@ARTICLE\{IMM2018-07123,
    author       = "J. Rutkowski and M. J. Canty and A. A. Nielsen",
    title        = "Site Monitoring with Sentinel-1 Dual Polarization {SAR} Imagery Using Google Earth Engine",
    year         = "2018",
    keywords     = "Remote sensing, synthetic aperture radar, statistical testing, change detection, cloud computing",
    pages        = "48-59",
    journal      = "Journal of Nuclear Materials Management",
    volume       = "XLVI",
    editor       = "",
    number       = "3",
    publisher    = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/7123-full.html",
    abstract     = "At no cost to the user, the Copernicus mission frequently releases Synthetic Aperture Radar (SAR) datasets collected by the Sentinel-1 sensors. These datasets are regularly pre-processed by the Google Earth Engine and made available to the scientific community for further processing and analysis. This paper describes the application of a recently developed sequential change detection algorithm for Sentinel-1 datasets based on an omnibus likelihood ratio test statistic within the Google Earth Engine platform. Change detection methods, such as the one described here, offer the nuclear non-proliferation community a new way to use remote sensing datasets for monitoring nuclear facilities worldwide."
}