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Harbour Area Change Detection and Analysis Using SAR Images from a Recent Measurement Campaign
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6834-5676
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0003-0423-9927
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0003-3945-8951
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312X
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2023 (English)In: Proceedings of the IEEE Radar Conference 2023, Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper, Published paper (Refereed)
Abstract [en]

Synthetic aperture radar (SAR) data are widely used for remote sensing applications, such as change detection and environmental monitoring. This paper presents a recent measurement campaign for SAR images using the LORA system and investigates the applicability of the collected data for change detection. The region of interest in this study is a busy commercial harbour area in the south of Sweden. During the measurements, there were significant changes on the ground in the parking lot as trucks were disembarking a ship. The obtained SAR images were first filtered to have similar regions of interest in the Fourier domain to increase the coherence magnitude. Then, a constant false alarm rate (CFAR) algorithm was employed to detect changes with respect to trucks. In addition, optical aerial images were collected during this measurement campaign and were utilized to adjust the CFAR detection threshold. As a result, all the changed and unchanged regions corresponding to the selected targets were detected successfully. Moreover, a pattern of trucks’ utilization of the harbour’s parking lot during this peak time was obtained. The results demonstrate the applicability of the data from the ongoing measurement campaign and the possibility of further algorithm development for target detection and classification.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023.
Series
IEEE International Conference on Radar (RADAR), ISSN 1097-5764, E-ISSN 2640-7736
Keywords [en]
aerial images, CFAR detector, change detection, LORA system, SAR images
National Category
Remote Sensing
Identifiers
URN: urn:nbn:se:bth-25853DOI: 10.1109/radar54928.2023.10371086Scopus ID: 2-s2.0-85182738528OAI: oai:DiVA.org:bth-25853DiVA, id: diva2:1823814
Conference
IEEE International Radar Conference, RADAR 2023, Sydney, 6 November through 10 November 2023
Available from: 2024-01-03 Created: 2024-01-03 Last updated: 2024-02-05Bibliographically approved

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Javadi, SalehPalm, BrunaVu, Viet ThuyPettersson, Mats

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