Automated Georeferencing of Optical Satellite Data with Integrated Sensor Model Improvement

The geometric processing of remotely sensed image data is of the key issues in data interpretation, added value generation, and multi-source data integration. optical satellite data can be orthorectified without use of Ground Control Points (GCP) to absolute geometric of some meters up to several hundred meters on the satellite mission, there is still a need to the geometric accuracy by using GCP. The manual of GCP is time consuming work, and leads, for larger data sets with hundreds of satellite , to a cost and time ineffective workload. To overcome shortcomings, an autonomous processing chain georeference and orthorectify optical satellite data is which uses reference data and digital elevation to generate GCP and to improve sensor model (namely for rigorous and universal sensor ) for a series of optical Earth observation satellite . Using a restrictive blunder removal strategy, the procedure leads to high quality orthorectified or at least to a geometrically consistent data set in of relative accuracy. The geometric processing chain is validated using SPOT-4 HRVIR, SPOT-5 HRG, IRS-P6 LISS III, and ALOS AVNIR-2 optical sensor data, for which a huge amount of satellite data (3,200 scenes) has been processed. Relative and absolute geometric accuracies of approximately half the pixel size (linear Root Mean Square Error) are achieved.