Effective and Universal Pre-Processing for Multi-Angle CHRIS/PROBA Images

Abstract

Compared with traditional nadir observations, multi-angle hyperspectral remote sensing can obtain more spatial and spectral information and improve the inversion precision of structure information on the Earth’s surface. However, processing multi-angle remote-sensing images presents new challenges. Owing to the multi-angle sensors used to obtain multi-angle images, there are major differences in the spatial and spectral information between each angle in these images. Data from the Compact High-resolution Imaging Spectrometer (CHRIS) on Project for On-Board Autonomy (PROBA) should be pre-processed to extract the BRDF (Bidirectional Reflectance Distribution Functions). Given the limitations of the pre-processing software currently available for CHRIS/PROBA images, and the lack of metadata and auxiliary origin schedules, some CHRIS multi-angle images cannot be pre-processed correctly. In the study, to promote the application of multi-angle data, a formula for calculating key parameters according to in-orbit geometric imaging relationships is derived to design a multi-angle image process flow including image rollovers, bad-line repairs, orthorectification and atmospheric corrections accounting for terrain effects. Test results indicate that the pre-processing method can quickly and effectively recover multi-angle hyperspectral information and obtain spectral characteristics of multi-angle observations.