Archaeological site monitoring: UAV photogrammetry can be an answer

During archaeological excavations it is important to monitor the new excavated areas and findings day by day in order to be able to plan future excavation activities. At present, this daily activity is usually performed by using total stations, which survey the changes of the archaeological site: the surveyors are asked to produce day by day draft plans and sections which allow archaeologists to plan their future activities. The survey is realized during the excavations or just at the end of every working day and drawings have to be produced as soon as possible in order to allow the comprehension of the work done and to plan the activities for the following day. By using this technique, all the measurements, even those not necessary for the day after, have to be acquired in order to avoid a ‘loss of memory'. A possible alternative to this traditional approach is aerial photogrammetry, if the images can be acquired quickly and at a taken distance able to guarantee the necessary accuracy of a few centimeters. Today the use of UAVs (Unmanned Aerial Vehicles) can be considered a proven technology able to acquire images at distances ranging from 4 m up to 20 m: and therefore as a possible monitoring system to provide the necessary information to the archaeologists day by day. The control network, usually present at each archaeological site, can give the stable control points useful for orienting a photogrammetric block acquired by using an UAV equipped with a calibrated digital camera and a navigation control system able to drive the aircraft following a pre-planned flight scheme. Modern digital photogrammetric software can solve for the block orientation and generate a DSM automatically, allowing rapid orthophoto generation and the possibility of producing sections and plans. The present paper describes a low cost UAV system realized by the research group of the Politecnico di Torino and tested on a Roman villa archaeological site located in Aquileia (Italy), a well-known UNESCO WHL site. The results of automatic orientation and orthophoto production are described in terms of their accuracy and the completeness of information guaranteed for archaeological site excavation managemen

Ice Detection on Aircraft Surface Using Machine Learning Approaches Based on Hyperspectral and Multispectral Images

Aircraft ground de-icing operations play a critical role in flight safety. However, to handle the aircraft de-icing, a considerable quantity of de-icing fluids is commonly employed. Moreover, some pre-flight inspections are carried out with engines running; thus, a large amount of fuel is wasted, and CO2 is emitted. This implies substantial economic and environmental impacts. In this context, the European project (reference call: MANUNET III 2018, project code: MNET18/ICT-3438) called SEI (Spectral Evidence of Ice) aims to provide innovative tools to identify the ice on aircraft and improve the efficiency of the de-icing process. The project includes the design of a low-cost UAV (uncrewed aerial vehicle) platform and the development of a quasi-real-time ice detection methodology to ensure a faster and semi-automatic activity with a reduction of applied operating time and de-icing fluids. The purpose of this work, developed within the activities of the project, is defining and testing the most suitable sensor using a radiometric approach and machine learning algorithms. The adopted methodology consists of classifying ice through spectral imagery collected by two different sensors: multispectral and hyperspectral camera. Since the UAV prototype is under construction, the experimental analysis was performed with a simulation dataset acquired on the ground. The comparison among the two approaches, and their related algorithms (random forest and support vector machine) for image processing, was presented: practical results show that it is possible to identify the ice in both cases. Nonetheless, the hyperspectral camera guarantees a more reliable solution reaching a higher level of accuracy of classified iced surfaces

Un nuovo approccio per la gestione delle risorse idriche sotterranee in ambito transfrontaliero: Prog. ALCOTRA-ALIRHYS

In seguito ai mutamenti climatici degli ultimi anni sono aumentati i rischi legati alle risorse idriche sotterranee, relativamente alle quali, una buona conoscenza finalizzata alla loro gestione e ottimizzazione è l'obiettivo del progetto, realizzato nel territorio tra Cuneo e Nizza a partire da marzo 2013. Il progetto prevede numerose acquisizioni sul campo di dati legati alle fonti di approvvigionamento delle risorse idriche mediante il monitoraggio di parametri chimici, fisici e isotopici di oltre 20 sorgenti, particolarmente significative, da correlare con i valori di precipitazione registrati da stazioni meteo e da nivo-pluviografi interrati appositamente installati. I dati vengono raccolti e gestiti in un Sistema Informativo Territoriale, adeguatamente progettato e strutturato secondo le regole dei database, per consentirne l'indipendenza dal software (commerciale o freeware), la corretta comprensione e procedure semplici di aggiornamento/modifica futuri. I dati di diversa natura raccolti dalle unità coinvolte vengono archiviati in un unico ambiente condiviso per una efficace connessione territoriale che consenta una corretta analisi dinamica delle informazioni contenute. Il SIT raccoglie la cartografia di base e i modelli altimetrici, a diverse scale e formati, dei territori dei due Stati in modo da integrare i differenti sistemi di riferimento planimetrici e altimetrici e i diversi tipi di proiezione cartografica, secondo le indicazioni INSPIRE. Il SIT prodotto è utilizzabile per l'aggiornamento continuo e per la diffusione dei risultati secondo tre livelli: traduzione in WebGIS, tramite la piattaforma open-source Geonode, per la condivisione delle informazioni e della cartografia automatica elaborabile, consentendo l'interazione da parte di utenti esterni; condivisione remota di dati vettoriali tramite Web Feature Service o Web Coverage Service; produzione dinamica di mappe tramite Web Map Service. La diffusione dei risultati di ALIRHYS viene conseguita mediante un sito internet che raccoglie, descrive e mette a disposizione dati e risultati in corso d'opera (attualmente) e finali e la realizzazione di un documentario

Inertial sensors for smartphones navigation

The advent of smartphones and tablets, means that we can constantly get informa- tion on our current geographical location. These devices include not only GPS/GNSS chipsets but also mass-market inertial platforms that can be used to plan activities, share locations on social networks, and also to perform positioning in indoor and outdoor scenarios. This paper shows the performance of smartphones and their inertial sensors in terms of gaining information about the user’s current geographical loca- tion considering an indoor navigation scenario. Tests were carried out to determine the accuracy and precision obtainable with internal and external sensors. In terms of the attitude and drift estimation with an updating interval equal to 1 s, 2D accuracies of about 15 cm were obtained with the images. Residual benefits were also obtained, however, for large intervals, e.g. 2 and 5 s, where the accuracies decreased to 50 cm and 2.2 m, respectively

DIRECT PHOTOGRAMMETRY USING UAV: TESTS AND FIRST RESULTS

In recent years, the quality of high resolution acquisition platforms for geomatic applications has decidedly increased, especially in the performance of the sensors devoted to image acquisition.<br><br> The small size of these new sensors combined with the increase in resolution allows them to be easily mounted onto Unmanned Aerial Vehicles (UAVs); in particular, calibrated, very-high-resolution digital cameras for photogrammetric purposes such as digital terrain model (DTM) and digital surface model (DSM) extraction, orthophotos, and map realization have been used. In this case, the UAV performance allows a high quality product to be obtained, considering the pixel size and the accuracy of the DTM/DSM which could be obtained with automatic procedures.<br><br> Several navigation sensors (GPS/GNSS and IMU-MEMS) are embedded into UAVs in order to realize autonomous flight. The quality of these sensors, in terms of accuracy, depends on the model of UAV and its purpose. The navigation solution (position and attitude) is estimated by the internal UAV sensor and can be employed to directly georeference the images, in order to produce an quick and easy description and analysis of the overlooked area. This is a good condition for semi-automatic procedures using a bundle-block photogrammetric approach. But is it possible to realize a direct photogrammetry? And what are the limits?<br><br> Several tests were carried out over different areas and in different conditions using three different UAVs belonging to the Geomatics group of the Politecnico di Torino.<br><br> In this paper, an investigation of the limits of some commercial UAVs is reported, defining a dedicated procedure to valuate their performance, especially considering the use of UAVs for direct photogrammetry

Positioning Techniques with Smartphone Technology: Performances and Methodologies in Outdoor and Indoor Scenarios

Smartphone technology is widespread both in the academy and in the commercial world. Almost every people have today a smartphone in their pocket, that are not only used to call other people but also to share their location on social networks or to plan activities. Today with a smartphone we can compute our position using the sensors settled inside the device that may also include accelerometers, gyroscopes and magnetometers, teslameter, proximity sensors, barometer, and GPS/GNSS chipset. In this chapter we want to analyze the state-of-the-art of the positioning with smartphone technology, considering both outdoor and indoor scenarios. Particular attention will be paid to this last situation, where the accuracy can be improved fusing information coming from more than one sensor. In particular, we will investigate an innovative method of image recognition based (IRB) technology, particularly useful in GNSS denied environment, taking into account the two main problems that arise when the IRB positioning methods are considered: the first one is the optimization of the battery, that implies the minimization of the frame rate, and secondly the latencies due to image processing for visual search solutions, required by the size of the database with the 3D environment images

Cartographic data harmonisation for a cross-border project development

An essential support for environmental monitoring activities is a rigorous definition of an homogeneous cartographic system required to correctly georeference the acquired data. Furthermore, since the 2007, the European INSPIRE Directive (INfrastructure for Spatial InfoRmation in the European Community) affirms the necessity to harmonize the European maps for permitting cross-border analysis. For satisfying these requirements, the authors have developed a procedure for the cartographic harmonisation in the cross border area studied during in the European project ALCOTRA (Alpes Latines- COopération TRAnsfrontalière) – ALIRHyS (Alpes Latines- Individuation Resources Hydriques Souterraines). It concerns the hydrogeological study of various springs and other water resources in an area between Italy and France including their constitution in a cross-border system. The basic cartographic information is obtained from existing national maps (Italian and French data), which use different reference systems and are produced from different data acquisitions and processes. In this paper the authors describe the methods used to obtain well-harmonised middle-scale maps (aerial orthophotos, Digital Terrain Model and digital maps). The processing has been performed using GIS software or image analysis software in order to obtain useful and correct cartographic support for the monitoring data, even if the obtained maps could be further analysed or refined in future works

Mapping Riparian Habitats of Natura 2000 Network (91E0*, 3240) at Individual Tree Level Using UAV Multi-Temporal and Multi-Spectral Data

Riparian habitats provide a series of ecological services vital for the balance of the environment, and are niches and resources for a wide variety of species. Monitoring riparian environments at the intra-habitat level is crucial for assessing and preserving their conservation status, although it is challenging due to their landscape complexity. Unmanned aerial vehicles (UAV) and multi-spectral optical sensors can be used for very high resolution (VHR) monitoring in terms of spectral, spatial, and temporal resolutions. In this contribution, the vegetation species of the riparian habitat (91E0*, 3240 of Natura 2000 network) of North-West Italy were mapped at individual tree (ITD) level using machine learning and a multi-temporal phenology-based approach. Three UAV flights were conducted at the phenological-relevant time of the year (epochs). The data were analyzed using a structure from motion (SfM) approach. The resulting orthomosaics were segmented and classified using a random forest (RF) algorithm. The training dataset was composed of field-collected data, and was oversampled to reduce the effects of unbalancing and size. Three-hundred features were computed considering spectral, textural, and geometric information. Finally, the RF model was cross-validated (leave-one-out). This model was applied to eight scenarios that differed in temporal resolution to assess the role of multi-temporality over the UAV’s VHR optical data. Results showed better performances in multi-epoch phenology-based classification than single-epochs ones, with 0.71 overall accuracy compared to 0.61. Some classes, such as Pinus sylvestris and Betula pendula, are remarkably influenced by the phenology-based multi-temporality: the F1-score increased by 0.3 points by considering three epochs instead of two

Bathymetric detection of fluvial environments through UASs and machine learning systems

In recent decades, photogrammetric and machine learning technologies have become essential for a better understanding of environmental and anthropic issues. The present work aims to respond one of the most topical problems in environmental photogrammetry, i.e., the automatic classification of dense point clouds using the machine learning (ML) technology for the refraction correction on the fluvial water table. The applied methodology for the acquisition of multiple photogrammetric flights was made through UAV drones, also in RTK configuration, for various locations along the Orco River, sited in Piedmont (Italy) and georeferenced with GNSS—RTK topographic method. The authors considered five topographic fluvial cross-sections to set the correction methodology. The automatic classification in ML has found a valid identification of different patterns (Water, Gravel bars, Vegetation, and Ground classes), in specific hydraulic and geomatic conditions. The obtained results about the automatic classification and refraction reduction led us the definition of a new procedure, with precise conditions of validity

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio