Abstract

Climate change is already affecting the entire world, with extreme weather conditions such as drought, heat waves, heavy rain, floods and landslides becoming more frequent, including Europe. In according to Paris agreement and relative European announcement of Carbon neutrality (by 2050), the saving of water and energy supplies is a fundamental aspect in the management of resources in production, sports, hospitality facilities and so on. Some methodologies for the optimization of the consumption of natural resources are required. This article describes an activity aimed at measuring, monitoring and analysing the thickness of the snowpack on the ski slopes during the winter season to permit a sustainable approach of snowmaking in alpine ski areas . The authors propose a methodology based on the integration of multitemporal surface (ground/snow) survey by Autonomous Aerial Vehicle (AAV) and low cost GNSS receivers mounted on snow groomers for a RTK (Real Time Kinematic) solution. To obtain a complete snow surface digital models with poor detailed images on ski slopes, some pre-processing techniques have been analysed to locally improve contrast and details with a local high pass filtering. The methodology has been employed in two study areas (Limone Piemonte, Prato Nevoso) located in the province of Cuneo, in the southern alpine area of Piedmont.

Details

Title
GEOMATIC TECHNIQUES FOR THE OPTIMIZATION OF SKI RESOURCES
Author
Aicardi, I 1 ; Angeli, S 2 ; Grasso, N 2   VIAFID ORCID Logo  ; Lingua, A M 1 ; Maschio, P 2 

 DIATI, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino, Italy; DIATI, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino, Italy; PIC4SeR, Politecnico di Torino Interdepartmental Centre for Service Robotics, Torino, Italy 
 DIATI, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino, Italy; DIATI, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino, Italy 
Pages
1009-1016
Publication year
2020
Publication date
2020
Publisher
Copernicus GmbH
ISSN
16821750
e-ISSN
21949034
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2432979249
Copyright
© 2020. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.