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Title

ADVANCED PROCESSING CAPABILITIES OF THE ORFEO TOOLBOX IN RAPID MAPPING CONTEXT

Abstract

The International Charter aims at providing a unified system of space data acquisition and delivery to those affected by disasters and help to mitigate their effects.It has already been activated more than 300 times and helped rescue efforts by providing updated views of how the landscape and the infrastructure have been affected. For example satellite images (both from optical and radar sensors) were acquired immediately after the earthquake which struck the Haitian capital of Port-au-Prince last January and were used to generate emergency maps to provide rescuers with an overview of the current state of the area.

Early response after the earthquake showed the conjugation of an unprecedented release of imageries and the collaborative efforts of international volunteer mappers from the Open Street Map project for example which provided acurate and updated maps to rescue teams and really change the way of understanding Disaster Response service. In most situations, getting the raw satellite image is not enough for the people involved in rescue operations, value-added content and dynamic products are compulsory to provide a valuable context to the image.

In the frame of the Charter, specific modules were developed for Monteverdi. The Monteverdi application aims at providing a end user application which works as a front end to the Orfeo Toolbox library. The purpose is to make the advanced processing capabilities of OTB available to non programmers. The architecture is highly scalable and the application was for example already extended to provide interaction between remote sensing products and exogenous data. The application provides modules which allow to interactively select  GCP using Open Street Map. It also provides automatic tools to extract and export the value added product to KML format. Additionally to classic maps, providing the information as KML file can help to reach a wider audience in a timely manner.

Authors

Manuel Grizonnet - CNES
Emmanuel Christophe - CRISP, National University of Singapore
Julien Michel - CNES
Rosario Ruiloba - CS-SI