A METHOD OF TIME-SERIES CHANGE DETECTION USING FULL POLSAR IMAGES FROM DIFFERENT SENSORS

Liu, W.; Yang, J.; Zhao, J.; Shi, H.; Yang, L.

Most of the existing change detection methods using full polarimetric synthetic aperture radar (PolSAR) are limited to detecting change between two points in time. In this paper, a novel method was proposed to detect the change based on time-series data from different sensors. Firstly, the overall difference image of a time-series PolSAR was calculated by ominous statistic test. Secondly, difference images between any two images in different times ware acquired by R j statistic test. Generalized Gaussian mixture model (GGMM) was used to obtain time-series change detection maps in the last step for the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection by using the time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can detect the time-series change from different sensors.

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Liu, W. / Yang, J. / Zhao, J. / et al: A METHOD OF TIME-SERIES CHANGE DETECTION USING FULL POLSAR IMAGES FROM DIFFERENT SENSORS. 2018. Copernicus Publications.

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