Abstract. While optical remote sensing has demonstrated its capabilities for landslide
detection and monitoring, spatial and temporal demands for landslide early
warning systems (LEWSs) had not been met until recently. We introduce a novel
conceptual approach to structure and quantitatively assess lead time for
LEWSs. We analysed “time to warning” as a sequence: (i) time to collect,
(ii) time to process and (iii) time to evaluate relevant optical data. The difference
between the time to warning and “forecasting window” (i.e. time from
hazard becoming predictable until event) is the lead time for reactive
measures. We tested digital image correlation (DIC) of best-suited
spatiotemporal techniques, i.e. 3 m resolution PlanetScope daily imagery
and 0.16 m resolution unmanned aerial system (UAS)-derived orthophotos to reveal fast ground
displacement and acceleration of a deep-seated, complex alpine
mass movement leading to massive debris flow events. The time to warning for
the UAS/PlanetScope totals 31/21 h and is comprised of time to (i) collect –
12/14 h, (ii) process – 17/5 h and (iii) evaluate – 2/2 h, which is well below the
forecasting window for recent benchmarks and facilitates a lead time for
reactive measures. We show optical remote sensing data can support LEWSs with
a sufficiently fast processing time, demonstrating the feasibility of
optical sensors for LEWSs.