Topographical data producers are currently confronted the need of a faster updating method. Although a state-of-the-art technique
exists, no automated tool predicts and locates changes. The general objective of the project is to capitalize partners' knowledge
in the development of a demonstrator to assist data producers in updating more efficiently their topographic database by using
state-of-the-art image processing and statistical analysis techniques. Data will include remote sensing images, together with
socio-economical data. To achieve this general objective, two main axes are distinguished: -	At a regional scale, the objective is to
analyze topographical databases from multiple sources such as satellite images, demographic database, or economic database in order
to predict information about the localization of changes in man-made structures (such as houses, roads, etc.). -	At a local scale,
for areas of predicted changes the older databases will be compared with recent very high resolution images in order to detect and
recognize differences (errors in the topographical database, building construction, road construction, etc'). Several types of
man-made structures are distinguished (house, road, etc.)