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

This dataset provides 3D ground displacement velocity estimates for the Jakarta city and metropolitan area derived from InSAR observations. The displacement vectors are derived using an internally constrained strapdown decomposition method, which estimates physically meaningful displacement components from ascending and descending InSAR Line-of-Sight (LoS) observations. The final distributed 3D velocity field is connected to the Sunda Plate Fixed Frame through a uniform datum connection based on GNSS data. 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 restricted to the transversal-normal (TN) plane. The method allows for the incorporation of prior uncertainty in the local frame orientation, enabling propagation of this uncertainty to the final displacement estimates. This supports cartographic visualization using vector fields with confidence ellipses, enhancing interpretability. See [2] for a full description of the method.This repository provides the 3D displacement velocity estimates associated with groundwater exploitation–induced land subsidence in the Jakarta region. Each data point represents a Region of Uniform Motion (RUM), corresponding to a 450 × 450 m grid cell. For each RUM, the dataset provides a set of coordinates, where for each coordinate nine parameters are provided: East displacement velocity estimate, `east` [mm/yr]North displacement velocity estimate, `north` [mm/yr]Up displacement velocity estimate, `up` [mm/yr]Variance of the east component, `var_east` [(mm/yr)²]Variance of the north component, `var_north` [(mm/yr)²]Variance of the up component, `var_up` [(mm/yr)²]Covariance between east and north, `covar_en` [(mm/yr)²]Covariance between east and up, `covar_eu` [(mm/yr)²]Covariance between north and up, `covar_nu` [(mm/yr)²] The dataset is stored as CSV and PKL files. In addition, the JSON file provides 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. The data can be visualized using the code available in the GitHub repository.[1] Brouwer, Wietske S., and Ramon F. Hanssen. "Estimating three-dimensional displacements with InSAR: the strapdown approach." Journal of Geodesy 98.12 (2024): 110. [2] Brouwer, Wietske S., and Ramon F. Hanssen. "3D surface displacement estimation over the Groningen gas field, the Netherlands." Submitted to: Netherlands Journal of Geoscience.