Autogeoreferencing

Autogeoreferencing is an automated method used in geographic information systems (GIS) and remote sensing to assign geographic coordinates to raster data, such as satellite or drone imagery, or scanned maps, without manual input to mark ground control points. The objective is to produce a georeferenced dataset that aligns with a defined coordinate reference system, enabling precise overlay with other spatial data and reliable spatial analysis.

Autogeoreferencing can rely on sensor metadata, such as rational polynomial coefficients (RPCs), or on automatic feature-based matching to a reference dataset. Popular approaches extract distinctive image features and seek correspondences with reference data using detectors like SIFT, SURF, or ORB, followed by estimating a transformation model (affine, projective, or higher-order) through optimization to minimize misfit. Some workflows integrate elevation or terrain data to improve geolocation in 3D space.

Accuracy is reported as an error metric such as RMSE in ground units. The quality of autogeoreferencing depends on image quality, sensor geometry, scene content, and the fidelity of the reference data. While it offers speed and reproducibility, its results can be less reliable in homogeneous areas with few distinctive features or in scenes with significant distortion if not properly modeled.

Applications include converting historical maps to GIS-ready layers, aligning drone or satellite imagery for change detection, and providing initial alignments for further refinement. Limitations include potential misregistrations, the need for carefully chosen transformation models, and occasional requirement for manual verification to attain high-accuracy geolocation.