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.