Near real-time disturbance detection using satellite image time series

► We propose a new time series based near real-time change monitoring approach. ► The method is robust, fast and does not require gap filling or smoothing. ► A wide range of in-situ and remote sensing data series can be analysed. ► Drought related disturbances are detected in southern Somalia as an example. ► Functionality is available via the 'bfast' package for R.