Evaluation of filtering methods for use on high-frequency measurements of landslide displacements

Abstract. Displacement monitoring is a critical control for risks associated with potentially sudden slope failures. Instrument measurements are, however, obscured by the presence of scatter. Data filtering methods aim to reduce scatter and therefore enhance performance early warning systems (EWSs). The effectiveness EWSs depends on lag time between onset acceleration its detection system such that timely issued implementation consequence mitigation strategies. This paper evaluates three (simple moving average, Gaussian-weighted Savitzky–Golay) considers their comparative advantages disadvantages. evaluation utilized six levels randomly generated synthetic data, as well high-frequency global navigation satellite (GNSS) displacement at Ten-mile landslide in British Columbia, Canada. simple average method exhibited significant disadvantages compared Savitzky–Golay approaches. presents framework evaluate adequacy different algorithms minimizing data