Search

Recent technological advances are leading numerous researchers and professional users to the adoption of photogrammetric products for a wide range of geoscientific applications. Especially, drone-based Structure-from-Motion (SfM) photogrammetry is often applied as a high-resolution topographic modelling technique with advantages in terms of time and cost when compared to traditional surveying approaches. The aim of this work, carried out within the GeoArchaeo Sites Project, is to investigate the adaptability of drone-based surveys, even with a targetless approach, and to estimate bathymetrical accuracies in shallow waters. The approach was applied on an underwater site to show the potential for the digitalization and monitoring of an archaeological coastal geosystem in central Italy. Specifically, this work has compared the photogrammetric surveying capability of two drones including a Phantom 4 RTK (‘P4RTK’) and a low-cost Mavic Mini 2 (‘MM2’) and an Olympus TG-6 (underwater camera) for a site submerged with a maximum depth of ∼1.6 m. The assessment of the drone SfM-based products was performed through area-based and point-wise comparisons. Specifically, the area-based were assessed through an underwater photogrammetric survey obtained by acquiring images by an operator snorkeling along a portion of the site of interest. The point-wise comparison was performed using data acquired with a Global Navigation Satellite System (GNSS). This study demonstrates that coupling SfM-photogrammetry and UAS-based surveys have potential to define submerged topography. In particular, the imagery acquired with the P4RTK survey can produce dense 3D models of the underwater surface with high resolution (about 0.02 m) and bathymetric measurements with a vertical accuracy ranging between 0.06 and 0.29 m for the area-based and point-wise analysis, respectively. Thus, the approach adopted and tested involving the use of a P4RTK has the potential to reduce constraints and limitations in terms of GCPs distribution and measurement. Also, with such an approach the need for qualified operators for underwater photogrammetric workflow can be avoided.

In this paper, the authors argue that integration of the hydrological model for landslide-prone areas should proceed under a soft geovisual communication in order to mitigate the uncertainty involved in downscaling rainstorm hazard mapping and geocomputational tracking. In this respect, examples of geovisualized spatial patterns for Terminio-Tuoro area affected by damaging landslide events is given by the rainstorm hazard index (RHI)–kriged probability map. These findings should contribute to improving the information base needed to implement and monitor a sound strategy for warning, forecasting and planning landslide hazard. . © Springer International Publishing Switzerland 2015.