Multi-temporal optical VHR image fusion for Land-Cover mapping

Land-Cover databases (LC-DB) are very useful for environmental purposes, but need to be semantically detailed to provide robust and instructive spatial indicators. Moreover, remote sensed data allow to cover large areas with high temporal resolution. Such multi-temporal data are very useful input to discriminate LC classes. Nevertheless, automatic fusion method need to be developed to provide high quality LC-DB. In this paper, several fusion methods are proposed and introduced in an existing Land-Cover mapping framework. Those fusion methods allow to take advantage of multi-temporal data. Those methods are compared, and assessed thanks to a very high resolution LC-DB.