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Three-Dimensional Ground Penetrating Radar (3D GPR) detects subsurface targets non-destructively, rapidly, and continuously. The complex environment around urban roads affects the positioning accuracy of 3D GPR. The positioning accuracy directly affects the data quality, as inaccurate positioning can lead to distortion and misalignment of 3D GPR data. This paper proposed a multi-level robust positioning method to improve the positioning accuracy of 3D GPR in dense urban areas in order to obtain more accurate underground data. In environments with good GNSS signals, fast and high-precision positioning can be achieved based on GNSS data using differential GNSS technology; in scenes with weak GNSS signals, high-precision positioning of subsurface data can be achieved by using GNSS and IMU as well as using GNSS/INS tightly coupled solution technology; in scenes with no GNSS signals, SLAM technology is used for positioning based on INS data and 3D point cloud data. In summary, this method ensures a positioning accuracy of 3D GPR better than 10 cm and high-quality 3D images of underground urban roads in any environment. This provides data support for urban road underground structure surveys and has broad application prospects in underground disease detection and prevention.

Urban planning and management need accurate three-dimensional (3D) data such as light detection and ranging (LiDAR) point clouds. The mobile laser scanning (MLS) data, with up to millimeter-level accuracy and point density of a few thousand points/m2, have gained increasing attention in urban applications. Substantial research has been conducted in the past decade. This paper conducted a comprehensive survey of urban applications and key techniques based on MLS point clouds. We first introduce the key characteristics of MLS systems and the corresponding point clouds, and present the challenges and opportunities of using the data. Next, we summarize the current applications of using MLS over urban areas, including transportation infrastructure mapping, building information modeling, utility surveying and mapping, vegetation inventory, and autonomous vehicle driving. Then, we review common key issues for processing and analyzing MLS point clouds, including classification methods, object recognition, data registration, data fusion, and 3D city modeling. Finally, we discuss the future prospects for MLS technology and urban applications.

The spread of new survey strategies for the documentation and 3D reconstruction of complex cultural heritage sites enables the implementation of virtual web navigation systems that are useful for their virtual fruition. In particular, remote indoor/outdoor exploration enhances our knowledge of cultural heritage sites, even in inaccessible or difficult-to-visit states. However, the 3D data acquisition of complex sites for documentation remains a challenge, and the 3D virtual exploration of these datasets is often limited to property software implementations. This work describes the 3D documentation and construction of an indoor/outdoor web visualization system based on the WebGL open-source technology of a complex cultural heritage site. The case study regards the complex of “Santa Maria della Grotta” in Marsala (Italy), which is composed of a church that is located mostly underground and is connected to a human-dug hypogea on the site of a Punic necropolis. The aim of the work was to obtain detailed 3D documentation of the indoor and outdoor spaces through the integration of mobile laser scanning and aerial photogrammetry survey, and to develop a virtual web navigation system for the remote exploration of the site. The indoor/outdoor web navigation system provides users with a simple, web-browser-based 3D visualization, enabling the dissemination of the monuments’ knowledge on the web through an economically sustainable solution based on open-source technologies.

This paper explores the use of Mobile Mapping Systems (MMSs) for urban Cultural Heritage (CH) documentation, which has become an increasingly important tool in surveying for rapid and accurate mapping of both internal and external environments. The study evaluates the performance of the STONEX® X120GO SLAM Laser Scanner, a recent commercial MMS, in documenting CH in various outdoor applications, including urban environments and inaccessible places. The methodology was applied to three test fields in the historic centre of Venice, which include Piazza San Marco, Santa Marta area, and the Venetian canal called Rio de le Toresele. The STONEX® X120GO SLAM Laser Scanner is composed of a 360° rotating head LiDAR scanner, three 5MP cameras, and an Inertial Measurement Unit (IMU) and Global Navigation Satellite System (GNSS) for geospatial 3D point cloud creation. The MMS was evaluated in terms of time, accuracy, and point cloud resolution against other active sensors such as Terrestrial Laser Scanners (TLSs) and spherical photogrammetry. The results suggest that the tested MMS has reached optimal levels of development, enabling high-speed data collection and providing good accuracy for significant urban CH sites. Overall, the paper highlights the importance and potential of MMSs for CH documentation and emphasizes the need for ongoing development to optimize the management process.

Nowadays, simultaneous localization and mapping (SLAM) algorithms support several commercial sensors which have recently been introduced to the market, and, like the more common mobile mapping systems (MMSs), are designed to acquire three-dimensional and high-resolution point clouds. The new systems are said to work both in external and internal environments, and completely avoid the use of targets and control points. The possibility of increasing productivity in three-dimensional digitization projects is fascinating, but data quality needs to be carefully evaluated to define appropriate fields of application. The paper presents the analytical measurement principle of these indoor mobile mapping systems (IMMSs) and the results of some tests performed on three commercial systems. A common test field was defined in order to acquire comparable data. By taking the already available terrestrial laser scan survey as the ground truth, the datasets under examination were compared with the reference and some assessments are presented which consider both quantitative and qualitative aspects. Geometric deformation in the final models was computed using the so-called Multiscale Model to Model Cloud Comparison (M3C2) algorithm. Cross sections and cloud to mesh (C2M) distances were also employed for a more detailed analysis. The real usability assessment is based on the features of recognizability, double surface evidence, and visualization effectiveness. For these evaluations, comparative images and tables are presented.

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.

In this article, we suggest the introduction of a new method of generating AR content, which we propose to call plane-based augmented geovisualizations (PAGs). This method concerns cases in which AR geovisualizations are embedded directly on any plane detected by the AR device, as in the case of the investigated “Crown of Polish Mountains 3D” application. The study on the usefulness of the AR solution against a classic solution was conducted as part of an online survey of people from various age and social groups. The application in the monitor version showing 3D models of mountain peaks (without AR mode) was tested by the respondents themselves. The use of the application in the AR mode, which requires a smartphone with the appropriate module, was tested by the respondents based on a prepared video demonstrating its operation. The results of the research on three age groups show that the AR mode was preferred among users against all compared criteria, but some differences between age groups were clearly visible. In the case of the criterion of ease of use of the AR mode, the result was not so unambiguous, which is why further research is necessary. The research results show the potential of the AR mode in presenting 3D terrain models.

Rapidly growing cities, multiple uses of urban space and the complexity of overlapping property rights require various types of rights to be registered and handled in a uniform and reliable way, considering the third dimension. The adoption of automated and low-cost but reliable procedures for cadastral surveys and for the capture and processing of cadastral data, as well as the use of modern Information Technology (IT) tools and m-services, is the beginning of a new cadastral evolution. 3D-crowdsourced cadastral data capture has huge potential and may soon facilitate the work of National Mapping Agencies (NMAs). In this paper, an innovative fit-for-purpose procedure is designed and initially tested that aims to save time and costs and to provide a modern technical solution for the initial collection, registration and visualization of 3D cadastral data. An open-source, mobile application for the acquisition of 3D crowdsourced cadastral data and 3D modelling and visualization of property units is developed, tested and presented. The proposed technical procedure is adjustable and may be used in both the developed and the developing world. The geometric accuracy of the final product depends on the geometric accuracy of the basemaps used. The developed application is tested on a multi-story building in an urban area of Larisa, in Greece. An initial evaluation of the procedure and the final product, in terms of its usability, affordability, reliability and implementation duration, is conducted. The first results are satisfactory and may lead to a fit-for-purpose procedure for a 3D cadastre for all in the future.

The research activity aims to evaluate the Mobile Laser Scanner mapping system's effectiveness and critical issues based on simultaneous localization and mapping (SLAM) called KAARTA Stencil. The research introduces a reflection on a series of test datasets resulting from the mobile system's application in an urban context taken as a case study and aimed at the representation and 3D modeling of architectural complexes.In detail, the metric accuracy of the proposed method was evaluated through a comparative analysis of the point cloud data through the evaluation of the surface deviation of the 3D point clouds based on the SLAM system and the data of static measurement systems, more precise to evaluate the accuracy of the proposed acquisition system. For each data were specified the possibilities of representation, the type of representation scale, and the possible manipulations and extractions of 2D profiles to design and analyze architectural elements through mobile systems.The analysis involves a breakdown of the problem of representation, identifying protocols that can be applicable at different levels and scales of reading aimed at the representation and discretization of parts and elements linked together in a hierarchical or interconnected relationship, outlining their criticality and potential.

Facility Management activities require to collect and organize a large amount of information about a building as, for example, geometry, MEP structures, lighting and antifire devices, typologies of furniture, paving characteristics, structures and more. Nowadays the data acquisition procedures for indoor environments are usually still carried on with old style approach, where surveyors have to manually map and acquire the data, walking along the sites with a poor level of digitalization The success story presented in the paper describes how using an Indoor Mobile Mapping approach (Zlot et al., 2014), it is possible to satisfy the need to acquire plant views of a large parts of buildings and, simultaneously, to record a 3D+Full resolution RGB images. Thanks to this fast acquisition it is later possible to feed a 2D/3D database, identifying the main objects needed to support a facility management process. The iMMS that has been used is based on SLAM approach, that allows the user to map and survey large sites also indoor, that means without the presence of GNSS signal and without the use of accurate and expense IMU devices. The data acquired in the field has been process with standard/commercial software that is usually used to create DB for outdoor mobile mapping.