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- W3138654015 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> 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 âtime to warningâ 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 âforecasting windowâ (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. 3âm resolution PlanetScope daily imagery and 0.16âm 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 31/21âh and is comprised of time to (i) collect â 12/14âh, (ii) process â 17/5âh and (iii) evaluate â 2/2âh, 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." @default.
- W3138654015 created "2021-03-29" @default.
- W3138654015 creator A5023432579 @default.
- W3138654015 date "2021-03-11" @default.
- W3138654015 modified "2023-10-16" @default.
- W3138654015 title "Online supplementary material to 'Point-by-point response' on RC1" @default.
- W3138654015 doi "https://doi.org/10.5194/nhess-2021-18-ac2" @default.
- W3138654015 hasPublicationYear "2021" @default.
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