The SWADE model for landslide dating in time series of optical satellite imagery

Abstract Landslides are destructive natural hazards that cause substantial loss of life and impact on built environments. Landslide frequencies important inputs for hazard assessments. However, dating landslides in remote areas is often challenging. We propose a novel landslide technique based Segmented WAvelet-DEnoising stepwise linear fitting (SWADE), using the Landsat archive (1985–2017). SWADE employs principle vegetation removed by landsliding vegetated areas, causing temporal decrease normalized difference index (NDVI). The applicability two previously published methods dating, harmonic modelling LandTrendr, evaluated 66 known Buckinghorse River area, northeastern British Columbia, Canada. identifies sudden changes NDVI values time series this may result one or more probable occurrence dates. most-probable date range identified detects 52% within maximum error 1 year, 62% 2 years. Comparatively, these numbers increase to 68% 80% when including ranges, respectively. Harmonic 79% with 82% years, but requires expert judgement well-developed seasonal cycle contrast SWADE. originally developed mapping deforestation, only 42% provides promising fully automatic method which can contribute constructing frequency-magnitude distributions areas.