FROM 3D SURVEY TO DIGITAL REALITY OF A COMPLEX ARCHITECTURE: A DIGITAL WORKFLOW FOR CULTURAL HERITAGE PROMOTION

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

Mapping and classification of ecologically sensitive marine habitats using unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA)

Nowadays, emerging technologies, such as long-range transmitters, increasingly miniaturized components for positioning, and enhanced imaging sensors, have led to an upsurge in the availability of new ecological applications for remote sensing based on unmanned aerial vehicles (UAVs), sometimes referred to as “drones”. In fact, structure-from-motion (SfM) photogrammetry coupled with imagery acquired by UAVs offers a rapid and inexpensive tool to produce high-resolution orthomosaics, giving ecologists a new way for responsive, timely, and cost-effective monitoring of ecological processes. Here, we adopted a lightweight quadcopter as an aerial survey tool and object-based image analysis (OBIA) workflow to demonstrate the strength of such methods in producing very high spatial resolution maps of sensitive marine habitats. Therefore, three different coastal environments were mapped using the autonomous flight capability of a lightweight UAV equipped with a fully stabilized consumer-grade RGB digital camera. In particular we investigated a Posidonia oceanica seagrass meadow, a rocky coast with nurseries for juvenile fish, and two sandy areas showing biogenic reefs of Sabelleria alveolata. We adopted, for the first time, UAV-based raster thematic maps of these key coastal habitats, produced after OBIA classification, as a new method for fine-scale, low-cost, and time saving characterization of sensitive marine environments which may lead to a more effective and efficient monitoring and management of natural resource

Photogrammetric 3D model via smartphone GNSS sensor. Workflow, error estimate, and best practices

Geotagged smartphone photos can be employed to build digital terrain models using structure from motion-multiview stereo (SfM-MVS) photogrammetry. Accelerometer, magnetometer, and gyroscope sensors integrated within consumer-grade smartphones can be used to record the orientation of images, which can be combined with location information provided by inbuilt global navigation satellite system (GNSS) sensors to geo-register the SfM-MVS model. The accuracy of these sensors is, however, highly variable. In this work, we use a 200 m-wide natural rocky cliff as a test case to evaluate the impact of consumer-grade smartphone GNSS sensor accuracy on the registration of SfM-MVS models. We built a high-resolution 3D model of the cliff, using an unmanned aerial vehicle (UAV) for image acquisition and ground control points (GCPs) located using a differential GNSS survey for georeferencing. This 3D model provides the benchmark against which terrestrial SfM-MVS photogrammetry models, built using smartphone images and registered using built-in accelerometer/gyroscope and GNSS sensors, are compared. Results show that satisfactory post-processing registrations of the smartphone models can be attained, requiring: (1) wide acquisition areas (scaling with GNSS error) and (2) the progressive removal of misaligned images, via an iterative process of model building and error estimation

A novel distributed architecture for UAV indoor navigation

Abstract In the last decade, different indoor flight navigation systems for small Unmanned Aerial Vehicles (UAVs) have been investigated, with a special focus on different configurations and on sensor technologies. The main idea of this paper is to propose a distributed Guidance Navigation and Control (GNC) system architecture, based on Robotic Operation System (ROS) for light weight UAV autonomous indoor flight. The proposed framework is shown to be more robust and flexible than common configurations. A flight controller and companion computer running ROS for control and navigation are also included in the section. Both hardware and software diagrams are given to show the complete architecture. Further works will be based on the experimental validation of the proposed configuration by indoor flight tests

Unmanned Aircraft System Assessments of Landslide Safety for Transportation Corridors

An assessment of unmanned aircraft systems (UAS) concluded that current, off-the-shelf UAS aircraft and cameras can be effective for creating the digital surface models used to evaluate rock-slope stability and landslide risk along transportation corridors. The imagery collected with UAS can be processed using a photogrammetry technique called Structure-from-Motion (SfM) which generates a point cloud and surface model, similar to terrestrial laser scanning (TLS). We treated the TLS data as our control, or “truth,” because it is a mature and well-proven technology. The comparisons of the TLS surfaces and the SFM surfaces were impressive – if not comparable is many cases. Thus, the SfM surface models would be suitable for deriving slope morphology to generate rockfall activity indices (RAI) for landslide assessment provided the slopes. This research also revealed that UAS are a safer alternative to the deployment and operation of TLS operating on a road shoulder because UAS can be launched and recovered from a remote location and capable of imaging without flying directly over the road. However both the UAS and TLS approaches still require traditional survey control and photo targets to accurately geo-reference their respective DSM.List of Figures ...................................................................................................... vi List of Abbreviations ......................................................................................... vii Acknowledgments ................................................................................................ x Executive Summary ............................................................................................. xi CHAPTER 1 INTRODUCTION .......................................................................... 1 CHAPTER 2 LITERATURE REVIEW ................................................................ 4 2.1 Landslide Hazards .................................................................................... 4 2.2 Unmanned Aircraft Systems Remote Sensing.......................................... 6 2.3 Structure From Motion (SfM) .................................................................. 7 2.4 Lidar terrain mapping ............................................................................... 8 CHAPTER 3 STUDY SITE/DATA .................................................................. 11 CHAPTER 4 METHODS ................................................................................ 13 4.1 Data Collection ............................................................................................. 13 4.1.1 Survey Control ..................................................................................... 14 4.1.2 TLS Surveys ........................................................................................ 16 4.1.3 UAS Imagery ....................................................................................... 17 4.1.4 Terrestrial Imagery Acquisition ........................................................... 19 4.2 Data Processing ............................................................................................ 20 4.2.1 Survey Control ..................................................................................... 20 4.2.2 TLS Processing .................................................................................... 20 4.2.3 SfM Processing .................................................................................... 21 4.2.4 Surface Generation .............................................................................. 22 4.3 Quality Evaluation ........................................................................................ 23 4.3.1 Completeness ....................................................................................... 23 4.3.2 Data Density/Resolution ...................................................................... 23 4.3.3 Accuracy Assessment .......................................................................... 23 4.3.2 Surface Morphology Analysis ............................................................. 24 4.2.6 Data Visualization ............................................................................... 25 CHAPTER 5 RESULTS ................................................................................. 27 v 5.1 UTIC DSM evaluation.................................................................................. 27 5.1.1 Completeness evaluation ..................................................................... 28 5.1.2 Data Density Evaluation ...................................................................... 29 5.1.3 Accuracy Evaluation............................................................................ 30 5.2 Geomorphological Evaluation ...................................................................... 32 CHAPTER 6 DISCUSSION ............................................................................ 35 6.1 Evaluation of UAS efficiencies .................................................................... 35 6.2 DSM quality and completeness .................................................................... 37 6.3 Safety and operational considerations .......................................................... 37 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS ................................ 40 7.1 Technology Transfer..................................................................................... 41 7.1.1 Publications ......................................................................................... 41 7.1.2 Presentations ........................................................................................ 42 7.1.3 Multi-media outreach .......................................................................... 43 6.4 Integration of UAS and TLS data ................................................................. 44 REFERENCES .............................................................................................. 4

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research

COMPARISON OF LOW COST PHOTOGRAMMETRIC SURVEY WITH TLS AND LEICA PEGASUS BACKPACK 3D MODELS

This paper considers Leica backpack and photogrammetric surveys of a mediaeval bastion in Padua, Italy. Furhtermore, terrestrial laser scanning (TLS) survey is considered in order to provide a state of the art reconstruction of the bastion. Despite control points are typically used to avoid deformations in photogrammetric surveys and ensure correct scaling of the reconstruction, in this paper a different approach is considered: this work is part of a project aiming at the development of a system exploiting ultra-wide band (UWB) devices to provide correct scaling of the reconstruction. In particular, low cost Pozyx UWB devices are used to estimate camera positions during image acquisitions. Then, in order to obtain a metric reconstruction, scale factor in the photogrammetric survey is estimated by comparing camera positions obtained from UWB measurements with those obtained from photogrammetric reconstruction. Compared with the TLS survey, the considered photogrammetric model of the bastion results in a RMSE of 21.9cm, average error 13.4cm, and standard deviation 13.5cm. Excluding the final part of the bastion left wing, where the presence of several poles make reconstruction more difficult, (RMSE) fitting error is 17.3cm, average error 11.5cm, and standard deviation 9.5cm. Instead, comparison of Leica backpack and TLS surveys leads to an average error of 4.7cm and standard deviation 0.6cm (4.2 cm and 0.3 cm, respectively, by excluding the final part of the left wing)

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