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We present a methodology to use a UAV (unmanned aerial vehicle) to perform photogrammetric surveys and detailed geological mapping in mountain areas. This work is specially related to the presented case study with the aim to realize geomorphological maps from UAVs, since they can house different types of sensors and acquire data more rapidly and cheaply than traditional geological surveys directly obtained with field observations. This work explains how UAVs can obtain digital terrain models, orthophotos and 3D models in order to create slope and aspect maps for geological purposes. By integrating data from UAVs with geological surveys made on the field, geological maps can be produced where many of the geological elements are presented. This paper presents the integration of geomatics and geological techniques. Starting from UAV slope map and orthophotos, a new geological map was created in a faster and more detailed way compared to traditional geological survey on the ground. The application of this method regards a sector of the Western Alps (NW Italy), formed by glaciers and deep-seated gravitational slope deformations.

Global Navigation Satellite System (GNSS) positioning is currently a common practice thanks to the development of mobile devices such as smartphones and tablets. The possibility to obtain raw GNSS measurements, such as pseudoranges and carrier-phase, from these instruments has opened new windows towards precise positioning using smart devices. This work aims to demonstrate the positioning performances in the case of a typical single-base Real-Time Kinematic (RTK) positioning while considering two different kinds of multi-frequency and multi-constellation master stations: a typical geodetic receiver and a smartphone device. The results have shown impressive performances in terms of precision in both cases: with a geodetic receiver as the master station, the reachable precisions are several mm for all 3D components while if a smartphone is used as the master station, the best results can be obtained considering the GPS+Galileo constellations, with a precision of about 2 cm both for 2D and Up components in the case of L1+L5 frequencies, or 3 cm for 2D components and 2 cm for the Up, in the case of an L1 frequency. Moreover, it has been demonstrated that it is not feasible to reach the phase ambiguities fixing: despite this, the precisions are still good and also the obtained 3D accuracies of positioning solutions are less than 1 m. So, it is possible to affirm that these results are very promising in the direction of cooperative positioning using smartphone devices.

Forests are significant resources from an ecological, economic and social point of view. Their protection and management could greatly benefit from a complete knowledge of the shape and distribution of trees in forest stands. To this purpose, aerial surveys, especially through Airborne Laser Scanning (ALS), were carried out in the last years to acquire point clouds to be used in 3D models aimed at achieving an accurate description of tree crowns and terrain. However, airborne data acquisition is expensive and may provide poor results in case of dense foliage. Further, point cloud resolution is not very high, as models with a grid of 2-3 m are usually obtained. In order to implement more accurate 3D forest models, a feasible solution is the integration of point clouds obtained by aerial acquisition (ALS or photogrammetry) for the treetops and the terrain description, with information from terrestrial surveys. In this paper, we investigated the possible integration of point clouds obtained by Terrestrial Laser Scanner (TLS) with those collected by photogrammetric 3D models based on images captured by Unmanned Aerial Vehicle (UAV) in a test site located in northern Italy, with the aim of creating an accurate dataset of the forest site with high resolution and precision. The limits of ALS and TLS were bridged by aerial photogrammetry at low altitude (and vice versa). A 3D model of the study area was obtained with a resolution of 5 cm and a precision of 3 cm. Such model may be used in a wide range of applications in forestry studies, e.g., the reconstruction of 3D shapes of trees or the analysis of tree growth throught time. The implications of the use of such integrate approach as a support tool for decision-making in forest management are discussed.

The geomatic survey in the speleological field is one of the main activities that allows for the adding of both a scientific and popular value to cave exploration, and it is of fundamental importance for a detailed knowledge of the hypogean cavity. Today, the available instruments, such as laser scanners and metric cameras, allow us to quickly acquire data and obtain accurate three-dimensional models, but they are still expensive, require a careful planning phase of the survey, as well as some operator experience for their management. This work analyzes the performance of a smartphone device for a close-range photogrammetry approach for the extraction of accurate three-dimensional information of an underground cave. The image datasets that were acquired with a high-end smartphone were processed using the Structure from Motion (SfM)-based approach for dense point cloud generation: different image-matching algorithms implemented in a commercial and an open source software and in a smartphone application were tested. In order to assess the reachable accuracy of the proposed procedure, the achieved results were compared with a reference dense point cloud obtained with a professional camera or a terrestrial laser scanner. The approach has shown a good performance in terms of geometrical accuracies, computational time and applicability. Appl. Sci. 2019, 9, 3884 2 of 20 solution, and today it is possible to find cheaper and smaller versions, such as profiler [12] and handheld laser scanner devices [13,14]. The active optical sensors [15] allow to directly obtain the spatial position of the detected points, sometimes coupled with the color information; the latter can be recorded by the sensor itself or by an external digital camera integrated into the instrument. These type of instruments have the main advantage of directly and quickly acquiring large amounts of data related to a complex geometry, with a very high accuracy. The raw output data of laser scanner sensors are unstructured point clouds, one for each acquisition point (in the case of a classical laser scanner), which need to be registered in a unique reference system to produce a single point cloud of the scene. Typically, in terrestrial laser scanners (TLS) a mirror rotates vertically and the whole instrument rotates horizontally, allowing a sequential scanning of the scene in both horizontal and vertical directions. There are also handled versions of laser scanners, but they do not always allow for the acquisition of the radiometric information of the object, or they are still very expensive and require some experience, especially in the post-processing of data. These instruments, however, can be easily transported and introduced in restricted access environments [16], but they have limited capabilities when it comes to describing details and edges, which become curved and approximate. Finally, 3D data delivered by active sensors are generally affected by the light and surface characteristics of the scanned materials, by the glass and by specular material...

Landslides are one of the major geo-hazards which have constantly affected Italy especially over the last few years. In fact 82% of the Italian territory is affected by this phenomenon which destroys the environment and often causes deaths: therefore it is necessary to monitor these effects in order to detect and prevent these risks. Nowadays, most of this type of monitoring is carried out by using traditional topographic instruments (e.g. total stations) or satellite techniques such as global navigation satellite system (GNSS) receivers. The level of accuracy obtainable with these instruments is sub-centimetrical in post-processing and centimetrical in realtime; however, the costs are very high (many thousands of euros). The rapid diffusion of GNSS networks has led to an increase of using mass-market receivers for real-time positioning. In this paper, the performances of GNSS mass-market receiver are reported with the aim of verifying if this type of sensor can be used for real-time landslide monitoring: for this purpose a special slide was used for simulating a landslide, since it enabled us to give manual displacements thanks to a micrometre screw. These experiments were also carried out by considering a specific statistical test (a modified Chow test) which enabled us to understand if there were any displacements from a statistical point of view in real time. The tests, the algorithm and results are reported in this paper.

Nowadays, navigation systems are becoming common in the automotive industry due to advanced driver assistance systems and the development of autonomous vehicles. The MPU-6000 is a popular ultra low-cost Microelectromechanical Systems (MEMS) inertial measurement unit (IMU) used in several applications. Although this mass-market sensor is used extensively in a variety of fields, it has not caught the attention of the automotive industry. Moreover, a detailed performance analysis of this inertial sensor for ground navigation systems is not available in the previous literature. In this work, a deep examination of one MPU-6000 IMU as part of a low-cost navigation system for ground vehicles is provided. The steps to characterize the performance of the MPU-6000 are divided in two phases: static and kinematic analyses. Besides, an additional MEMS IMU of superior quality is also included in all experiments just for the purpose of comparison. After the static analysis, a kinematic test is conducted by generating a real urban trajectory registering an MPU-6000 IMU, the higher-grade MEMS IMU, and two GNSS receivers. The kinematic trajectory is divided in two parts, a normal trajectory with good satellites visibility and a second part where the Global Navigation Satellite System (GNSS) signal is forced to be lost. Evaluating the attitude and position inaccuracies from these two scenarios, it is concluded in this preliminary work that this mass-market IMU can be considered as a convenient inertial sensor for low-cost integrated navigation systems for applications that can tolerate a 3D position error of about 2 m and a heading angle error of about 3 °.