Andrea Maria Lingua

Indoor navigation using Smartphone technology: A future challenge or an actual possibility?

Today knowing where we are has become an important issue for people who interactively and dynamically live and work in urban cities. Each user has a very complete and complex set of technologies for positioning and navigating in his/her hands which are simple to use even if they are not good at positioning or in Geomatics. Accelerometers, gyroscopes, magnetometers, pressure sensors, GNSS receivers, digital cameras are all tools which can be used for defining a three-dimensional position and their integration could be the key point of this technology. Indoor positioning is the latest challenge to be used whenever GNSS positioning is not always available or null, even using high sensitivity sensors. An alternative solution must be found starting from determining the other available solutions in Smartphone devices. An example of indoor positioning could be obtained by using the Image Based Navigation (IBN) approach, where the coordinates of our device are defined using the photogrammetric principle. Several papers demonstrate that IBN can be an useful approach for positioning and how the device in Smartphones can work indoors. In this study, the authors attempt to combine the IBN method with the potentiality of Smartphone internal sensors, in order to verify their performance in indoor positioning.

Low cost mobile mapping systems: an Italian experience

Road cadastre mapping is a topic of current interest in Italy because each Region has to prepare one. The main problem is to obtain an accurate low cost product but in a brief operational time. Nowadays, many tools exist to solve this problem: one of these is the mobile mapping. Different integrated systems (GNSS, IMU, video camera) are available that allow accurate and quick mapping. These systems are usually expensive. Starting from some previous international experience, a low cost mobile mapping system has been developed that employs 2 GNSS receivers, 1 IMU, 1 digital video camera and some dedicated software tools to calibrate, manage and use the system. These devices have been installed on a particular crossbar, which was installed on the roof of a standard vehicle. This allows the images to be recorded using the video camera and single frames are directly georeferenced. This system must be first calibrated using a special control network; in this way, it is possible to use this platform on any vehicle and the system is completely independent of the support. The recorded videos are divided into single frames and each one is georeferencing using GNSS and IMU data. Moreover each frame is used to identify the single details on the road (i.e. traffic signal) which are the main components of the road cadastre map. It is then possible to reconstruct the roadway axis and the average between two trajectories. A special software devoted to defining each axis has been developed. The aim is to recover the position of the axis with submetric accuracy. A special algorithm has been used, which works considering the ortho distance between the axes. This system has been tested over several kilometres: accuracy of the shape, axes and roadways has been estimated, considering the limits imposed by Italian law about road cadastral mapping. The results obtained, in particular the accuracy of the relief, the quality and the calibration procedures are described in this paper. The main product of this work is that it is possible to obtain a low cost mobile mapping system (about 25 Keuro), with a good accuracy which is useful for any kind of vehicle.

Monitoring post-fire forest recovery using multi-temporal Digital Surface Models generated from different platforms

Wildfires can greatly affect forest dynamics. Given the alteration of fire regimes foreseen globally due to climate and land use changes, greater attention should be devoted to prevention and restoration activities. Concerning in particular post-fire restoration actions, it is fundamental, together with a better understanding of ecological processes resulting from the disturbance, to define techniques and protocols for long-term monitoring of burned areas. This paper presents the results of a study conducted within an area affected by a stand-replacing crown fire (Verrayes, Aosta (AO), Italy) in 2005, which is part of a long-term monitoring research on post-fire restoration dynamics. We performed a change detection analysis through a time sequence (2008-2015) of DSMs (Digital Surface Models) obtained from LiDAR (ALS - Airborne Laser Scanner) and digital images (UAV - Unmanned Aerial Vehicle flight) to test the ability of the systems (platform + sensor) to identify the ongoing processes. New technologies providing high-resolution information and new devices (i.e. UAV) able to acquire geographic data “on demand” demonstrated great potential for monitoring post disturbance recovery dynamics of vegetation

Dense 3D Model Generation of a Dam Surface Using UAV for Visual Inspection

In recent years the term “industry 4.0” has been consolidated, indicating a trend towards the automation of industrial processes with the introduction of new technologies to support the production of goods and services. Connected to this new type of industry, in this paper, the authors describe the implementation of a solution based on the automatic analysis of data extracted from a photogrammetric survey. In particular, a low-cost UAV system has been used and, in this paper, all the analyses involved in the planning of the data acquisition phase, their management and processing within a GIS system are described. During the acquisition phase, different data sets were acquired using different techniques, recording 4 k video and acquiring high resolution images. The place chosen to perform this test was the Serru dam, a plant located in Ceresole Reale, near Turin, Piedmont (Italy). A 3D model was made of this structure on which a wall integrity check was carried out.