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In the presented research, the change detection of the urban area in Poland was conducted. Due to the lack of availability of multi-temporal data from a similar sensor, the multi-sensor change detection was applied. For the research purpose data from low-resolution Landsat satellites, medium resolution Sentinel, along with high-resolution WorldView, Spot, and Pleiades satellites were used. In order to perform change detection, all data were preprocessed with radiometric calibration and geometric correction. The analysis of changes for the urban area was carried out for three dates. Because for each of the dates various sets of data were available, i.e. for each date, there were imagery data acquired with at least two different sensor-low and high-resolution data, and for different dates, the sets varied, in the first place data fusion for each date was conducted. For data fusion, pan-sharpening was applied. Thanks to this process, images with a similar spatial resolution for three dates were obtained. After such data preparation, the process of detecting changes was started. For change detection, both pixel and object-based change detection techniques were used, i.e. image differencing, image transformations, pixel-based and object-based classification, vegetation indices differencing, and image regression, were applied. As a result of the conducted analyses, many changes were noted in the analysed urbanised area, including changes in land use and changes in vegetation. In order to get complete information about the changes, basic detection techniques were integrated. The accuracy of the obtained results of change detection was affected by the accuracy of data integration for the different dates. In spite of several errors, the use of multi-sensors would enable the analysis of changes in a wider scope.
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