest verticalstructure information extraction using MBPol-InSAR Tomo were analyzed. It is discoveredthat, R2is0.53, R is0.73, and RMSE is4.08m between the esimated forest height using MBPol-InSAR Tomo and Lidar H80. But the backscattering power at certain height contributeslittle to forest AGB estimation.The results show that similar with MBInSAR Tomo, baseline number, temporal baselineand wavelength have effects on forest vertical structure information extraction usingMBPol-InSAR Tomo technique. The precision of forest height estimated using MBPol-InSARTomo is not better than that from MBInSAR Tomo. Meanwhile, the introduction ofpolarization information basically has no contribution on forest AGB estimation in coniferousforest. Polarization angle is the new inverted parameters for MBPol-InSAR Tomocompared with MBInSAR Tomo, it could describe vertical variations of backscatteringmechanism in forest.