Geometric Calibration of High-Resolution Satellite Imagery

Geometric calibration is the process of correcting systematic distortions and aligning the pixels of high-resolution satellite sensors with true ground positions. It ensures that each image element corresponds accurately to its geographic location, which is essential for mapping, change detection, urban planning and environmental monitoring. The calibration workflow typically involves constructing a rigorous imaging model that accounts for the sensor’s interior orientation (focal length, principal point and lens distortion), exterior orientation (sensor position and attitude) and scanning effects. Ground control points and digital elevation models are used to estimate and validate these parameters. Modern approaches also address platform jitter, inter-chip alignment in multichip arrays and non-linear scanning errors, achieving sub-metre to sub-pixel accuracy. As satellite constellations proliferate, robust geometric calibration underpins the interoperability of data from diverse sensors and supports precise time-series analyses at a global scale.

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Geometric Calibration of High-Resolution Satellite Imagery publication trend

The graph below shows the total number of articles in geometric calibration of high-resolution satellite imagery across all publications each year (not limited to Nature Index journals).

Technical terms

Geometric calibration: The procedure to correct systematic sensor distortions and align image pixels with true ground coordinates.

Exterior orientation parameters (EOPs): The position and attitude (roll, pitch and yaw) of the sensor platform relative to the Earth.

Interior orientation parameters (IOPs): The intrinsic characteristics of the imaging sensor such as focal length, principal point offset and lens distortion.

Ground control points (GCPs): Precisely surveyed points on the Earth’s surface used to anchor images to real-world coordinates.

Digital elevation model (DEM): A gridded representation of terrain heights used to orthorectify imagery and correct relief displacement.

Rational function model (RFM): A mathematical mapping using ratios of polynomials to relate image coordinates to ground coordinates.

References

1. In-Orbit Geometric Calibration for Long-Linear-Array and Wide-Swath Whisk-Broom TIS of SDGSAT-1. IEEE Transactions on Geoscience and Remote Sensing (2023).
2. On-Orbit Geometric Calibration and Performance Validation of the GaoFen-14 Stereo Mapping Satellite. Remote Sensing (2023).
3. Impact of UAV-Derived RTK/PPK Products on Geometric Correction of VHR Satellite Imagery. Drones (2025).