Abstract. While optical remote sensing has demonstrated its capabilities for landslide detection and monitoring, spatial and temporal demands for landslide early warning systems (LEWS) were not met until recently. We introduce a novel conceptual approach for comprehensive lead time assessment and optimisation for LEWS. We analysed time to warning as a sequence; (i) time to collect, (ii) to process and (iii) to evaluate relevant optical data. The difference between 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 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 UAS and PlanetScope totals 31 h/21 h and is comprised of (i) time to 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 lead time for reactive measures. We show optical remote sensing data can support LEWS with a sufficiently fast processing time, demonstrating the feasibility of optical sensors for LEWS.

中文翻译：

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挑战多光谱遥感对陆上预警系统的及时预测：一种新颖的概念方法，在奥地利的萨特尔卡进行了测试

摘要。尽管光学遥感已经证明了其在滑坡检测和监测方面的能力，但直到最近才满足了对滑坡预警系统（LEWS）的时空需求。我们介绍了一种新颖的概念方法，用于LEWS的全面提前期评估和优化。我们按顺序分析了警告时间。（i）收集时间，（ii）处理和（iii）评估相关的光学数据。预警时间与预测时间之间的差异（即从危险变为可预测到事件发生的时间）是被动措施的准备时间。我们测试了最适合的时空技术的数字图像相关性（DIC），即3 m分辨率的PlanetScope每日图像和0.16 m分辨率的UAS衍生的正射影像，以揭示深层复杂的高山质量运动的快速地面位移和加速度，从而导致巨大的山体运动。泥石流事件。UAS和PlanetScope的警告时间总计31 h / 21 h，其中包括（i）收集时间12/14 h，（ii）处理时间17/5 h，以及（iii）评价2/2 h，这很好低于最近基准的预测窗口，并缩短了应对措施的交货时间。我们显示光学遥感数据可以以足够快的处理时间支持LEWS，证明了LEWS光学传感器的可行性。