Jordi Inglada, Emmanuel Christophe
Going from raw remote sensing images to value added maps can be seen as an information production work-flow which consists of several steps. One has to deal with geometric and radiometric corrections of all data sources, use the appropriate algorithms in order to capture the essential information for the application at hand and put all this together in order to build a product (the map) which is useful for the final users.
All these steps need efficient tools (software) and it is very difficult to build good processing work-flows without understanding the main issues related to the different steps involved.
This tutorial will present in detail the different steps of a general remote sensing image processing chain through a hands-on approach. The free and open source software Monteverdi (user friendly application based on the Orfeo Toolbox) will be used for the work.
Jordi Inglada received the Telecommunications engineer degree in 1997 from both Universitat Politècnica de Catalunya and Ecole Nationale Supérieure des Téléecommunications de Bretagne and the PhD degree in Signal Processing and Telecommunications in 2000 from Université de Rennes 1. He has been since working at Centre National d'Etudes Spatiales, the French Space Agency, in Toulouse, France, in the field of remote sensing image processing. He is in charge for the development of image processing algorithms for the operational exploitation of Earth Observation images, mainly in the fields of image registration, change detection and object recognition.
Emmanuel Christophe received the PhD degree from Supaero, France in 2006 for his work in hyperspectral image compression and image quality. From 2006 to 2008, he was a research engineer at CNES, the French Space Agency, focusing on information extraction for high resolution optical images. Since that time, he is also deeply involved in the development of the open-source OTB. In October 2008, he moved to Singapore at CRISP, National University of Singapore, where he is discovering new challenges for remote sensing in tropical areas focusing particularly on SAR data.