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There are several applications of vehicle information (position, speed, and direction). WorldView-2 satellite has three sensors: one Pan and two MS (MS-1: BGRN1, Pan, and MS-2:CYREN2). Because of a slight time gap in acquiring images from these sensors, the WorldView-2 images capture three different positions of the moving vehicles. This paper proposes a new technique to extract the vehicle information automatically by utilizing the small time gap in WorldView-2 sensors. A PCA-based technique has been developed to automatically detect moving vehicles from MS-1 and MS-2 images. The detected vehicles are used to limit the search space of the adaptive boosting (AdaBoost) algorithm in accurately determining the positions of vehicles in the images. Then, RPC sensor model of WorldView-2 has been used to determine vehicles' ground positions from their image positions to calculate speed and direction. The technique has been tested on a Worldview-2 image. A vehicle detection rate of over 95% has been achieved. The results of vehicles' speed calculations are reliable. This technique makes it feasible to use satellite images for traffic applications on an operational basis

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

AUTOMATIC MOVING VEHICLE'S INFORMATION EXTRACTION FROM ONE-PASS WORLDVIEW-2 SATELLITE IMAGERY