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Teaching experience in geomatics heavily relies on hands-on activities, but field surveys for educational purposes are usually conducted in controlled environments without proper connection to real-world scenarios. Combining the widespread availability of low-cost equipment with the potential of Free and Open Source Software for Geospatial (FOSS4G) in innovative teaching programmes can fill the gap in preparing young professionals in geomatics and surveying for real-world problems and global challenges, including climate change. This paper presents the active learning experience of the Belvedere Glacier Summer School organized annually by the Department of Civil and Environmental Engineering of Politecnico di Milano in the Italian Alps. During the week-long programme of theoretical and practical sessions, students from different backgrounds, ranging from Engineering to Architecture and Geoinformatics, transform knowledge into skills by designing and carrying out surveys focused on monitoring the evolution of the glacier volume, using GNSS and UAV photogrammetry, and familiarising with 2D and 3D data processing. In a peer-led environment, participants also contribute to the production of open data (orthophotos, DSM and point measurements) published in Zenodo, fostering teamwork and collaboration not only internally but also with the wider research community.

In recent years, the digitalization and dissemination of historical heritage have become crucial nodes in the preservation and valorization of Cultural Heritage (CH). Technologies such as Unmanned Aerial Vehicle (UAV) and terrestrial photogrammetry, Terrestrial Laser Scanning (TLS) and handheld Simultaneous Localisation and Mapping (SLAM) laser scanning allow the generation of digital models of architecture that can be explored through interactive web platforms, such as those based on WebGL graphic library. These are considered one of the most promising innovations for digitizing and sharing CH site due to their application in a wide range of contexts, promoting new forms of interaction with architecture at different scales. Additionally, the use of geomatic tools allows for a more complete 3D reconstruction and evaluation of the results by comparing different techniques. The article focuses on digitization as a tool for documenting and sharing CH assets, with the aim of developing a replicable prototype platform for an immersive Virtual Tour (VT) of an art collection and the architectural complex in which it is resided. In addition, this paper presents the results of a case study conducted at the Ricci Oddi Gallery of Modern Art in Piacenza, Italy. The source code of the implemented application is available on GitHub to permit replicability for other case studies.

The recent collapse of bridges in Italy has prompted numerous studies on monitoring and maintenance. Many structures in Italy have been in service for over 50 years, necessitating new approaches to ensure their safety. To address this issue, Italy's Consiglio Superiore dei Lavori Pubblici (Superior Council of Public Works) has developed the Guidelines for Risk Classification and Management, proposing a multi-level approach to bridge management within a complex geomorphological environment. The guidelines outline a multi-level process that includes surveying the structures, conducting detailed inspections, and assigning risk classes based on hazard, exposure, and vulnerability. Current inspection processes are time-consuming and costly. Therefore, alternative monitoring technologies are crucial. Unmanned aerial vehicles equipped with cameras, laser technologies, and GPS systems offer flexible and cost-effective solutions for visual inspection. These technologies enable the collection of both quantitative and qualitative data, such as size, material properties, and overall condition. In this context, efficient data management and exploration systems are necessary to handle the vast amount of geo-referenced information. Multi-epoch databases play a crucial role in documenting the conditions of bridges and supporting a maintenance and structural health monitoring workflow. These databases can be utilized within a Bridge Management System to aid road managers in decision-making processes. Additionally, 3D exploration platforms provide visual analysis and highlight areas of interest within the structure. This work presents a multi-epoch geo-database that adheres to the Italian guidelines, offering optimized data management and queryability for 2D and 3D information. The entire process is designed using open-source and reproducible solutions.

Glacier monitoring plays a crucial role in understanding the impacts of climate change on these dynamic natural systems. One or more time-lapse cameras are often employed to acquire short-term observations of glacier flow dynamics. However, the lack of multi-camera photogrammetric software packages for multi-temporal 3D scene reconstruction, especially in case of wide camera baselines, hinders the application of Structure-from-Motion techniques to these scenarios. To address this, we present ICEpy4D, a novel Python toolkit designed for 4D monitoring of alpine glaciers using low-cost time-lapse cameras and state-of-the-art computer vision techniques. ICEpy4D leverages deep-learning-based matching algorithms to solve 3D reconstruction with wide camera baselines, making it well-suited for challenging scenarios encountered in mountainous regions. The toolkit offers comprehensive functionalities for multi-epoch monitoring, enabling short-term glacier 3D reconstruction and extraction of relevant information from time-series point clouds, such as volume variations and glacier retreat. In a pilot study on the Belvedere Glacier northern snout (Italian Alps), ICEpy4D estimated glacier volume loss of 63 × 103 m3 of ice and ∼17.5m of retreat. Results showcased the toolkit’s potential for analyzing a glacier ice cliff, with prospects for application to other glaciers with varying characteristics. ICEpy4D is actively being developed as an open-source project at github.com/labmgf-polimi/icepy4d/, promoting ease of extension and customization.

Knowledge about streamflow regimes and values is essential for different activities and situations in which justified decisions must be made. However, streamflow behavior is commonly assumed to be non-linear, being controlled by various mechanisms that act on different temporal and spatial scales, making its estimation challenging. An example is the construction and operation of infrastructures such as dams and reservoirs in rivers. The challenges faced by modelers to correctly describe the impact of dams on hydrological systems are considerable. In this study, an already implemented solution of the MOHID-Land (where MOHID stands for HYDrodinamic MOdel, or MOdelo HIDrodinâmico in Portuguese) model for a natural flow regime in the Ulla River basin was considered as a baseline. The watershed referred to includes three reservoirs. Outflow values were estimated considering a basic operation rule for two of them (run-of-the-river dams) and considering a data-driven model of a convolutional long short-term memory (CLSTM) type for the other (high-capacity dam). The outflow values obtained with the CLSTM model were imposed in the hydrological model, while the hydrological model fed the CLSTM model with the level and the inflow of the reservoir. This coupled system was evaluated daily using two hydrometric stations located downstream of the reservoirs, resulting in an improved performance compared with the baseline application. The analysis of the modeled values with and without reservoirs further demonstrated that considering dams' operations in the hydrological model resulted in an increase in the streamflow during the dry season and a decrease during the wet season but with no differences in the average streamflow. The coupled system is thus a promising solution for improving streamflow estimates in modified catchments.

The adoption of open-source mobile mapping applications in public administration has risen over the last decade due to their interdisciplinary vocation and flexibility in adapting to existing Geographic Information System (GIS) software architectures. This facilitates complex procedures of data collection and management required for transportation and environmental models, emergency management, and maintenance operations. The Ministry of Infrastructure and Transport in Italy requires road-owning agencies to build and maintain a mapping inventory of their road networks, including georeferenced information about streets and ancillary elements, such as traffic signs. Innovative and integrated street-level approaches for the rapid mapping of road entities using open-source mobile mapping tools represent a valuable low-cost solution for the periodical update of road entities inventory. The adoption of these tools allows public administrators to easily consult the road inventory even outside the office, conducting in situ validation and quality evaluation. This work presents a case study focused on the update and management of traffic sign entities of the Road Cadastre of the Province of Piacenza (Italy) using Qfield and Open Data Kit (ODK) Collect as alternatives to the previous traditional survey method that consisted in the use of field papers. A comparison between the adoption of the two mobile apps is conducted, identifying benefits and limitations in terms of both data accuracy and usability. Validation scripts, project and form structure were developed with the perspective of making the entire workflow as reproducible and transparent as possible, sharing details in a dedicated GitHub repository.

Georeferenced reconstructions can help understand the dynamic evolution of the urban context surrounding a historical site, supporting decision-making processes in the field of urban planning. The development of web applications that allow the interaction between 2D and 3D products, as well as their exploration, can facilitate virtual inspections and foster collaboration in digitization of interventions and site evolutions over time. The article discusses how virtual scene reconstructions and visits can provide alternatives to traditional in-situ tourism promotion, through digital storytelling solutions for the exploration of sites. The article also describes how 3D storytelling technologies are currently being used for dissemination cultural heritage sites. The case study of the Castello Farnese, an old XVI century heritage site in Piacenza (Italy), test the adoption of two distinct free and open-source JavaScript WebGL, Potree and Cesium, for the rendering of photogrammetric and laser scanning georeferenced scaled products and for the integration of narrative features such as annotations, camera animations, texts, and other multimedia contents. Potentials and limitations of both tools are discussed in detail, highlighting how they can be implemented for enhancing user experience in virtual tour and exploration of 3D products. In order to guarantee replicability for other case studies, source code of the implemented application is shared on GitHub along with its documentation for contributions.

Image-based monitoring has emerged as a prevalent technique for sensing mountain environments. Monoscopic time-lapse cameras, which rely on digital image correlation to quantify glacier motion, have limitations due to the need for a Digital Elevation Model for deriving 3D flow velocity fields. Multi-camera systems overcome this limitation, as they allow for a 3D reconstruction of the scene. This paper presents a replicable low-cost stereoscopic system designed for 4D glacier monitoring. The system consists of independent and autonomous units, built from off-the-shelves components, such as a DSLR camera, an Arduino microcontroller, and a Raspberry Pi Zero, reducing costs compared to pre-built time-lapse cameras. The units are energetically self-sufficient and resistant to harsh alpine conditions. The system was successfully tested for more than a year to monitor the northwest terminus of the Belvedere Glacier (Italian Alps). Daily stereo-pairs acquired were processed with Structure-from-Motion to derive 3D point clouds of the glacier terminus and estimate glacier retreat and ice volume loss. By combining the information about ice volume loss with ablation estimates and ice flow velocity information, e.g., derived from monoscopic-camera time series, a multi-camera system enables a comprehensive understanding of sub-seasonal glacier dynamics.

The health assessment of strategic infrastructures and bridges represents a critical variable for planning appropriate maintenance operations. The high costs and complexity of traditional periodical monitoring with elevating platforms have driven the search for more efficient and flexible methods. Indeed, recent years have seen the growing diffusion and adoption of non-invasive approaches consisting in the use of Unmanned Aerial Vehicles (UAVs) for applications that range from visual inspection with optical sensors to LiDAR technologies for rapid mapping of the territory. This study defines two different methodologies for bridge inspection. A first approach involving the integration of traditional topographic and GNSS techniques with TLS and photogrammetry with cameras mounted on UAV was compared with a UAV-LiDAR method based on the use of a DJI Matrice 300 equipped with a LiDAR DJI Zenmuse L1 sensor for a manual flight and an automatic one. While the first workflow resulted in a centimetric accurate but time-consuming model, the UAV-LiDAR resulting point cloud’s georeferencing accuracy resulted to be less accurate in the case of the manual flight under the bridge for GNSS signal obstruction. However, a photogrammetric model reconstruction phase made with Ground Control Points and photos taken by the L1-embedded camera improved the overall accuracy of the workflow, that could be employed for flexible low-cost mapping of bridges when medium level accuracy (5–10 cm) is accepted. In conclusion, a solution for integrating interactively final 3D products in a Bridge Management System environment is presented.

Monitoring cracks opening on concrete bridges is a key aspect for structural health assessment. Digital image processing, combined with Unmanned Aerial Vehicles (UAVs) and photogrammetry, allows for non-contact 3D reconstruction of cracks, reducing costs and potential unsafe factors involved in manual inspections. This paper presents a flexible procedure based on UAV photogrammetry for accurate evaluation of cracks geometry, that can be implemented for periodic structural monitoring. Stereo-pair of images, acquired with UAVs close to the cracked surface, are used to build a scaled photogrammetric model through Structure-from-Motion. Cracks are detected on images by image binarization and digital image processing techniques. Thereafter, one single image is used to reconstruct crack 3D geometry, by back-projecting crack image coordinates on a 3D model of the object. This can be built from the current stereo-pair of images, or based on an existing photogrammetric model, in the case of a periodic monitoring set-up. Crack width is accurately estimated in 3D world. The procedure is tested and evaluated in a case study, obtaining millimetric accurate results, which is in line with the average ground sample distance of the images employed. Results highlight the potentials of UAVs and photogrammetry not only for bridge inspections and damages localization, but also for accurately evaluating cracks geometry and helping structural engineers to assess structure health conditions.

The possibility of equipping UAVs with lightweight GNSS receivers in order to estimate the camera position within a photogrammetric block allows for a reduction of the number of Ground Control Points (GCP), saving time during the field work and decreasing operational costs. Additionally, this makes it possible to build photogrammetric models even in morphologically complex areas or in emergency situations. This work is proposing a non-intrusive and low-cost procedure to retrieve the coordinates of the camera projection centre with decimetric accuracy. The method was designed and tested with the quadcopter DJI Matrice 210 V2 drone equipped with a DJI ZENMUSE X5S camera and an Emlid reach M, a low-cost, single-frequency (L1) GNSS receiver. GNSS observations are post-processed in PPK in order to obtain the UAV trajectory. Synchronization between the camera and the GNSS receiver is achieved by looking at the camera triggering timestamps in flight telemetry data, without requiring an electronic connection between camera and the GNSS that may be troublesome with commercial UAVs. Two surveys were carried out, respectively to calibrate and validate the procedure. The validation test evidenced the possibility of obtaining the coordinates of the camera projection centres with decimetric accuracy. The centre of projections can then be employed for GNSS-assisted aerial triangulation as input of the bundle block adjustment. Provided that at least one GCP is used, it is possible to reach centimetric accuracy on the ground.

A fundamental step of UAV photogrammetric processes is to collect Ground Control Points (GCPs) by means of geodetic-quality GNSS receivers or total stations, thus obtaining an absolutely oriented model with a centimetric accuracy. This procedure is usually time-consuming, expensive and potentially dangerous for operators who sometimes need to reach inaccessible areas. UAVs equipped with low-cost GNSS/IMU sensors can provide information about position and attitude of the images. This telemetry information is not enough for a photogrammetric restitution with a centimetric accuracy, but it can be usefully exploited when a lower accuracy is required. The algorithm proposed in this paper aims at improving the quality of this information, in order to introduce it into a direct-photogrammetric process, without collecting GCPs. In particular, the estimation of an optimal trajectory is obtained by combining the camera positions derived from UAV telemetry and from the relative orientation of the acquired images, by means of a least squares adjustment. Then, the resulting trajectory is used as a direct observation of the camera positions into a commercial software, thus replacing the information of GCPs. The algorithm has been tested on different datasets, comparing the classical photogrammetric solution (with GCPs) with the proposed one. These case-studies showed that using the improved trajectory as input to the commercial software (without GCPs) the reconstruction of the three-dimensional model can be improved with respect to the solution computed by using the UAV raw telemetry only.

This case study addresses the experiences of female undergraduate students in the geology and geophysics programs at Universidad de Chile. These majors are part of the Faculty of Physical Sciences and Mathematics (FCFM) and have a relatively large proportion of female representation compared to the other engineering and science majors at FCFM that are dominated by male students. We interviewed 12 female students in geoscience majors to understand (a) the reasons for choosing geoscience as a major and (b) their experiences both at FCFM and in geoscience in an institution with a strong masculine environment that aims to increase women's undergraduate enrollment. We found that the decision to pursue a geoscience career was made during high school, and they maintained this decision during the first years of college, which is heavily focused on mathematics and physics, with no geoscience-related courses. During this early period in college, known as the common core program, students perceived a hostile environment due to high academic demands and gender-based discrimination. Their experiences had a positive shift once they started the geoscience courses in their fifth or sixth semester. The relatively large proportion of female students in the geoscience majors at FCFM creates a positive environment in which the participants developed a sense of belonging in the geoscience community. Students also felt that the feminist movement during 2018 in Chile positively influenced their perspectives on their path at FCFM. These findings give insights for developing strategies to increase early interest, participation, and satisfaction of women in science, technology, engineering, and mathematics (STEM) disciplines at various educational levels.

All over the world, road infrastructures are getting closer to their life cycle and need to be constantly inspected: a consistent number of bridges are structurally deficient, and the risk of collapse can no longer be excluded. In contrast with the past, the interest in structure durability has recently grown rapidly. In order to make bridges durable, it is necessary to carry out ordinary maintenance, preceded by inspection activities, which can be traditionally divided in two categories: destructive and non-destructive (NDT). All the NDT inspections (visual, IR thermography, GPR) can be conducted by using UAS (Unmanned Aerial Systems), a technology that makes bridges inspections quicker, cheaper, objective and repeatable. This study presents the visual inspection and survey of two bridges by using a UAS DJI Mavic 2 Pro, equipped with a 20Mpixel Hasselblad camera that records 60fps 4K video and a 10bit radiometric resolution. Starting from the acquired data, a 3D model of each structure was built by using Structure from Motion (SfM) principles and software. To validate the two models, each of them characterized by a centimetric accuracy, the UAS camera generated cloud of points and was co-registered with the point cloud of a terrestrial laser-scanner using Ground Control Points (GCPs). To make this, CloudCompare comparison software was used; the plugin M3C2 automatically calculates the distance between the points of two compared clouds. Finally, some general rules concerning the UAS main characteristics for inspection of bridges and software for data processing are proposed.

Traditional flow velocity measurements in natural environments require contact with the fluid and are usually costly, time-consuming and, sometimes, even dangerous. Particle Image Velocimetry allows the flow velocity field to be remotely characterized from the shift of intensity patterns of sub-image areas in at least two video frames with a known time lag. Recently, Airborne Image Velocimetry has enabled the surface velocity field of large-scale water bodies to be determined by applying Particle Image Velocimetry on videos recorded by cameras mounted on unmanned aerial vehicles. This work presents a comparison of three Airborne Image Velocimetry approaches: BASESURV, Fudaa-LSPIV and RIVeR. For the evaluation, two nadiral videos were acquired with a low-cost quadcopter. The first was recorded under low flow and seeded conditions, the second during a flood event. According to the results obtained, BASESURV is an accurate and complete research oriented approach but it is time-consuming and neither a graphical interface nor documentation are yet provided. Fudaa-LSPIV is a well-developed software package, with a user-friendly graphical interface and good documentation. However it lacks some features and the source code is closed. RIVeR may be suitable for real time monitoring thanks to the rectification of velocity vectors only. Overall, all the codes are found to be effective in performing Airborne Image Velocimetry in riverine environments.

The effects of aerosol on warm convective cloud cores are evaluated using single cloud and cloud field simulations. Three core definitions are examined: positive vertical velocity (Wcore), supersaturation (RHcore), and positive buoyancy (Bcore). As presented in Part 1 (Heiblum et al., 2019), the property Bcore⊆RHcore⊆Wcore is seen during growth of warm convective clouds. We show that this property is kept irrespective of aerosol concentration. During dissipation core fractions generally decrease with less overlap between cores. However, for clouds that develop in low aerosol concentrations capable of producing precipitation, Bcore and subsequently Wcore volume fractions may increase during dissipation (i.e., loss of cloud mass). The RHcore volume fraction decreases during cloud lifetime and shows minor sensitivity to aerosol concentration. It is shown that a Bcore forms due to two processes: (i) convective updrafts – condensation within supersaturated updrafts and release of latent heat – and (ii) dissipative downdrafts – subsaturated cloudy downdrafts that warm during descent and “undershoot” the level of neutral buoyancy. The former process occurs during cloud growth for all aerosol concentrations. The latter process only occurs for low aerosol concentrations during dissipation and precipitation stages where large mean drop sizes permit slow evaporation rates and subsaturation during descent. The aerosol effect on the diffusion efficiencies plays a crucial role in the development of the cloud and its partition to core and margin. Using the RHcore definition, it is shown that the total cloud mass is mostly dictated by core processes, while the total cloud volume is mostly dictated by margin processes. Increase in aerosol concentration increases the core (mass and volume) due to enhanced condensation but also decreases the margin due to evaporation. In clean clouds larger droplets evaporate much slower, enabling preservation of cloud size, and even increase by detrainment and dilution (volume increases while losing mass). This explains how despite having smaller cores and less mass, cleaner clouds may live longer and grow to larger sizes.

The properties of a warm convective cloud are determined by the competition between the growth and dissipation processes occurring within it. One way to observe and follow this competition is by partitioning the cloud to core and margin regions. Here we look at three core definitions, namely positive vertical velocity (Wcore), supersaturation (RHcore), and positive buoyancy (Bcore), and follow their evolution throughout the lifetime of warm convective clouds. Using single cloud and cloud field simulations with bin-microphysics schemes, we show that the different core types tend to be subsets of one another in the following order: Bcore⊆RHcore⊆Wcore. This property is seen for several different thermodynamic profile initializations and is generally maintained during the growing and mature stages of a cloud's lifetime. This finding is in line with previous works and theoretical predictions showing that cumulus clouds may be dominated by negative buoyancy at certain stages of their lifetime. The RHcore–Wcore pair is most interchangeable, especially during the growing stages of the cloud. For all three definitions, the core–shell model of a core (positive values) at the center of the cloud surrounded by a shell (negative values) at the cloud periphery applies to over 80 % of a typical cloud's lifetime. The core–shell model is less appropriate in larger clouds with multiple cores displaced from the cloud center. Larger clouds may also exhibit buoyancy cores centered near the cloud edge. During dissipation the cores show less overlap, reduce in size, and may migrate from the cloud center.

This work aims at presenting the use of new technologies in the field of forensic engineering. In particular, the use of UAV photogrammetry and laser scanning is compared with the traditional methods of surveying an accident site. In this framework, surveys must be carried out promptly, executed in a short time and performed so that the greatest possible amount of information is collected with sufficient accuracy to avoid the possibility of neglecting details once that the scene is no longer preserved. The combination of modern surveying techniques such UAV photogrammetry and laser scanning can properly fulfill these requirements. An experimental test has been arranged and instruments, procedures, settings, practical limits and results have been evaluated and compared with respect to the usual way of performing the survey for forensic purposes. In particular, both qualitative and quantitative considerations are given, assessing the completeness of the reconstructed model, the statistical evaluation of the errors and the accuracy achieved.

Fisheye camera installed on-board mass market UAS are becoming very popular and it is more and more frequent the use of such platforms for photogrammetric purposes. The interest of wide-angles images for 3D modelling is confirmed by the introduction of fisheye models in several commercial software packages. The paper exploits the different mathematical models implemented in the most famous commercial photogrammetric software packages, highlighting the different processing pipelines and analysing the achievable results in terms of checkpoint residuals, as well as the quality of the delivered 3D point clouds. A two-step approach based on the creation of undistorted images has been tested too. An experimental test has been carried out using a Parrot Bebop 2 UAS by performing a flight over an historical complex located near Piacenza (Northern Italy), which is characterized by the simultaneous presence of horizontal, vertical and oblique surfaces. Different flight configurations have been tested to evaluate the potentiality and possible drawbacks of the previously mentioned UAS platform. Results confirmed that the fisheye images acquired with the Parrot Bebop 2 are suitable for 3D modelling, ensuring accuracies of the photogrammetric blocks of the order of the GSD (about 0.05 m normal to the optic axis in case of a flight height equal to 35 m). The generated point clouds have been compared to a reference scan, acquired by means of a MS60 MultiStation, resulting in differences below 0.05 in all directions.

A pure GNSS navigation is often unreliable in urban areas because of the presence of obstructions, thus preventing a correct reception of the satellite signal. The bridging between GNSS outages, as well as the vehicle attitude reconstruction, can be recovered by using complementary information, such as visual data acquired by RGB-D or RGB cameras. In this work, the possibility of integrating low-cost GNSS and visual data by means of an extended Kalman filter has been investigated. The focus is on the comparison between the use of RGB-D or RGB cameras. In particular, a Microsoft Kinect device (second generation) and a mirrorless Canon EOS M RGB camera have been compared. The former is an interesting RGB-D camera because of its low-cost, easiness of use and raw data accessibility. The latter has been selected for the high-quality of the acquired images and for the possibility of mounting fixed focal length lenses with a lower weight and cost with respect to a reflex camera. The designed extended Kalman filter takes as input the GNSS-only trajectory and the relative orientation between subsequent pairs of images. Depending on the visual data acquisition system, the filter is different because RGB-D cameras acquire both RGB and depth data, allowing to solve the scale problem, which is instead typical of image-only solutions. The two systems and filtering approaches were assessed by ad-hoc experimental tests, showing that the use of a Kinect device for supporting a u-blox low-cost receiver led to a trajectory with a decimeter accuracy, that is 15 % better than the one obtained when using the Canon EOS M camera.

Coastal defence structures are often constructed to prevent beach erosion. However, poorly designed structures may cause serious erosion problems in the downdrift direction. Morphological models are useful tools to predict such impacts and assess the efficiency of defence structures for different scenarios. Nevertheless, morphological modelling is still a topic under intense research effort. The processes simulated by a morphological model depend on model complexity. For instance, undertow currents are neglected in coastal area models (2DH), which is a limitation for simulating the evolution of beach profiles for long periods. Model limitations are generally overcome by predefining invariant equilibrium profiles that are allowed to shift offshore or onshore. A more flexible approach is described in this paper, which can be generalised to 3-D models. The present work is based on the coupling of the MOHID modelling system and the SWAN wave model. The impacts of different designs of detached breakwaters and groynes were simulated in a schematic beach configuration following a 2DH approach. The results of bathymetry evolution are in agreement with the patterns found in the literature for several existing structures. The model was also tested in a 3-D test case to simulate the formation of sandbars by undertow currents. The findings of this work confirmed the applicability of the MOHID modelling system to study sediment transport and morphological changes in coastal zones under the combined action of waves and currents. The same modelling methodology was applied to a coastal zone (Costa da Caparica) located at the mouth of a mesotidal estuary (Tagus Estuary, Portugal) to evaluate the hydrodynamics and sediment transport both in calm water conditions and during events of highly energetic waves. The MOHID code is available in the GitHub repository.

Understanding aerosol effects on deep convective clouds and the derived effects on the radiation budget and rain patterns can largely contribute to estimations of climate uncertainties. The challenge is difficult in part because key microphysical processes in the mixed and cold phases are still not well understood. For deep convective clouds with a warm base, understanding aerosol effects on the warm processes is extremely important as they set the initial and boundary conditions for the cold processes. Therefore, the focus of this study is the warm phase, which can be better resolved. The main question is: How do aerosol-derived changes in the warm phase affect the properties of deep convective cloud systems? To explore this question, we used a weather research and forecasting (WRF) model with spectral bin microphysics to simulate a deep convective cloud system over the Marshall Islands during the Kwajalein Experiment (KWAJEX). The model results were validated against observations, showing similarities in the vertical profile of radar reflectivity and the surface rain rate. Simulations with larger aerosol loading resulted in a larger total cloud mass, a larger cloud fraction in the upper levels, and a larger frequency of strong updrafts and rain rates. Enlarged mass both below and above the zero temperature level (ZTL) contributed to the increase in cloud total mass (water and ice) in the polluted runs. Increased condensation efficiency of cloud droplets governed the gain in mass below the ZTL, while both enhanced condensational and depositional growth led to increased mass above it. The enhanced mass loading above the ZTL acted to reduce the cloud buoyancy, while the thermal buoyancy (driven by the enhanced latent heat release) increased in the polluted runs. The overall effect showed an increased upward transport (across the ZTL) of liquid water driven by both larger updrafts and larger droplet mobility. These aerosol effects were reflected in the larger ratio between the masses located above and below the ZTL in the polluted runs. When comparing the net mass flux crossing the ZTL in the clean and polluted runs, the difference was small. However, when comparing the upward and downward fluxes separately, the increase in aerosol concentration was seen to dramatically increase the fluxes in both directions, indicating the aerosol amplification effect of the convection and the affected cloud system properties, such as cloud fraction and rain rate.

The task of conservation and management of cultural heritage is quite central in Italy, which lists a high number of beautiful architectures. A quick and precise survey may be requested in case of calamity. In the present paper, the most commonly used survey techniques are discussed, focusing on their applications for the conservation of the artistic heritage in case of emergency. Particular attention is given to Unmanned Aerial Systems (UAS) photogrammetry and its potentiality in obtaining good results in terms of speed, cheapness, precision and accuracy, assuring at the same time the safety of the operators in critical situations (e.g. natural disasters). A case study, realized at the Castle of Casalbagliano (Alessandria, Italy), is discussed. Different image block configurations and acquisition geometries (nadiral and oblique images) have been exploited, with the aim of defining useful guidelines for emergencies UAS survey of partially collapsed structures. An application to a significative case study is introduced.

New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients). Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field), to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB) and false color (NIR-RG) images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM) of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

Since its launch on the market, Microsoft Kinect sensor has represented a great revolution in the field of low cost navigation, especially for indoor robotic applications. In fact, this system is endowed with a depth camera, as well as a visual RGB camera, at a cost of about 200$. The characteristics and the potentiality of the Kinect sensor have been widely studied for indoor applications. The second generation of this sensor has been announced to be capable of acquiring data even outdoors, under direct sunlight. The task of navigating passing from an indoor to an outdoor environment (and vice versa) is very demanding because the sensors that work properly in one environment are typically unsuitable in the other one. In this sense the Kinect could represent an interesting device allowing bridging the navigation solution between outdoor and indoor. In this work the accuracy and the field of application of the new generation of Kinect sensor have been tested outdoor, considering different lighting conditions and the reflective properties of the emitted ray on different materials. Moreover, an integrated system with a low cost GNSS receiver has been studied, with the aim of taking advantage of the GNSS positioning when the satellite visibility conditions are good enough. A kinematic test has been performed outdoor by using a Kinect sensor and a GNSS receiver and it is here presented.

We investigate snow depth distribution at peak accumulation over a small Alpine area ( ∼ 0.3 km2) using photogrammetry-based surveys with a fixed-wing unmanned aerial system (UAS). These devices are growing in popularity as inexpensive alternatives to existing techniques within the field of remote sensing, but the assessment of their performance in Alpine areas to map snow depth distribution is still an open issue. Moreover, several existing attempts to map snow depth using UASs have used multi-rotor systems, since they guarantee higher stability than fixed-wing systems. We designed two field campaigns: during the first survey, performed at the beginning of the accumulation season, the digital elevation model of the ground was obtained. A second survey, at peak accumulation, enabled us to estimate the snow depth distribution as a difference with respect to the previous aerial survey. Moreover, the spatial integration of UAS snow depth measurements enabled us to estimate the snow volume accumulated over the area. On the same day, we collected 12 probe measurements of snow depth at random positions within the case study to perform a preliminary evaluation of UAS-based snow depth. Results reveal that UAS estimations of point snow depth present an average difference with reference to manual measurements equal to −0.073 m and a RMSE equal to 0.14 m. We have also explored how some basic snow depth statistics (e.g., mean, standard deviation, minima and maxima) change with sampling resolution (from 5 cm up to ∼ 100 m): for this case study, snow depth standard deviation (hence coefficient of variation) increases with decreasing cell size, but it stabilizes for resolutions smaller than 1 m. This provides a possible indication of sampling resolution in similar conditions.

Nowadays, devices and applications that require navigation solutions are continuously growing. For instance, consider the increasing demand of mapping information or the development of applications based on users’ location. In some case it could be sufficient an approximate solution (e.g. at room level), but in the large amount of cases a better solution is required. The navigation problem has been solved from a long time using Global Navigation Satellite System (GNSS). However, it can be unless in obstructed areas, such as in urban areas or inside buildings. An interesting low cost solution is photogrammetry, assisted using additional information to scale the photogrammetric problem and recovering a solution also in critical situation for image-based methods (e.g. poor textured surfaces). In this paper, the use of assisted photogrammetry has been tested for both outdoor and indoor scenarios. Outdoor navigation problem has been faced developing a positioning system with Ground Control Points extracted from urban maps as constrain and tie points automatically extracted from the images acquired during the survey. The proposed approach has been tested under different scenarios, recovering the followed trajectory with an accuracy of 0.20 m. For indoor navigation a solution has been thought to integrate the data delivered by Microsoft Kinect, by identifying interesting features on the RGB images and re-projecting them on the point clouds generated from the delivered depth maps. Then, these points have been used to estimate the rotation matrix between subsequent point clouds and, consequently, to recover the trajectory with few centimeters of error.

Scene's 3D modelling, gesture recognition and motion tracking are fields in rapid and continuous development which have caused growing demand on interactivity in video-game and e-entertainment market. Starting from the idea of creating a sensor that allows users to play without having to hold any remote controller, the Microsoft Kinect device was created. The Kinect has always attract researchers in different fields, from robotics to Computer Vision (CV) and biomedical engineering as well as third-party communities that have released several Software Development Kit (SDK) versions for Kinect in order to use it not only as a game device but as measurement system. Microsoft Kinect Fusion control libraries (firstly released in March 2013) allow using the device as a 3D scanning and produce meshed polygonal of a static scene just moving the Kinect around. A drawback of this sensor is the geometric quality of the delivered data and the low repeatability. For this reason the authors carried out some investigation in order to evaluate the accuracy and repeatability of the depth measured delivered by the Kinect. The paper will present a throughout calibration analysis of the Kinect imaging sensor, with the aim of establishing the accuracy and precision of the delivered information: a straightforward calibration of the depth sensor in presented and then the 3D data are correct accordingly. Integrating the depth correction algorithm and correcting the IR camera interior and exterior orientation parameters, the Fusion Libraries are corrected and a new reconstruction software is created to produce more accurate models.

UAVs systems represent a flexible technology able to collect a big amount of high resolution information, both for metric and interpretation uses. In the frame of experimental tests carried out at Dept. ICA of Politecnico di Milano to validate vector-sensor systems and to assess metric accuracies of images acquired by UAVs, a block of photos taken by a fixed wing system is triangulated with several software. The test field is a rural area included in an Italian Park ("Parco Adda Nord"), useful to study flight and imagery performances on buildings, roads, cultivated and uncultivated vegetation. The UAV SenseFly, equipped with a camera Canon Ixus 220HS, flew autonomously over the area at a height of 130 m yielding a block of 49 images divided in 5 strips. Sixteen pre-signalized Ground Control Points, surveyed in the area through GPS (NRTK survey), allowed the referencing of the block and accuracy analyses. Approximate values for exterior orientation parameters (positions and attitudes) were recorded by the flight control system. The block was processed with several software: Erdas-LPS, EyeDEA (Univ. of Parma), Agisoft Photoscan, Pix4UAV, in assisted or automatic way. Results comparisons are given in terms of differences among digital surface models, differences in orientation parameters and accuracies, when available. Moreover, image and ground point coordinates obtained by the various software were independently used as initial values in a comparative adjustment made by scientific in-house software, which can apply constraints to evaluate the effectiveness of different methods of point extraction and accuracies on ground check points.

Ground Penetrating Radar (GPR) is an active instrument often used to detect underground utility locations up to a few meters. To perform a three-dimensional reconstruction of position and geometry of the surveyed features, the accuracy of GPR position data has to be in the order of 20-30 cm. This requirement is easily attainable using a GNSS system in open sky conditions, while in urban areas signal leakage is frequent, leading to inadequate position accuracy or even positioning failure. Usually, in those cases, GPS/INS navigation systems are used, but they are quite an expensive solution. To determine the position of the GPR, another strategy could be utilizing a photogrammetric method that uses information extracted from a large scale map, often available for towns. In this paper, the characteristics of this procedure and some possible configurations of cameras are described. Results obtained from preliminary tests are hereby presented and discussed to demonstrate that the proposed methodology could achieve the required precision.

The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs) is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment): it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes). Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs) were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS) and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.