Data of the four different test-sites on the Greenland ice sheet as measured by the NASA/JPL active microwave AIRSAR remote sensing system are analysed. Details of this multifrequency fully polarimetric airborne imaging radar system are given previously in chapters 1 and 2.
4.2.1 Multifrequency fully polarimetric imagery.
For each location on the Greenland ice sheet full polarimetric images at the three operating frequencies: P, L and C band are available. These images may be displayed as total power images (TP), or any polarization combination for the receive and transmit antennas can be simulated and the resulting polarimetric image is synthesized and displayed (for example: HH, VV, HV, VH, RR, LL or any other combination of polarimetric states). A review of the use of polarimetry and polarimetric theory may be found in chapters 1 and 2.
The polarimetric AIRSAR image data are displayed using the NASA/JPL MacMultiview andMacSigmaO_ll software (Norikane, 1990,1992).
The total power images for P, L and C bands for all four zones, and the P band images for the linear polarizations W and HH for each location are given in chapter 5.
These images are checked by eye to detect any unusual features: For example; the different frequency images (P, L and C band) of the same area may show different features, and so may the polarimetric images for each scene.
4.2.2 Radar response from measured data. 4.2.2.1 Numerical data.
The numerical data of the Greenland images are analysed using MacMultiview and MacSigmaO_ll software.
The MacMultiview program allows the 3D polarimetric response of a particular area of any displayed image to be determined and the response of the sampled area is plotted. The 3D response curves show the normalized co and cross polar power return as a function of the ellipticity and orientation of the incident wave (figure 2.4).
The MacSigmaO_l 1 program allows a statistical analysis of the data. Values of TP, HH, HV, VV power and HHVV* phase for any sampled area of any displayed image are calculated. Details of the necessary calculations to determine these values from the Stokes matrices of the measured data sets are given by Norikane (1990,1992).
4.2.2.2 Pow er values.
The return power for each image is determined using MacSigmaO_l 1. This program is used to calculate the power values for line averages at the near and far edge of the image and for intermediate positions to determine the variation of the return power with the incidence angle for each scene.
The difference in the return power for each image, for the three frequencies and the various polarization states, is analysed for each zone of the ice sheet.
The noise floor of the AIRSAR system is ~-40dB. Low power data can produce a misleading shape of polarimetric response as the output response is plotted on a
normalized scale. A small change in power for low power signals then causes a relatively large change in the shape of the response. In order to approach this problem of accurate representation of the measured data a minimum of 15dB difference signalmoise is required to ensure the signal strength, and a significant sample size is required. The accuracy of the results is proportional to 1/Vn from Noise theory, where n is the number of data takes, or number of individual elements in a sample. Taking a line average sample of data helps to overcome this problem for uniform, high power images.
The data sets analysed in this work are as supplied by JPL using the standard calibration for the campaign. Additional calibration work using data from the comer reflector array has not been included in this thesis as the results and data are not available. These data would, however, be useful for determining any polarization imbalance and for calculating the absolute value of return power.
The polarimetric nature of the return signal from each of the four zones is investigated. The measured polarization response is given as a normalized signal for each plot so the difference in the polarimetric content of each of the return signals for each zone may each be determined independent of the absolute power value.
4.2.2.3 Polarization response 3D plots.
The type of scattering behaviour of the different zones of the ice sheet is investigated using the 3D polarimetric response plots for each image. The information contained within these polarimetric response plots gives details of the dominant scattering mechanism (Freeman and Durden, 1992) as discussed in chapter 2. The physical mechanism for these types of scattering behaviour is shown in figure 2.5(i) and the typical polarimetric response plots (co and cross polar power) for direct scattering, double bounce and diffuse/ volume scattering are given in figure 2.5(ii).
The polarization response for each zone of the ice sheet is investigated and the variation of the measured polarization response with incidence angle, and with frequency is analysed for each scene. The measured polarization response is compared with theoretical values to explain the variation of the shape of the response with the change in the incidence angle of the radar.
4.2.2.4 Theoretical classification method.
The theoretical classification method using the polarimetric content of the return signal as described in chapter 3 (section 3.3) is applied to the measured data of the C233-1
AIRSAR image over the ablation zone. This image was measured by the active
polarimetric airborne imaging radar system during a previous campaign further down the Greenland ice sheet (August 1989). A copy of the total power image is given in chapter 5. This image shows distinct light and dark regions, with the dark regions indicating the position of melt pools on the surface of the ice sheet, and is therefore used in the
application of the classification method. The classification method is used to distinguish the different dielectric material of the ice sheet as imaged by the radar.
4.2.2.5 Position of subsurface ice layer.
The measured polarimetric P band AIRSAR data of the percolation zone is analysed and compared with the theoretical signal to infer the depth of a subsurface ice layer using the
method described in chapter 3 (section 3.3.4.3). The position of the subsurface layer predicted by the theoretical analysis of the measured polarimetric signal is compared with the actual values of the snowpack layers at the test site as measured by KJezek's field party (figure 4.2).
A line average of data from the measured image is taken from the line corresponding to that containing the 6th comer reflector marked 2KmE in the site map (figure 4.1) which contains the position of the snow pit marked 2KmE (figure 4.2). Information on the actual position along the line of the image of the snow pit as dug by the field party is not available, so the line average (of the same incidence angle) is used The measured values of HH and W polarization return power and VV-HH phase of the return polarimetric signal are used to give the measured data point on the power ratio vs. phase difference plot in chapter 5 (figure 5.11). This measured data point is then compared with the theoretical values for the simulated system of snow and ice layers to predict the depth of the surface layer of fim and hence the position of the subsurface ice layer. This is then compared with the measured snowpit data.
The standard deviation of the measured data point is calculated from the relative standard deviation of the data as given by the NASA/JPL MacSigmaO_l 1 software (Norikane,
1992). The relative standard deviation is a term used by JPL and equation 4.1 below shows the relationship with the more usual value of standard deviation.
4.2.2.6 Statistical analysis.
The relative standard deviation, G^eiadve» given by equation 4.1, where a is the standard deviation and m is the mean value (fractional value, not dBs).
( m + a ^ n . l a t i v e - ( ^ m
Equation 4.1: Standard deviation relationship (Norikane, JPL, 1992).
Error bars are plotted on the figures to show the 68.3% confidence interval (±1 standard deviation). Further work on the statistical analysis of the measured data is given with the results in chapter 5 and in Appendix A 1.6.