Volcanic Risk Assessment and Mapping in the Vesuvian Area Using GIS

This paper assesses the risk to people and property from lava flow hazard in the Vesuvian area of Italy using a Geographical Information System (GIS). The intense urbanisation and dense population near Mt. Vesuvius make the area very hazardous. Due to the large amount of available data, GIS is an essential tool to facilitate risk evaluation and constant monitoring of the zone. This analysis is based mainly on a lava flow hazard map of Mt. Vesuvius, determined from volcanic activity between 1631 and 1944. A land-use zonation map of the area was created in order to show areal distribution of the resources, built-up centres and population. For each of the 17 municipalities in the area, demographic and urban data were entered into the GIS database and linked to each appropriate geographic unit in order to create a set of reference maps at the 1:50 000 scale. The lava flow hazard map was overlain on the land use map, and spatial and numerical information of risk were extracted from the resulting maps.     

Use of terrestrial photogrammetry based on structure‐from‐motion for mass balance estimation of a small glacier in the Italian alps

Different high‐resolution techniques can be employed to obtain information about the three‐dimensional (3D) surface of glaciers. This is typically carried out using efficient, but also expensive and logistically demanding, light detection and ranging (LiDAR) technologies, such as airborne scanners and terrestrial laser scanners. Recent technological improvements in the field of image analysis and computer vision have prompted the development of a low‐cost photogrammetric approach, which is referred to as ‘structure‐from‐motion’ (SfM). Combined with dense image‐matching algorithms, this method has become competitive for the production of high‐quality 3D models. However, several issues typical of this approach should be considered for application in glacial environments. In particular, the surface morphology, the different substrata, the occurrence of sharp contrast from solar shadows and the variable distance from the camera positions can negatively affect the image texture, and reduce the possibility of obtaining a reliable point cloud from the images. The objective of this study is to test the structure‐from‐motion multi view stereo (SfM‐MVS) approach in a small debris‐covered glacier located in the eastern Italian Alps, using a consumer‐grade reflex camera and the computer vision‐based software PhotoScan. The quality of the 3D models produced by the SfM‐MVS process was assessed via the comparison with digital terrain models obtained from terrestrial laser scanning (TLS) surveys that were performed at the same epochs. The effect of different terrain gradients and different substrata (debris, snow and firn) was also evaluated in terms of the accuracy of the reconstruction by SfM‐MVS versus TLS. Our results show that the quality of this new photogrammetric approach is similar to the quality of TLS and that point cloud densities are comparable or even higher compared with TLS. However, special care should be taken while planning the SfM survey geometry, to optimize the 3D model quality and spatial coverage. Copyright © 2015 John Wiley & Sons, Ltd.     

Characterization of wood-laden flows in rivers

Inorganic sediment is not the only solid-fraction component of river flows; flows may also carry significant amounts of large organic material (i.e. large wood), but the characteristics of these wood-laden flows (WLFs) are not well understood yet. With the aim to shed light on these relatively unexamined phenomena, we collected home videos showing natural flows with wood as the main solid component. Analyses of these videos as well as the watersheds and streams where the videos were recorded allowed us to define for the first time WLFs, describe the main characteristics of these flows and broaden the definition of wood transport regimes (adding a new regime called here hypercongested wood transport). According to our results, WLFs may occur repeatedly, in a large range of catchment sizes, generally in steep, highly confined single thread channels in mountain areas. WLFs are typically highly unsteady and the log motion is non-uniform, as described for other inorganic sediment-laden flows (e.g. debris flows). The conceptual integration of wood into our understanding of flow phenomena is illustrated by a novel classification defining the transition from clear water to hypercongested, wood and sediment-laden flows, according to the composition of the mixture (sediment, wood, and water). We define the relevant metrics for the quantification and modelling of WLFs, including an exhaustive discussion of different modelling approaches (i.e. Voellmy, Bingham and Manning) and provide a first attempt to simulate WLFs. We draw attention to WLF phenomena to encourage further field, theoretical, and experimental investigations that may contribute to a better understanding of flows in river basins, leading to more accurate predictions, and better hazard mitigation and management strategies. © 2019 John Wiley & Sons, Ltd.     

From consumer to enterprise grade: How the choice of four UAS impacts point cloud quality

Uncrewed aerial systems (UAS), combined with structure-from-motion photogrammetry, has already proven to be very powerful for a wide range of geoscience applications and different types of UAS are used for scientific and commercial purposes. However, the impact of the UAS used on the accuracy of the point clouds derived is not fully understood, especially for the quantitative analysis of geomorphic changes in complex terrain. Therefore, in this study, we aim to quantify the magnitude of systematic and random error in digital elevation models derived from four commonly used UAS (XR6/Sony α6000, Inspire 2/X4s, Phantom 4 Pro+, Mavic Pro) following different flight patterns. The vertical error of each elevation model is evaluated through comparison with 156 GNSS reference points and the normal distribution and spatial correlation of errors are analysed. Differences in mean errors (−0.4 to −1.8 cm) for the XR6, Inspire 2 and Phantom 4 Pro are significant but not relevant for most geomorphological applications. The Mavic Pro shows lower accuracies with mean errors up to 4.3 cm, thus showing a higher influence of random errors. QQ plots revealed a deviation of errors from a normal distribution in almost all data. All UAS data except Mavic Pro exhibit a pure nugget semivariogram, suggesting spatially uncorrelated errors. Compared to the other UAS, the Mavic Pro data show trends (i.e. differences increase with distance across the survey—doming) and the range of semivariances is 10 times greater. The lower accuracy of Mavic Pro can be attributed to the lower GSD at the same flight altitude and most likely, the rolling shutter sensor has an effect on the accuracy of the camera calibration. Overall, our study shows that accuracies depend highly on the chosen data sampling strategy and that the survey design used here is not suitable for calibrating all types of UAS camera equally.