First results on road network extraction and fusion on optical and SAR images using a multi-scale adaptive approach

In this article, we introduce a unitary approach to road extraction in wide area images, obtained by means of satellite sensors in both the optical/infrared and microwave domains. Despite the large amount of methodologies discussed in technical literature for road extraction, they have been mostly tested on relatively small portions of satellite images. Moreover, in many cases, the method targeted an optical or a synthetic aperture radar (SAR) image, and a unitary strategy is missing. This study is aimed at bridging these gaps and provides a unique framework for the extraction of roads with different characteristics using optical or SAR data sets. The approach exploits a multi-scale analysis to adapt to the different resolutions of data and a pre-processing step to adapt to the different wavelengths of data. When possible, the framework allows the fusion of the road networks extracted from optical and SAR data of the same area. The soundness of the approach is proved by means of the analysis of Landsat and ALOS data of an area in Congo.