Novel Approach for Generalizing the Process Chain of Optical Satellite Images Based on Knowledge Capitalisation

Abstract

Optical remote sensing from satellites such as SPOT, Landsat, Sentinel2, Terra Modis, offers exceptional solutions for monitoring the earth’s surface. Indeed, these satellites deliver multi-source, multi-date images. These are Bigdata, voluminous, heterogeneous and their treatment are not only complex but also require a lot of time. Studies have been carried out on the formalization of experimental protocols in satellite image processing. Those propose automated processing chains. But, these solutions are specific and their reuse are not possible for other cases. Our reflection allows us to propose a new approach for generalizing the optical satellite image processing chains. This approach respects standards in knowledge capitalization. The objective is to ensure the interoperability to the use of optical satellite images. Metamodels for the generalization of processing chains, a method of execution, generalization rules and implementation prototypes have been developed. These results are obtained through theoretical analyses and also experiments on the processing of multidate, multisource optical satellite images applied in multisectoral domains. Thus, this research solves today’s interrogability problem in the processing of satellite images optical.