Towards Robust Analysis of Satellite Images of Algeria Application to Road Network and its Nodes Extraction

Actualization of cartographic data using imagery is an important application in the earth sciences. Extraction of map objects such roads from satellite imagery are an important task in many civilian and military applications. Particularly, extraction of these objects from digital imagery is of major practical importance for data acquisition and update of geographic information systems GIS database. So, the integration of automatic objet extraction from imagery and GIS for the update of geodata becomes more and more important. In this article, we present a study which its main objective is to solve the problem of the automatic update a roadmap. This study is thus applied for that the geographical representation of the images is as near as possible to the reality. It concerns a proposed approach for semi-automated extraction of road networks with its nodes (intersections points between each two roads) by optimizing the developed methodology for this problem of extraction from satellite imagery in our previous works (Nougrara and al., 2011 and 2012). It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Tests of this approach are conducted on satellite imagery. The results show that the proposed method can successfully extract objects (roads, road network and nodes) from the satellite images and optimize the time when comparing to some existing methods in this field.