Method for determining weight matrix for resolving threedimensional surface deformation using MultiLOS DInSAR technology Abstract   Threedimensional surface deformation is resolved using deformations obtained from multiple line of sight differential interferometry synthetic aperture radar (multiLOS DInSAR). However, the random model is susceptible to both accidental errors (such as errors due to noises) and system errors (such as orbital errors and topographic errors). To solve this problem, we present a weightdetermining method based on highprecision global positioning system (GPS) observations. Specifically, the precision of multiLOS DInSAR deformation observations is evaluated based on highprecision GPS deformation observations from the same period. Then, by considering the influence of system errors and accidental errors on the deformation of a pixel observed by multiLOS DInSAR, a combined fitting model associated with the positions and elevations of a pixel is built. Finally, the precision of deformations from multiLOS DInSAR is evaluated pixelbypixel by using the built model. As a result, the weights of observations in the model for resolving threedimensional surface deformation using multiLOS DInSAR can be determined. We verify the feasibility and precision of the weightdetermining method through a simulation experiment and a real data experiment, respectively. The verification results show that the proposed weightdetermining method based on highprecision GPS observations provides higher reliability for the resolved threedimensional surface deformation.

The Extraction of Ocean Tidal Loading from ASAR Differential Interferograms The spatiotemporal crustal nontectonic deformation caused by ocean tidal loading (OTL) can reach the centimeters scale in coastal land areas. The temporal variation of the site OTL displacements can be estimated by the global positioning system (GPS) technique, but its spatial variation needs to be further determined. In this paper, in order to analyze the spatial characteristics of the OTL displacements, we propose a multiscale decomposition method based on signal spatial characteristics to derive the OTL displacements from differential interferometric synthetic aperture radar (DInSAR) measurements. The method was tested using longterm advanced synthetic aperture radar (ASAR) data and GPS reference site data from the Los Angeles Basin in the United States, and we compared the results with the FES2014b tide model. The experimental results showed that the spatial function of the OTL displacements in an ASAR image can be represented as a higherorder polynomial function, and the spatial trends of the OTL displacements determined by the InSAR and the GPS techniques are basically consistent with the FES2014b tide model. The rootmeansquare errors of the differences between the spatial OTL displacements of these two methods and the FES2014b tide model are less than 0.8 mm. The results indicate that the OTL displacement extracted from InSAR data can accurately reflect the spatial characteristics of the OTL effect, which will help to improve the spatial resolution and accuracy of the OTL displacement in coastal areas.