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.

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].

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:

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_east
The variance of var_north
The variance of var_up
The covariance between east and north, covar_en
The covariance between east and up, covar_eu
The covariance between north and up, covar_nu

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.

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." 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.