Semantic Map Generation from Satellite Images for Humanitarian Scenarios Applications

摘要

This paper demonstrates how knowledge driven methods and the associated data analysis algorithms are changing the paradigms of user-data interactions, providing an easier and wider access to the Earth Observation data. Some information theory based algorithms are proposed for anomaly and change detection on SPOT images, relative to a widespread humanitarian crisis scenario: floods. The outcomes of these algorithms define an informational representation of the image, revealing the spatial distribution of a particular theme. Using image analysis and interpretation, the multitude of features from a scene are classified into meaningful classes to create sematic maps.