Benefiting from the improved resolution and polarization information of SAR data, ship recognition has attracted much attention during the last decade. This paper considers the ship recognition in TerraSAR-X imagery. We propose a novel feature extraction algorithm, named Superstructure Scattering Distribution (SSD), by investigating the ship’s superstructure and corresponding electromagnetic sc...

Monitoring urban growth and change is an important issue for urban planning and disaster management. In this study, two different approaches are conducted to monitor the urban areas. One is that a TerraSAR-X image is compared with an ALOS/PALSAR image to investigate the characteristics of urban land cover in different radar wavelengths. Also, a very high resolution optical QuickBird image is us...

In this paper an object based classification method for detection of storm damages with TerraSAR-X images is described. The segmentation process is carried out with the software Ecognition. Classification is done by setting a threshold, which is identified by visual interpretation. Afterwards a region growing method is applied and forest GIS and pre storm ortho photos are used to improve the ac...

This paper shows the suitability of High Resolution (HR) TerraSAR-X data for monitoring urban areas by means of feature extraction algorithms able to exploit the new information content provided by HR Synthetic Aperture Radar (SAR) images. The approach we follow is deterministic and model-based, meaning that the building feature extraction is based on the direct inversion of the electromagnetic...

This paper introduces a method for road network extraction from satellite images. The proposed approach covers a new fusion method (using data from multiple sources) and a new Markov random field (MRF) defined on connected components along with a multilevel application (two levels MRF). Our method allows the detection of roads with different characteristics and decreases by around 30% the size ...