Ice Typical Features Retrieval In Liaodong Bay Based On Microwave Remote Sensing Imagery

Operational ice remote sensing mainly include the monitoring of sea ice type, sea iceextent and sea-ice thickness. In this paper, high spatial resolution spaceborne SAR, airbornemicrowave radiometer (ABMR), and spaceborne microwave radiometer images are used toobserve the ice in Liaodong Bay, and then to retrieve sea ice type, sea ice thickness and iceedge.As for ice type retrieval, we first analyzed the ice detection capability of ENVISATASAR AP data (Alternating Polarisation mode) at different polarizations. Then we studied theelectromagnetic characteristics of different ice types of Liaodong Bay in SAR images. Theresults indicate that SAR can distinguish coastal fast-land ice, level ice and hummocked ice.But in some cases, new ice cannot be distinguished from open water in SAR image.According to the analysis, we used the PCNN neural network to segment SAR images of seaice, and then the segmentation of SAR images can be used in ice classification. Thesimplified and improved PCNN neural network can retrieve the information of ice type in asmall area of sea ice. The effects of the parameters of PCNN on the classification results wereanalyzed;the scopes of the parameters were set. A semi-automatic classificationinterpretation system of sea ice SAR images was built based on the PCNN neural network.In order to determine the ice thickness by using ABMR, we deduced the non-coherent seatheoretical models of ice thickness, and obtained the expression of the high order brighttemperature for the first time. We analyzed the theoretical models and pointed out that ABMRcan only detect a certain range of ice thickness. The maximal detectable ice thickness isdependent on wavelength and precision of the ABMR, while the minimum detectable icethickness is only associated with the wavelength of it. On this basis, the suitable detectableice thicknesses of several ABMR in common use in China were calculated. Moreover, someModel factors and the application Scope of the model were analyzed.In the fourth chapter of this paper, we applied the PSSM algorithm to AMSR data for thefirst time to extract Liaodong Bay sea ice edge. Using that algorithm, we can obtain the iceedge of Liaodong Bay with a spatial resolution of 2.5km and a repetition period of 1 day. Theresults are compared with those obtained from Jason-1 altimeter data and SAR images, andthe results show that it is valid to use the PSSM algorithm to retrieve ice edge in LiaodongBay.The final chapter summarizes this paper and predicts the further tasks for theimprovement of this study.