The use of a Remotely Piloted Aircraft System (RPAS) for the characterization and monitoring of landslides has been widely improved in the last decade. In particular, the use of this system is particularly effective for the study of areas prone to geohazards. Zones affected by landslides, such as rock slides and debris flows, are often quite critical in terms of accessibility due to unstable blocs that can strongly limit the direct access to the studied area. In this paper, we present the case study of Ponte Formazza in NW Italian Alps. In June 2019, a massive and complex debris flow re-mobilized about 300,000 m³ of a rockslide deposit that occurred in 2009. In this particular environment, we tested traditional, direct and mixed photogrammetric approaches using various configurations of Ground Control Points (GCPs) of the photogrammetric block and by calculating the relative errors. The minimum configuration of GCPs was established to reduce in situ measurements without degrading the accuracy of the cartographic products. The images of three RPAS campaigns (2017, 2018 and 2019), processed with a Structure from Motion (SfM) technique, allowed us to obtain very high-resolution orthophoto and digital surface models (DSMs) before and after the 2019 event. A few GCPs, geolocated with a Global Navigation Satellite System (GNSS), improved the orthophoto and DSM quality (Root Mean Squared Error RMSE 5 cm) even in the areas far from the drone deployment. The availability of high-resolution models has been fundamental for the identification of the volume changes. Furthermore, the 3D view supported and completed the geomorphological mapping of affected areas, particularly in the areas where the field survey is dangerous. The use of ancillary meteorological data and Sentinel-2 satellite images allows for a better definition of the kinematics and the predisposal and triggering factors of the 2019 debris flow.

中文翻译：

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基于高分辨率RPAS数据的先进摄影测量技术进行泥石流和滑坡分析。Ponte Formazza案例研究（西北阿尔卑斯山）

在过去的十年中，使用远程驾驶飞机系统（RPAS）进行滑坡的特征描述和监测已经得到了广泛的改进。特别是，对于研究容易发生地质灾害的区域，该系统的使用特别有效。受滑坡影响的区域，例如岩石滑坡和泥石流，在通达性方面通常非常关键，因为不稳定的集团会严重限制直接进入研究区域的机会。在本文中，我们将介绍意大利西北阿尔卑斯山的Ponte Formazza案例。2019年6月，大量和复杂的泥石流重新运送了约300,000 m ³对2009年发生的岩石滑坡矿床进行了分析。在这种特殊环境下，我们使用摄影测量块的地面控制点（GCP）的各种配置并计算了相对误差，测试了传统的，直接的和混合的摄影测量方法。建立了GCP的最小配置，以减少原位测量而不会降低制图产品的准确性。使用运动结构（SfM）技术处理的三个RPAS活动（2017、2018和2019）的图像，使我们能够在2019年活动之前和之后获得非常高分辨率的正射和数字表面模型（DSM）。即使在远离无人机部署的地区，也有一些GCP与全球导航卫星系统（GNSS）进行了地理定位，从而提高了正射和DSM质量（均方根误差RMSE 5厘米）。高分辨率模型的可用性对于识别体积变化至关重要。此外，3D视图支持并完成了受影响区域的地貌制图，尤其是在实地调查很危险的区域。使用辅助气象数据和Sentinel-2卫星图像可以更好地定义运动学以及2019年泥石流的易感性和触发因素。