3D displacement velocity estimates associated with groundwater exploitation in Jakarta using satellite radar interferometry (2014–2025)

This dataset provides 3D ground displacement estimates for the Jakarta city and metropolitan area estimated from InSAR observations. The displacement vectors are derived using an internally constrained strapdown decomposition method, which estimates physically meaningful displacement components using ascending and descending InSAR Line-of-Sight (LoS) observations and connects the resulting 3D components to a Sunda Plate–fixed reference frame using GNSS data.<br>The strapdown approach enables so-called “3D-global / 2D-local” solutions by incorporating minimal but meaningful contextual information about the expected physical behavior and/or spatial geometry of the deformation field [1]. The method defines a local reference system with transversal, longitudinal, and normal (TLN) directions, with motion only occurring in the transversal-normal (TN) plane. The method allows for the incorporation of a prior uncertainty in the local frame orientation, enabling the propagation of this uncertainty to the final displacement estimates. This supports cartographic visualization using vector fields with confidence ellipses, enhancing interpretability. See for a full description of the method [2].<br>This repository provides the 3D displacement estimates associated with groundwater exploitation–induced land subsidence in the Jakarta region. The dataset includes a set of coordinates, where for each coordinate nine parameters are provided:<br>East displacement velocity estimate, east [mm/yr]North displacement velocity estimate, north [mm/yr]Up displacement velocity estimate, up [mm/yr]The variance of var_eastThe variance of var_northThe variance of var_upThe covariance between east and north, covar_enThe covariance between east and up, covar_euThe covariance between north and up, covar_nu<br>Each set of parameters in the dataset represents a single Region of Uniform Motion (RUM), which is a 450x450 m grid cell. The dataset is stored as a csv file. In addition, the JSON file provides the metadata related to this dataset. The GitHub repository provides an example script on how to read and plot the 3D velocity data including the error ellipses.<br>The data can be visualized using the link to the GitHub repository.[1] Brouwer, Wietske S., and Ramon F. Hanssen. "Estimating three-dimensional displacements with InSAR: the strapdown approach." <em>Journal of Geodesy</em> 98.12 (2024): 110.<br>[2] Brouwer, Wietske S., and Ramon F. Hanssen. "3D surface displacement estimation over the Groningen gas field, the Netherlands." Submitted to: <em>Netherlands Journal of Geoscience</em>.

本数据集提供雅加达城市及大都市区基于合成孔径雷达干涉测量（Interferometric Synthetic Aperture Radar, InSAR）观测反演得到的三维地表位移估算结果。位移矢量通过内部约束的捷联分解法求解，该方法利用升轨与降轨InSAR视线向（Line-of-Sight, LoS）观测数据，估算具备物理意义的位移分量，并结合全球导航卫星系统（GNSS）数据将所得三维位移分量约束至巽他板块固定参考框架。<br>该捷联分解法可通过引入少量但具备物理意义的形变场预期行为与/或空间几何的先验语境信息，实现所谓的"三维全局/二维局域"解[1]。该方法定义了包含横向、纵向与法向（TLN）三个方向的局域参考系，限定运动仅发生在横向-法向（TN）平面内。此外，该方法允许对局域参考系的取向引入先验不确定性，可将该不确定性传播至最终位移估算结果中，支持带置信椭圆的矢量场制图可视化，提升解译性。完整方法细节可参见文献[2]。<br>本仓库提供雅加达地区由地下水开采引发的地面沉降相关三维位移估算数据。数据集包含一系列坐标点，每个坐标点对应9项参数：东向位移速率估算值（单位：毫米/年，mm/yr）、北向位移速率估算值（单位：毫米/年，mm/yr）、垂向位移速率估算值（单位：毫米/年，mm/yr）、东向位移速率方差（var_east）、北向位移速率方差（var_north）、垂向位移速率方差（var_up）、东-北向位移速率协方差（covar_en）、东-垂向位移速率协方差（covar_eu）、北-垂向位移速率协方差（covar_nu）。<br>数据集中的每组参数对应一个单一均匀运动区域（Region of Uniform Motion, RUM），即450×450米的网格单元。数据集以逗号分隔值（CSV）文件存储，此外还附带JSON格式的元数据文件。本GitHub仓库提供了读取并绘制含误差椭圆的三维速度数据的示例脚本。数据可通过本GitHub仓库链接进行可视化。<br>[1] Brouwer, Wietske S. 与 Ramon F. Hanssen. 《利用InSAR估算三维位移：捷联分解法》，*Journal of Geodesy*，98卷12期（2024年）：110。<br>[2] Brouwer, Wietske S. 与 Ramon F. Hanssen. 《荷兰格罗宁根气田地表三维位移估算》，投稿于*Netherlands Journal of Geoscience*。