NH6.4 | PICO
Remotely Piloted Aircraft Systems (RPAS) and geosciences: innovation in methodologies, sensors and activities
Co-organized as G6.5/GI3.22/GM2.14
Convener: Daniele Giordan | Co-conveners: Marc Adams, Yuichi S. Hayakawa, Francesco Nex, Fabio Remondino
| Tue, 09 Apr, 10:45–12:30
PICO spot 1

The use of Remotely Piloted Aircraft Systems (RPAS) for geosciences applications has strongly increased in last years. Nowadays the massive diffusion of mini- and micro-RPAS is becoming a valuable alternative to the traditional monitoring and surveying applications, opening new interesting viewpoints. The advantages of the use of RPAS are particularly important in areas characterized by hazardous natural processes, where the acquisition of high resolution remotely sensed data could be a powerful instrument to quickly assess the damages and plan effective rescues without any risk for operators.
In general, the primary goal of these systems is the collection of different data (e.g., images, LiDAR point clouds, gas or radioactivity concentrations, etc.) and the delivery of various products (e.g., 3D models, hazard maps, high-resolution orthoimages, etc.).
The possible use of RPAS has promising perspectives not only for natural hazards, but also in the different field of geosciences, to support a high-resolution geological or geomorphological mapping, or to study the evolution of active processes. The high repeatability of RPAS flight and their limited costs allows the multi-temporal analysis of a studied area. However, methodologies, best practices, advantages and limitations of this kind of applications are yet unclear and/or poorly shared by the scientific community.
This session aims at exploring the open research issues and possible applications of RPAS in geosciences, collecting experiences, case studies, and results, as well as define methodologies and best practices for their practical use. The session will concern the contributions aiming at: i) describing the development of new methods for the acquisition and processing of RPAS dataset, ii) introducing the use of new sensors developed or adapted to RPAS, iii) reporting new data processing methods related to image or point cloud segmentation and classification and iv) presenting original case studies that can be considered an excellent example for the scientific community.