@CONFERENCE\{IMM2011-05983, author = "A. A. Nielsen and M. J. Canty", title = "A method for unsupervised change detection and automatic radiometric normalization in multispectral data", year = "2011", month = "apr", booktitle = "34th International Symposium on Remote Sensing of Environment", volume = "", series = "", editor = "", publisher = "", organization = "", address = "Sydney, Australia", url = "http://www2.compute.dtu.dk/pubdb/pubs/5983-full.html", abstract = "The iteratively re-weighted multivariate alteration detection (IR-MAD) algorithm may be used for unsupervised change detection in multi- and hyperspectral remote sensing imagery as well as for automatic radiometric normalization of such multitemporal image sequences. Simple spectral band-byband differences make sense only when the data are calibrated or at least normalized to the same scale and zero. The idea in the {IR-MAD} method is: rather than ordering the data by wavelength we order them by a measure of similarity, here correlation. This is done by means of an established multivariate statistical technique called canonical correlation analysis. This ensures independence of linear and affine scaling of the original data. The pair-wise differences between the canonical variates which are as similar as they can get are the change variables; these differences are termed the {MAD} variates. The {IR-MAD} method in a series of iterations places increasing weight on the no-change observations. Examples show the application to Landsat {ETM}+ data covering villages, agricultural areas and open pit mines in western Germany as well as to {ASTER} imagery for detection of landslides in the aftermath of the 2005 earthquake in Kashmir. It is demonstrated how the iterated scheme homes in on the no-change observations giving a very good discrimination between change and no-change regions. It is also shown how the no-change observations may be used in (orthogonal) regression to obtain automatic radiometric normalization of image time series. {IDL}/{ENVI,} Python and Matlab software to carry out the analyses is available from the authors’ websites." }