GEOMATIC TECHNIQUES FOR THE OPTIMIZATION OF SKI RESOURCES

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

ICE DETECTION ON AIRPLANE WINGS USING A PHOTOGRAMMETRIC POINT CLOUD: A SIMULATION

Abstract. This study describes some tests carried out, within the European project (reference call: MANUNET III 2018, project code: MNET18/ICT-3438) called SEI (Spectral Evidence of ice), for the geometrical ice detection on airplane wings. The purpose of these analysis is to estimate thickness and shape of the ice that an RGB sensor is able to detect on large aircrafts as Boeing 737-800. However, field testing are not available yet, therefore, in order to simulate the final configuration, a steel panel has been used to reproduce the aircraft surface. The adopted methodology consists in defining a reference surface and modelling its 3D shape with and without ice through photogrammetric acquisitions collected by a DJI Mavic Air drone hosting a RGB camera and processed by Agisoft Metashape software. The comparison among models with and without the ice has been presented and results show that it is possible to identify the ice, even though some noise still remains due to the geometric reconstruction itself. Finally, using 3dReshaper and Matlab software, the authors develop various analysis defining the operative limits, the processing time, the correct setting up of Metashape for a more accurate ice detection, the optimization of the methodology in terms of processing time, precision and completeness. The procedure can certainly be more reliable considering the usage of the hyperspectral sensor technique as future implementation

Sensors integration for smartphone navigation: performances and future challenges

Nowadays the modern Smartphones include several sensors which are usually adopted in geomatic application, as digital camera, GNSS receivers, inertial platform and RFID system. In this paper the Authors would like to testing the performances of internal sensors (IMU) of three modern smartphones (Samsung GalaxyS4, Samsung GalaxyS5 and iPhone4) compared to external mass-market IMU platform in order to verify their accuracy levels, in terms of positioning. Moreover, the Image Based Navigation (IBN) approach is also investigated: this approach can be very useful in hard-urban environment or for indoor positioning, as alternative to GNSS positioning. IBN allows to obtain a sub-metrical accuracy, but a special database of georeferenced images (DB) is needed, moreover it is necessary to use dedicated algorithm to resizing the images which are collected by smartphone, in order to share it with the server where is stored the DB. Moreover, it is necessary to characterize smartphone camera lens in terms of focal length and lens distortions. The Authors have developed an innovative method with respect to those available today, which has been tested in a covered area, adopting a special support where all sensors under testing have been installed. Geomatic instrument have been used to define the reference trajectory, with purpose to compare this one, with the path obtained with IBN solution. First results leads to have an horizontal and vertical accuracies better than 60 cm, respect to the reference trajectories. IBN method, sensors, test and result will be described in the paper

Reliability of the geometric calibration of an hyperspectral frame camera

One of the main tools for high resolution remote sensing and photogrammetry is the lightweight hyperspectral frame camera, that is used in several application areas such as precision agriculture, forestry, and environmental monitoring. Among these types of sensors, the Rikola (which is based on a Fabry–Perot interferometer (FPI) and produced by Senop) is one of the latest innovations. Due to its internal geometry, there are several issues to be addressed for the appropriate definition and estimation of the inner orientation parameters (IOPs). The main problems concern the possibility to change every time the sequence of the bands and to assess the reliability of the IOPs. This work focuses the attention on the assessment of the IOPs definition for each sensor, considering the impact of environmental conditions (e.g., different time, exposure, brightness) and different configurations of the FPI camera, in order to rebuild an undistorted hypercube for image processing and object estimation. The aim of this work is to understand if the IOPs are stable over the time and if and which bands can be used as reference for the calculation of the inner parameters for each sensor, considering different environmental configurations and surveys, from terrestrial to aerial applications. Preliminary performed tests showed that the focal length percentage variation among the bands of different experiments is around 1%

GEOMATIC TECHNIQUES FOR THE OPTIMIZATION OF SKI RESOURCES

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

ICE DETECTION on AIRPLANE WINGS USING A PHOTOGRAMMETRIC POINT CLOUD: A SIMULATION

This study describes some tests carried out, within the European project (reference call: MANUNET III 2018, project code: MNET18/ICT-3438) called SEI (Spectral Evidence of ice), for the geometrical ice detection on airplane wings. The purpose of these analysis is to estimate thickness and shape of the ice that an RGB sensor is able to detect on large aircrafts as Boeing 737-800. However, field testing are not available yet, therefore, in order to simulate the final configuration, a steel panel has been used to reproduce the aircraft surface. The adopted methodology consists in defining a reference surface and modelling its 3D shape with and without ice through photogrammetric acquisitions collected by a DJI Mavic Air drone hosting a RGB camera and processed by Agisoft Metashape software. The comparison among models with and without the ice has been presented and results show that it is possible to identify the ice, even though some noise still remains due to the geometric reconstruction itself. Finally, using 3dReshaper and Matlab software, the authors develop various analysis defining the operative limits, the processing time, the correct setting up of Metashape for a more accurate ice detection, the optimization of the methodology in terms of processing time, precision and completeness. The procedure can certainly be more reliable considering the usage of the hyperspectral sensor technique as future implementation

UAV PHOTOGRAMMETRY WITH OBLIQUE IMAGES: FIRST ANALYSIS ON DATA ACQUISITION AND PROCESSING

In recent years, many studies revealed the advantages of using airborne oblique images for obtaining improved 3D city models (e.g. including façades and building footprints). Expensive airborne cameras, installed on traditional aerial platforms, usually acquired the data. The purpose of this paper is to evaluate the possibility of acquire and use oblique images for the 3D reconstruction of a historical building, obtained by UAV (Unmanned Aerial Vehicle) and traditional COTS (Commercial Off-the-Shelf) digital cameras (more compact and lighter than generally used devices), for the realization of high-level-of-detail architectural survey. The critical issues of the acquisitions from a common UAV (flight planning strategies, ground control points, check points distribution and measurement, etc.) are described. Another important considered aspect was the evaluation of the possibility to use such systems as low cost methods for obtaining complete information from an aerial point of view in case of emergency problems or, as in the present paper, in the cultural heritage application field. The data processing was realized using SfM-based approach for point cloud generation: different dense image-matching algorithms implemented in some commercial and open source software were tested. The achieved results are analysed and the discrepancies from some reference LiDAR data are computed for a final evaluation. The system was tested on the S. Maria Chapel, a part of the Novalesa Abbey (Italy)

Automatic Path Planning for Unmanned Ground Vehicle Using UAV Imagery

Field machines play an important role in the management of agricultural environments. Increasing use of automated machines in precision agriculture has gained significant attention of farmers and industries to minimize human work load to perform tasks such as land preparation, seeding, fertilizing, plant health monitoring and harvesting. Path planning is considered as a fundamental step for agricultural machines equipped with autonomous navigation system. For mountain vineyards, path planning is a big challenge due to terrain morphology and unstructured vineyards. This paper proposes a workflow to generate an automatic coverage path plan for unmanned ground vehicles (UGVs) using georeferenced imagery taken by an unmanned aerial vehicle (UAV). First, image acquisition is performed over a vineyard to generate an orthomosaic and a digital surface model, which are then used to identify the vine rows and inter-row terrain. This information is then used by the algorithm to generate a path plan for UGV

Opinion on 'Responsible Dual Use' Political, Security, Intelligence and Military Research of Concern in Neuroscience and Neurotechnology

Current and newly emerging insights and technologies arising from research in brain sciences increase capabilities to access, assess and affect thought, emotion and behaviour. While much of this research and development is directed towards clinical use, it also has applications in other settings, notably in the political, security, intelligence and military (PSIM) domains. This is often referred to in terms of ‘Dual Use’. Many of these potential uses raise important social and ethical questions which demand the attention of all those involved in the research, administration, management and regulation of neuroscience research and related technological developments, including those in information and communication technologies (ICT) and robotics. In this Opinion, we suggest that we can increase our ability to identify which programmes and projects of research, development and innovation are ‘of concern’ by applying the principles of Responsible Research and Innovation (RRI) to the concept of ‘dual use’ and distinguishing between ‘responsible’ and ‘irresponsible’ systems of research and technological development. We therefore use the term ‘dual use research of concern’ (DURC) to refer to neuroscience research and technological innovations, and brain inspired developments in information and communication technologies, for use in the political, security, intelligence and military domains, which are either directly of concern because of their potential for use in ways that threaten the peace, health, safety, security and well-being of citizens, or are undertaken without responsible regard to such potential uses. To ensure ongoing attention to these issues, the Opinion proposes recommendations for the Human Brain Project, the European Union and the wider neuroscience and ICT community