Integration of GPS and InSAR Data for Resolving 3‐Dimensional Crustal Deformation
Integration of GPS and InSAR Data for Resolving 3‐Dimensional Crustal Deformation
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DOI：
10.1029/2019ea001036
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发表时间：
2019-12
影响因子：
3.1
通讯作者：
Zheng‐Kang Shen;Zhen Liu
中科院分区：
文献类型：
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作者：
Zheng‐Kang Shen;Zhen Liu
我们开发了一种算法来集成GPS和干涉合成孔径雷达数据在地球表面的三维地壳形变场。该算法首先对离散GPS数据点进行插值，得到三维连续速度场，然后利用最小二乘法将其与干涉合成孔径雷达的视线（LOS）速度数据逐像素进行合成。我们的方法与以前的方法相比的优点是：1）通过平衡空间分辨率和解的稳定性之间的权衡，对GPS数据点进行最佳插值。2)针对GPS-干涉合成孔径雷达（InSAR）组合中GPS数据的权值问题，提出了一种新的GPS速度插值不确定度估计算法。3)对干涉合成孔径雷达视线速率数据的实际不确定性进行了估计，并将其作为GPS-干涉合成孔径雷达组合中干涉合成孔径雷达数据的权值。4)全局估计所有图像的干涉合成孔径雷达数据的斜坡和/或偏移，以最小化数据失配，特别是在数据重叠的区域。将该方法应用于南加州的真实的数据，表明该方法能够成功地从空间有限的GPS和尺寸有限的干涉合成孔径雷达数据中恢复三维连续形变场。形变场揭示了加州南部不同地区的退水引起的沉降和干旱引起的隆起。
We develop an algorithm to integrate GPS and InSAR data for a 3‐dimensional crustal deformation field at the Earth's surface. In the algorithm discrete GPS data points are interpolated to obtain a 3‐dimensional continuous velocity field, which is then combined with the InSAR line‐of‐sight (LOS) velocity data pixel by pixel using the least‐squares method. Advantages of our method over previous ones are that: 1) The GPS data points are optimally interpolated by balancing a trade‐off between spatial resolution and solution stability. 2) A new algorithm is developed to estimate realistic uncertainties for the interpolated GPS velocities, to be used as weights for GPS data in GPS‐InSAR combination. 3) Realistic uncertainties for the InSAR LOS rate data are estimated and used as weights for InSAR data in GPS‐InSAR combination. 4) The ramps and/or offsets of the InSAR data are globally estimated for all the images to minimize data misfit, particularly at regions where the data overlaps. Application of this method to real data from southern California shows its capability of successfully restoring 3‐dimensional continuous deformation field from spatially limited GPS and dimensionally limited InSAR data. The deformation field reveals water withdrawal induced subsidence and drought caused uplift at various regions in southern California.