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Automated vehicle extraction and speed determination from quickbird satellite images
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
2011 (English)In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 4, no 1, 75-82 p.Article in journal (Refereed) Published
Abstract [en]

A new method has been developed to automatically extract moving vehicles and subsequently determine their speeds from a pair of QuickBird (QB) panchromatic (PAN) and multispectral (MS) images. Since the PAN and MS sensors of QB have a slight time lag (approximately 0.2 s), the speed of a moving vehicle can be determined from the difference in the positions of the vehicle observed in the PAN and MS images due to the time lag. An object-based approach can be used to extract a vehicle from the PAN image, which has a resolution of 0.6 m. However, it is difficult to accurately extract the position of a vehicle from an MS image because its resolution is 2.4 m. Thus, an area correlation method is proposed to determine the location of a vehicle from an MS image at a sub-pixel level. The speed of the moving vehicle can then be calculated by using the vehicle extraction results. This approach was tested on several parts of a QB image covering central Tokyo, Japan, and the accuracy of the results is demonstrated in this study.

Place, publisher, year, edition, pages
2011. Vol. 4, no 1, 75-82 p.
Keyword [en]
Correlation, object detection, vehicles, velocity measurement, Automated vehicles, Moving vehicles, Multi-spectral, Object based, Quickbird, QuickBird satellite, Sub pixels, Time lag, Tokyo, Japan, Vehicle extractions, Environmental management, Object recognition, Remote sensing, Velocimeters, Tracking (position), accuracy assessment, image analysis, measurement method, multispectral image, panchromatic image, satellite imagery, velocity, Honshu, Japan, Kanto, Tokyo [Kanto]
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-151433DOI: 10.1109/JSTARS.2010.2069555ISI: 000288678800010ScopusID: 2-s2.0-79953092400OAI: diva2:748893

QC 20140922

Available from: 2014-09-22 Created: 2014-09-22 Last updated: 2014-09-22Bibliographically approved

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Vu, Tuong Thuy
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