There are three popular methods to understand the land subsidence: leveling, Global Navigation Satellite System, and Interferometric Synthetic Aperture Radar (InSAR) analysis using SAR images. While both leveling and the Global Navigation Satellite System can measure the amount of land subsidence only at specific points, InSAR analysis can observe a wide area in short time intervals. In terms of accuracy, however, InSAR analysis is inferior to leveling; centimeter/millimeter order (InSAR/PSInSAR analysis) vs. millimeter order (leveling). Among all observation errors in InSAR analysis, a tropospheric delay error has a large adverse effect on the measurement. It is difficult to suppress this tropospheric delay error by conventional methods because they try to remove error at each pixel independently in an InSAR image. However, geometrically-neighboring regions/pixels should be naturally correlated. Our proposed method employs such a neighboring relationship in a convolutional neural network (CNN). Our CNN is designed to improve InSAR analysis by mutually incorporating the InSAR image and the tropospheric delay error, which are estimated by any conventional methods. Experimental results demonstrate that our proposed method can reduce the mean error compared with a conventional method: from 10.3mm to 6.80mm. INDEX TERMS PSInSAR analysis, Tropospheric delay, Deep convolutional neural networks, Multi-modal data fusion I. INTRODUCTIONThe ground always shifts vertically and horizontally. One of the critical shifts is a land subsidence. Once the land subsidence occurs, the ground hardly returns to its original state. It is essential to understand the land subsidence and to take a countermeasure against it as early as possible, because it may cause huge negative impacts on our lives such as building collapse and lifeline damages.We have three popular methods to measure the land subsidence: leveling, Global Navigation Satellite Systems (GNSSs), and Interferometric Synthetic Aperture Radar (In-SAR) analysis using SAR images. The functional properties of these three methods are summarized in Table 1. For leveling, a huge human effort is required in order to measure a wide area. The GNSSs including Global Positioning System (GPS), GLObal NAvigation Satellite System (GLONASS), Galileo, and Quasi-Zenith Satellite System (QZSS) measure the crustal alteration so that ground-installation devices receive signals transmitted from artificial satellites. SAR is a form of high spatial-resolution micro-wave radar. SAR is transmitted from a satellite towards the ground surface. Its 21 reflection intensity and phase are captured by the same satel-22 lite. From the phase shift between those captured at different 23 capturing times, we can compute the ground subsidence. As 24 summarized in Table 1, while both the leveling and GNSS 25 (1) require special measurement devices and (2) measure the 26 amount of the land subsidence only at specific points, InSAR 27 analysis can observe a wide area in short time intervals with 28 no ground-installat...

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