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Change detection involving SAR combined with optics
In this combination, changes are automatically detected via the SAR satellite images of two periods. In particular, for SAR images, in which it has heretofore been difficult to detect changes via simple image comparison, the use of AI has made it possible to detect only the changes desired.
By comparing satellite images from two periods, it is possible to read the changes during those periods. Here, the change detection capabilities of optics and SAR are combined, thus allowing for the continuous extraction of changes when currently available satellite data is limited. Although the change detection capability of optical satellites has improved due to the progress of the utilization of small satellites, etc., in terms of SAR, it has been difficult to detect changes due to image noise, and thus continuous analysis in combination with optics was considered difficult. Against this backdrop, SAR satellites can intimately grasp ground surface conditions, even amid inclement weather conditions such as cloud cover. Conversely, optical satellites cannot grasp conditions at night or at times of cloud cover.
Thus, by combining highly available optical satellite data with SAR satellite data, which is not affected by weather or restricted by time, a higher temporal resolution can be achieved. Furthermore, by developing a dedicated AI algorithm for each, it has become possible to extract only the desired changes. Also, in the analysis of urban sprawl as a measure of new structure detection or changes in land use status, etc., it is now possible to achieve automatic analysis that makes the best use of currently available satellite data.