BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt changes within the trend and seasonal components. BFAST can be used to analyze different types of satellite image time series and can be applied to other disciplines dealing with seasonal or non-seasonal time series, such as hydrology, climatology, and econometrics. The algorithm can be extended to label detected changes with information on the parameters of the fitted piecewise linear models. BFAST monitor provides functionality to detect disturbance in near real-time based on BFAST-type models.
Installation: need R environment;
Input: time series data
Output: the fited trend component,the fited seasonal component, the noise or remainder component;
Contact SupportNorthwest Institute of Eco-Environment and Resources, CAS 0931-4967287 firstname.lastname@example.org
LinksNational Tibetan Plateau Data Center