Dataset
Deformation, Strains, and Velocities for the Tibetan Plateau from Sentinel-1 InSAR, GNSS, and Levelling Data, version 1
Abstract
This dataset provides velocity and strain rate fields for the Tibetan Plateau derived from Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and levelling data. Interferograms in GeoTIFF format at ~100 m resolution are available from the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics - Looking Inside the Continents from Space InSAR (COMET-LiCSAR) portal (https://comet.nerc.ac.uk/comet-lics-portal/). Using the Looking Inside the Continents from Space with Small Baseline Subset (LiCSBAS) approach, line-of-sight displacement time series and average velocities at ~1 km resolution are inverted, applying corrections for troposphere, ionosphere, Earth tides, and plate motions. Also compiling GNSS velocities and levelling observations from published studies. Following the velmap methodology, a unified coarse 3D velocity field is obtained that fits the GNSS, levelling, and InSAR data. From this, mosaics of ascending and descending line-of-sight velocities in a Eurasia reference frame. Inverting pixel-by-pixel for the east-west and vertical velocities directly from the referenced line-of-sight velocities, using the north–south velocities from the coarse 3D velocity model as a constraint. Strain and rotation rates are calculated from the horizontal gradients of the median-filtered east-west velocities at InSAR resolution and the north-south velocities from the coarse velocity model. Further details are provided in Wright et al. (2025, Science).
The directory overview for this dataset are given below:
ENU_vels/
East-west, north-south, and vertical velocity fields, along with their associated uncertainties.
georeferenced_los_vels/
Line-of-sight (LOS) velocities in a Eurasia-fixed reference frame defined by GNSS
GNSS_levelling_data/
Compiled GNSS velocities and levelling rates from published studies.
LiCSBAS_los_vels/
Original LOS velocities and displacement time series derived from LiCSBAS processing.
strain_rates/
Components of the horizontal velocity gradient tensor, second invariant, maximum shear, dilatation, and vorticity.
velmap_strain_rates/
Strain rates calculated from velmap.
velmap_vels/
Coarse 3D velocity model derived from velmap.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). |
| Data Quality: |
Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).
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| File Format: |
These data are provided in GeoTiff format.
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Related Documents
Process overview
Instrument/Platform pairings
| Sentinel 1 Synthetic Aperture Radar (SAR) | Deployed on: Sentinel 1A |
Instrument/Platform pairings
| Sentinel 1 Synthetic Aperture Radar (SAR) | Deployed on: Sentinel 1B |
Computation Element: 1
| Title | Computation for Deformation, Strains, and Velocities for the Tibetan Plateau |
| Abstract | Approximately 44,500 Sentinel-1 SAR acquisitions were processed to generate around 341,400 interferograms at ~100 m resolution using the automated COMET-LiCSAR system. The Tibetan Plateau was divided into 127 ascending and 114 descending frames (each approximately 250 km wide), forming short-baseline interferometric networks with additional 6- and 12-month pairs to reduce phase bias. Using LiCSBAS, line-of-sight displacement time series and average velocities at ~1 km resolution were estimated. Corrections were applied for tropospheric, ionospheric, and solid Earth tidal effects. Velocity uncertainties were flattened via semi-variogram analysis, and Eurasian plate motion was subtracted from all frames. A total of 18,203 GNSS velocities and 6,607 levelling rates were compiled from 131 studies published since 2013. The dataset was refined by removing outliers, aligning studies via Euler poles, eliminating outdated or duplicate entries, and merging collocated measurements. To construct a unified coarse velocity model integrating GNSS, levelling, and InSAR data, the velmap approach was followed. This involved inverting for 3D velocities at each node of a triangular mesh spaced by ~0.2° in longitude and latitude, along with frame-specific reference frame adjustment parameters and linear-with-height atmospheric correction terms. The reference frame adjustment parameters consisted of a second-order polynomial surface, and regularization was applied using Laplacian smoothing. East-west and vertical velocities were derived from georeferenced mosaics of ascending and descending line-of-sight velocities, using coarse north-south velocities as constraints. Horizontal strain and rotation rates were calculated from velocity gradients, with spherical corrections applied. A 150 km median filter was applied to east-west velocities to balance resolution and noise. Further details are available in Wright et al. (2025, Science). |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
| Output Description | None |
| Output Description | None |
- var_id: z
- long_name: GDAL Band Number 1
- var_id: lat
- var_id: lon
- var_id: z
- long_name: z
Co-ordinate Variables
Temporal Range
2016-01-01T00:00:00
2024-12-31T23:59:59
Geographic Extent
45.0000° |
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73.5000° |
112.0000° |
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20.0000° |