A novel interpolation method for InSAR atmospheric wet delay correction

The accuracy and capability of Differential interferometric Synthetic Aperture Radar (DInSAR) depends on the phase errors. In particular, errors associated with Atmospheric Wet Delay (AWD) should be reduced to ensure reliable results from the interferometric process. This paper addresses a new method for AWD estimation based on MEdium Resolution Imaging Spectrometer (MERIS) water vapor image which is used as an auxiliary data to correct AWD effects on ENVIronment SATellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) interferogram. We also explore the possibility of using MERIS data under cloudy conditions and we propose a novel method for the interpolation of water vapor in the presence of clouds using a hybrid technique we name Three Dimensional Inverse Distance Weighted (3D-IDW). It is shown that the proposed method succeeds to provide a quite realistic prediction of MERIS water vapor distribution on cloudy area. Obtained results show that 3D-IDW method succeeds to estimate IWV for each cloudy pixel with RMSE not exceeding 0.094 g/cm(2) over area masked by 90% of cloud. The proposed method was tested on Mitidja region (north central Algeria), using a couple of Advanced Synthetic Aperture Radar (ASAR) and MERIS images on the 65 descending track. The results demonstrates an improvement of 15% in the standard deviation of interferogram after ADW correction. Finally, the obtained surface deformation reveals the presence of subsiding districts which may be linked to seasonal water level fluctuation and overdrafting groundwater confirming the results of previous study.