The present work aims to introduce an efficient set of high spatial resolution (HSR) images in order to more fairly evaluate building detection algorithms. The introduced images are chosen from two recent HSR sensors (QuickBird and GeoEye-1) and based on several challenges of urban areas encountered in building detection such as diversity in building density, building dissociation, building sha...

Land use recognition from multispectral satellite images is fundamentally critical for geological applications, but the results are not satisfied. The scale dimension of current multiscale learning too coarse to account rich scales in images, and pixel-wise classification tends produce “salt-and-pepper” labels due possible misclassification heterogeneous regions. In this paper, these issues add...

Landslides can be listed as a major natural hazard for the Bostanlik district, Uzbekistan characterized by its mountain terrain. Currently, monitoring system is not in place, which mitigate numerous negative effects of landslides. The current study presents first Earth Observation-based landslide inventory Uzbekistan. We applied random forest Object-Based Image Analysis (OBIA) on very high-reso...

This paper discusses the potentials of very high-resolution (VHR) stereo imagery for automatic generation of digital surface models (DSM) and 3D information extraction on large metropolitan cities. Stereo images acquired by GeoEye-1 on Dakar (Senegal) and Guatemala City (Guatemala) and by WorldView-2 on Panama City (Panama), Constitucion (Chile), Kabul (Afghanistan), Teheran (Iran), Kathmandu (...

As the aerospace industry grows, images obtained from Earth observation satellites have been successfully used in various fields. Specifically, the demand for a high-resolution (HR) optical images is gradually increasing, and hence the generation of a high-quality mosaic image is being magnified as an interesting issue. In this paper, we have proposed an efficient mosaic algorithm for HR optica...

This study aims to extract the instantaneous shoreline from remote sensing data acquired with very high resolution multispectral and SAR sensors. The capabilities of IKONOS, GeoEye and COSMO-SkyMed for shoreline detection are tested in the Venice littoral (Italy) by classifying the imagery into its land/water components. GPS measurements synchronously to the COSMO-SkyMed acquisitions are carrie...

Detection of urban objects in very high resolution (VHR) satellite imagery is challenging due to the similarities in the spectral and textural characteristics of urban land cover classes. Therefore, additional information such as elevation data is required for a proper classification. In this study, instead of LiDAR data, elevation information generated from satellite stereo images is used to a...