A Sustainable Approach For Upgrading Geographic Databases Based On High Resolution Satellite Imagery

The availability of high-resolution satellite images could be exploited for upgrading geographic databases at medium scales (1:5,000-1:25,000) as alternative to aerial photogrammetry. The paper presents a procedure to carry out this task which is based on an automatic image-to-image registration procedure of new satellite data to existing ortho-photomaps that have to be upgraded. In order to get a regularization of control points extracted in automatic way, a technique implementing a neural network algorithm is applied. Once an image has been georeferenced, this can be ortho-corrected thanks to a DTM (nowadays available in almost all developed countries). However, the product which is obtained so far is still a raster maps. To cope with the increasing need of vector data in geographic databases, some tests performed on the extraction of features (buildings and roads) from real high-resolution satellite images have been performed and results are shown here. Finally, to complete the data acquisition process, the use of GPS-GIS data-logger receivers in differential mode is proposed.