@ARTICLE\{IMM2017-07027, author = "A. A. Nielsen and K. Conradsen and H. Skriver and M. J. Canty", title = "Visualization of and software for omnibus test based change detected in a time series of polarimetric {SAR} data", year = "2017", keywords = "Complex covariance matrix test statistic, complex Wishart distribution, multitemporal {SAR} data, quad polarization, full polarization, dual polarization, remote sensing change detection, visualization.", pages = "582-592", journal = "Canadian Journal of Remote Sensing", volume = "43", editor = "", number = "6", publisher = "", note = "{SAR} input images to wcRjl and wishart\_change\_Q etc are images of the (row-wise) upper-right elements of the covariance or coherency matrix, e.g. for full polarimetry: a vector with nine real (i.e., non-complex) elements, namely [ShhShh* Re(ShhShv*) Im(ShhShv*) Re(ShhSvv*) Im(ShhSvv*) ShvShv* Re(ShvSvv*) Im(ShvSvv*) SvvSvv*]. - Matlab code in zip-file ({NEW} {VERSION} of wishart\_change\_Q /10 April 2018), Python code at http://mortcanty.github.io/SARDocker/, Python code for Google Earth Engine at https://github.com/mortcanty/earthengine, JavaScript code to run directly in {GEE} Code Editor at http://fwenvi-idl.blogspot.de/2017/10/polsar-change-detection-in-google-earth.html.", url = "http://doi.org/10.1080/07038992.2017.1394182", abstract = "Based on an omnibus likelihood ratio test statistic for the equality of several variance-covariance matrices following the complex Wishart distribution and a factorization of this test statistic with associated p-values, change analysis in a time series of multilook polarimetric {SAR} data in the covariance matrix representation is carried out. The omnibus test statistic and its factorization detect if and when change occurs. Using airborne {EMISAR} and spaceborne {RADARSAT} 2 data this paper focuses on change detection based on the p-values, on visualization of change at pixel as well as segment level, and on computer software." }