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The paper proposes an approach for defining a generative modelling process of complex objects and their sharing. The case study is the Stronghold of Arquata del Tronto, a monument of extraordinary historical, cultural and landscape value, damaged by the earthquake in 2016. The first step has been data acquisition on a geometrical level, through laser scanner and UAV photogrammetry, and on a historical level, through archival research to understand construction phases and transformations. The Stronghold was probably built between the 11 and the 12th century on a hill to control the territory. It underwent several transformations and neglection phases over the centuries. The second phase has been the generative modelling following the scan-to-BIM approach. The three-dimensional model is intended to support the design phases, from preliminary analysis to the construction site.For this reason, the Stronghold has been modelled with different Grade of Generation (GOG). The study of the eastern curtain wall, where the signs suffered by the structure due to the earthquake are most evident, was deepened through a Building Archaeology preliminary analysis. The third phase aimed at orienting the HBIM towards three digital information-sharing solutions such as Common Data Environment (CDE), and Virtual Reality (VR) to enhance the cultural and historical values, supporting the reopening of the Stronghold as a venue for conferences and exhibitions.

Light Detection and Ranging (LiDAR) technology is playing a major role in different applications. Indeed, the possibility of exploiting either 3D geometric features and radiometric information makes LiDAR suitable for a wide range of practical domains. LiDAR proved also being quite flexible in terms of platforms where it can be implemented for the acquisition, spanning from airborne sensors up to car-based and hand-held instruments. Due to the rapid expansion of research concerning LiDAR intensity, the ISPRS WG III/5 launched in 2017 an initiative aimed at providing free access to LiDAR data acquired by modern multispectral ALS sensors as well as MLS data. The two datasets, MLS Data Set 1 – (“Sun Prairie”), and Multispectral LiDAR Data Set 2 – (“Tobermory”), were provided by Teledyne Optech Company (Canada) and were made freely available to researchers upon request. This paper is presenting the first results of this initiative in terms of applications, application domains and topics tackled by applicants. The relevance of this data set is also evaluated through a bibliometric analysis considering both Scopus and Web of Science indexed databases to analyse the main directions where the scientific research, the technical development and the application interest is moving to.

Monitoring landscapes in times of climate change patterns is a crucial issue, moreover, in the analyzed Mediterranean area, one of the major global candidates to develop land degradation stresses and consequential desertification phenomena. The research presented here is developed in the Mediterranean Basin, specifically in the Basilicata Region (southern Italy). The region is characterized by a very long history of intensive anthropization endowed by the high diversity of relatively geologically young soil types that consequentially created a vastity of spatial mosaics, which contributed to the composition of its archeolandscapes and endorsed some specific characteristics of the Mediterranean region, that evolved to respond to the human impact, including grazing, cultivation, and fires. Those key elements lead to the crucial issues of the region investigated here as soil erosion, salinization, loss of organic carbon, loss of biodiversity, and landslides, which together with deforestations, depopulation, and wildfires, define the exact framework of degradation and marginality. The evaluation of the sensitivity to degradation was performed (i) firstly at the regional scale, through a MEDALUS (Kosmas et al. 1999) approach, by implementing 6 main indicators (Soil Quality Index, Climate Quality Index, Vegetation Quality Index, Management Quality Index, Landslide Risk Index, Water Availability Index), and (ii) secondly at the mid-regional scale, through remote sensing by evaluation of the NDVI differencing thresholds in time intervals, covering a 20 years’ time span going from 2000 to 2020. The study helped to define the in-progress land degradation trends and scenarios of the region, which must be the evidence-based foundation of integrated landscape planning strategies in marginal territories, implemented through a Decision Support System (DSS) based both on ecological, climate-adaptive, and environmental indicators, and on social, cultural, and economic development co-creation strategies.

Automatic extraction of road features from LiDAR data is a fundamental task for different applications, including asset management. The availability of updated and reliable models is even more important in the context of smart roads. One of the main advantages of LiDAR data compared with other sensing instruments is the possibility to directly get 3D information. However, the task of deriving road networks form LiDAR data acquired with Airborne Laser Scanning (ALS) may be quite complex due to occlusions, low feature separability and shadowing from contextual objects. Indeed, even if roads elements can be identified in the ALS point cloud, the automated identification of the network starting form them can be involved due to large variability in the size of roads, shapes and presence of connected off-road features such as parking lots. This paper presents a workflow aimed at partially solving the automatic creation of a road network from high-resolution ALS data. The presented method consists of three main steps: (i) labelling of road points; (ii) a multi-level voting scheme; and (iii) the regularization of the extracted road segments. The developed method has been tested using the “Vaihingen”, “Toronto” and “Tobermory” data set provided by the ISPRS.

In the wake of the success of Deep Learning Networks (DLN) for image recognition, object detection, shape classification and semantic segmentation, this approach has proven to be both a major breakthrough and an excellent tool in point cloud classification. However, understanding how different types of DLN achieve still lacks. In several studies the output of segmentation/classification process is compared against benchmarks, but the network is treated as a “black-box” and intermediate steps are not deeply analysed. Specifically, here the following questions are discussed: (1) what exactly did DLN learn from a point cloud? (2) On the basis of what information do DLN make decisions? To conduct such a quantitative investigation of these DLN applied to point clouds, this paper investigates the visual interpretability for the decision-making process. Firstly, we introduce a reconstruction network able to reconstruct and visualise the learned features, in order to face with question (1). Then, we propose 3DCAM to indicate the discriminative point cloud regions used by these networks to identify that category, thus dealing with question (2). Through answering the above two questions, the paper would like to offer some initial solutions to better understand the application of DLN to point clouds.

This paper presents the contribution of digital surveying techniques for the estimation of fluvial sediment transport. The aim is to create predictive models able to minimize or reduce the hydrogeological hazard, especially before or during critical meteorological events. The case study is the Caldone stream, a watercourse located in the municipality of Lecco (Italy). Structure-from-Motion photogrammetry and terrestrial laser scanning techniques were used to collect metric data about the morphology of the riverbed. Data acquisition was carried out to create a digital model of visible and submerged parts of the riverbed. Then, a second area with a sedimentation pool was selected to monitor the variation of the depth induced by progressive accumulation of sediments. As the pool is constantly covered by water, a low-cost bathymetric drone was used coupling the measured depth values with total station measurements to track the drone. Finally, the paper describes the implementation of an on-line data delivery platform able to facilitate retrieval of heterogeneous geospatial data, which are used in the developed numerical model for sediment transport. This service aims at providing simplified access to specific map layers without requiring knowledge about data formats and reference systems.

Structural Health Monitoring (SHM) allows tracking the structural behavior in time and support decisions regarding, for instance, the need for maintenance and repair activities. Most traditional SHM systems require sensors that are directly applied to the structure to get insights into the structural performance. Satellite technologies can provide an appealing alternative to traditional SHM. They allow to measure displacements at a large scale and to follow their evolution without the need of directly accessing the structure. Further to this, the possibility to monitor large areas opens new avenues for the development of automatic alert systems able to issue an alarm and early-flag damaged structures. However, displacements of civil structures might also be induced by sources other than damage such as thermal or periodic hydrogeological variations. These can hinder the onset and development of damage or lead to false alarms if such displacements are erroneously interpreted as damages. This paper aims to present a new method for damage detection based on DInSAR measurements, that tackles both aspects providing reliable information about the onset of damage under environmentally changing conditions in a period corresponding to about twice the revisit time of the satellite. A case study is presented to demonstrate the applicability of the proposed method, namely the Palatino bridge in Rome, Italy. The satellite data are acquired by COSMO-SkyMed of the Italian Space Agency and consist of displacements of the observed structure recorded during a period spanning between 2011 and 2019.

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG Since the last two decades, the use of laser scanners for generating accurate and dense 3D models has been rapidly growing in multiple disciplines. The reliance on human-expertise to perform an efficient scanning in terms of completeness and quality encouraged the researchers to develop strategies for carrying out an optimized and automated scan planning. Nevertheless, due to the predominant use of static terrestrial laser scanners (TLS), the most of developed methods have been focused on scan optimization by fixing standpoints on basis of static scanning. The increasing use of portable mobile laser scanning systems (MLS) enables faster non-stop acquisition which demands the planning of optimal scan trajectories. Therefore, a novel method addressing the absence of dynamic scan planning is proposed considering specific MLS constraints such as maximum acquisition time or closed-loops requirement. First, an initial analysis is carried out to determinate key-positions to reach during data acquisition. From these positions a navigable graph is generated to compute routes satisfying specific MLS constraints by a three-step process. This starts by estimating the number of routes necessary to subsequently carry out a coarse graph partition based on Kmedoids clustering. Next, a balancing algorithm was implemented to compute a balanced graph partition by node exchanging. Finally, partitions are extended by adding key nodes from their adjacent ones in order to provide a desirable overlapping between scans. The method was tested by simulating three laser scanner configurations in four indoor and outdoor real case studies. The acquisition quality of the computed scan planning was evaluated in terms of 3D completeness and point cloud density with the simulator Helios++. Xunta de Galicia | Ref. ED431F 2022/08 Agencia Estatal de Investigacion | Ref. PCI2022-132943 Agencia Estatal de Investigación | Ref. RYC2020-029193-I

Growing interest in boosting urban identity and character is increasing the demand for historic maps and documents of cities in constant evolution as in the case of metropolitan areas, peripheries and riverbank sites. A ‘Heritage & Development strategy based on the Historic Urban Landscape approach is required by city makers to ensure that exploitation needs can valorise the site’s natural and cultural heritage for sustainable social and economic optimisation.This paper intends to propose innovative virtual hub technologies of brokering, discovering and accessing open data, making available - to a large public of users - the multi-temporal dense stratified evidences of the targeted built environment areas and its surroundings, through the navigation of geo-referenced historical maps, together with current maps, going through design data. Enhancing the practice of publishing maps as open data represents a powerful leverage for time and cost effectiveness among planners, scientists and historians; soliciting their use to gain a vast knowledge of that areas, including a better comprehension of the transformations over the centuries, in order to support decision-making analysis, environmental monitoring and urban area planning; thus contribute to improving the sustainability of interventions respectful of the identity of the urban landscape. A case study of the ‘Deux Rives’ planning area in the city of Strasbourg is presented to illustrate these issues. The City of Strasbourg’s commendable work in publishing the historical maps supports the municipal authority’s Heritage & Development strategy in meeting contemporary and future needs while mitigating long-term damage from pressures for new interventions. Innovative virtual hub based applications to gather open data coming from different sources (city territorial services, design data sources, mobility services) can result in immeasurable added value through communicating the wealth of the planned areas and raising awareness among citizens and visitors of the interventions.

This paper presents the survey of the Baptistery of the Collegiata Museum (Castiglione Olona - Italy), painted by Masolino da Panicale in 1435. Surveying activity was carries out throughout the use of combined digital techniques of documentation (topographic measurements, laser scanning, digital photogrammetry, thermal imaging, digital photography). Different data were collected inside and outside the Baptistery following a multi-resolution reconstruction that ranges from the whole Baptistery up to small details. Laser scans were also used to obtain a digital representation of inner volumes of the structure. Registered scans were uploaded into a modelling software, in order to produce a 3D model based on scan data, increasing the correspondence with the existent building; this model can be used to better understand the volume arrangement, also for educational and dissemination purposes. A particular attention was devoted to documentation of graffiti scratched onto the frescos, since their presence is a significative evidence of the history of the building. A digital-based workflow was set out in order to assure high quality outputs in respect of the conservation needs.This multi-resolution approach proved to be a suitable solution when dealing with features, such as ancient architectures, with a high number of complex details to be correctly recorded and joint together as starting point and support of historical researches. Results and scope are here presented.

Informative models are not limited only to new construction or existing building but can also be used (also been used) for large infrastructure management like bridges. The adoption of informative content models for structural health monitoring (SHM) of such infrastructures poses some issues that need to be solved in order to develop smooth management and maintenance workflows. This paper describes a novel methodology for the generation of a detailed BIM of a complex medieval bridge and the possibility to link specific data coming from load testing. Integration of information coming from different data sources is one of the most important aspects for the development of maintenance programs. However, each actor in the process makes use of different strategies and protocols whose integration can generate bottlenecks. To partially overcome this limitation a cloud-based solution was used, and a Building Information Model (BIM) of the bridge was used as main collector of information for the different stakeholders involved in its management.

The development of advanced survey techniques in the last years is offering a wide set of tools for implementing the building analysis. In the preservation field, the use of 3D interactive models is a prerogative of few and rare excellent cases and the information contained in high-resolution virtual representation are only partially developed. In the past centuries, the representation was centred on the theoretical roles of the descriptive geometry devoted to the representation of the architectural elements complexity in the space to manage the construction site process. It has been progressively lost the past skill to managing 3D objects in the space. Being HBIM based on 3D solids representation, the theme of the 3D model comes back to the foreground. The complexity of the architectural heritage and its components is evidencing a gap of best practices, protocols and specification in the HBIM-modeling. Do-It-Yourself modeling process has been characterised by the first phase of HBIM generation in the last years. Modeling phase within HBIM is left to the single responsibility, with lack of specification on the accuracy and level of geometry.This paper presents a first tentative to summarize the relationship among the surveying accuracy, the Level of Geometry and the Level of Accuracy (LOA) of each BIM object, starting from a series of experiences, in which advanced survey techniques were applied to condition assessment required by architectural preservation HBIM approach. The objectives of the surveying and HBIM can change for different aspects: but in the preservation context the specificity of each single objects and their complexity need to be taken into account. As in the surveying, the choice of a scale implies a range of accuracy and tolerance in the data acquisition and processing, in HBIM modelling the choice of the Grade of Accuracy drives within the Level of Geometry the scale model that is expected to be performed and required by the different actors involved by the different phases (i.e. restoration, Energy Efficiency, Finite Element Analysis, CoSiM). On the base of different experiences occurred in the last years, the specifications conventionally adopted for the surveying have been here proposed and extended to the HBIM domain, particularly in the modelling of objects, in order to classify different accuracies. A transparent choice of accuracy allows to define the LOG and to support the adoption of the proper Grade of Generation among the different options (GOG1-10) in function of the point clouds geometry and of the scales chosen by the different actors. The architectural scale together with the urban scale (Heritage Urban Level) is considered as well to keep advantage of a multi-resolution model, diversified in function of the objectives, thus of Level of accuracy (and Level of Information) and Level of Geometry.

The protection and management of archaeological sites require from a deep documentation and analysis, and although hand measuring and documentation is the cheapest way for collecting data, laser scanner has been gradually integrated for the geometrical data capture since point clouds have a high quality in terms of accuracy, precision and resolution. Although acquisition with laser scanner is considered a quick process, scan planning is of high relevance when considering outdoor archaeological sites because of their large size and complexity. In this paper, an automatic methodology to optimize the number and position of scans in order to obtain a point cloud of high quality in terms of data completeness is proposed. The aim of the methodology is to minimize the number of scans, minimizing at the same time the estimated surveying time and the amount of repetitive acquired data. Scan candidates are generated by using a grid-based and a triangulation-based distribution, and results show a faster analysis when triangulation is implemented. The methodology is tested into two real case studies from Italy and Spain, showing the applicability of scan planning in archaeological sites Xunta de Galicia | Ref. ED481B 2016/079-0 Xunta de Galicia | Ref. ED431C 2016-038 Universidade de Vigo | Ref. 00VI 131H 641.02 Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-77158-C4-2-R Ministerio de Economía, Industria y Competitividad | Ref. RTC-2016-5257-7 European Cooperation in Science and Technology (COST) | Ref. CA15201

The main objective of the research was identifying the phenomena that generate land degradation (LD), in the Basilicata region’s landscape (southern Italy),with a MEDALUS (Kosmas et al., 1999) and RS approach, through the help of 6 main indicators (Soil Quality Index, Climate Quality Index, Vegetation Quality Index, Management Quality Index, Landslide Risk Index, Water Availability Index) and through NDVI differencing thresholds evaluation in time intervals, covering a 20 years’ time span going from 2000 to 2020. The Basilicata region saw this phenomenon increased in the past centuries, both because there has never been any monitoring of LD at regional planning-level, and for the fact that historically the region suffered severe agricultural stress, with enormous deforestations that have led to soil degradation and consequently to the depopulation of the internal marginal areas. These elements caused a strong impact on the potential regional progress, both economic and social, leading to a huge ecological damage. The methodology helped to outline the future LD predictions for the region, and consequentially its management possibilities and implications in relation to this critical issue, in order to maintain or restore the pre-existing values, thus integrating the study of Environmentally Sensitive Areas (ESAs) in a scientific validated Decision Support System (DSS), for new coherent and integrated landscape strategies in marginal territories. This objective derives from recognizing the landscape as defined in the European Convention (Council of Europe, 2000) as an important element for community interest, on the cultural, ecological, environmental and social point of view, and as a resource for economic development, pursued by enhancing the preservation of its fundamental component of cultural and natural heritage.

In the wide framework of Scan-to-BIM 3D modelling procedures, the complexity of the architectural heritage and its components is evidencing a gap of best practices and specification in the HBIM-modeling and thus it is requiring important considerations about the modelling strategies and protocols between the requested level of detail (LOD), the expect accuracy and above all the actual use-oriented requirements. Several works are largely focusing on developing workflows for traditional static LiDAR scanning sensors. However, the chance to benefit from on-site faster data acquisition is needful at times, and procedures are directing toward rapid mapping 3D approaches, evolving from traditional static scanning toward MMS (Mobile Mapping Systems) based on SLAM technology (Simultaneous Localization and Mapping) algorithms implemented in portable devices. The potential of these solutions can contribute to increase a massive cost-effective documentation, and also in view of BIM-HBIM modelling generation, and this needs further researches. At the same time, the descriptive capabilities of this class of portable scanners do not reach the precision of the static solutions. Many time-cost balance evaluations towards an analysis of geometry, grade of generation (GOG) and details can be thus conducted. This paper presents a first comparison between TLS (Faro Focus 3D) and hand-held scanner Zeb Revo (by GeoSLAM) of the entire workflow (from raw data acquisition up to parametric modeling) focusing on the Bramante’s Canonica Court in the Basilica di Sant’Ambrogio. First, the two raw data are compared, considering geometric features (data density, precision, possibility to detect edges, details and accurate curvature). Then, some well-established modelling procedures developed for TLS data, as triangulation mesh and NURBS generation, are applied to MMS point cloud to identify their suitability. Different elements belonging to the architectural structure hierarchy are considered in a multi-scale perspective: the vaulted system of the porch, the columns and the arches of the porch with their different architectural elements.

The landscape is the system of both tangible and intangible heritage. A key element to evaluate a landscape is its integrity intended as the wholeness and intactness of natural and/or cultural heritage. The problem of identifying the integrity of a landscape is twofold: on one side it is necessary to identify the element that determines the intactness of a landscape and on the other side the methodology to study and quantify the integrity. Different methodologies have been developed in literature to assess and measure landscape integrity: some of them are more quantitative, while others are more qualitative. This paper presents two different methods for landscape integrity evaluation: the Valutazione Storico Ambientale (VASA) and the Landscape System Historical Analysis (LaHSA) one. The comparison of the two methodologies is carried out in a portion of the Ticino river (North Italy) and more specifically in the municipality of Morimondo. The two methods are compared considering a set of elements taking into account both the understanding of tangible and intangible permanencies and data accessibility/accuracy to carry out the analysis.

In recent years, the advent of the latest-generation technologies and methods have made it possible to survey, digitise and represent complex scenarios such as archaeological sites and historic buildings. Thanks to computer languages based on Visual Programming Language (VPL) and advanced real-time 3D creation platform, this study shows the results obtained in eXtended Reality (XR) oriented to archaeological sites and heritage buildings. In particular, the scan-to-BIM process, digital photogrammetry (terrestrial and aerial) were oriented towards a digitisation process able to tell and share tangible and intangible values through the latest generation techniques, methods and devices. The paradigm of the geometric complexity of the built heritage and new levels of interactivity between users and digital worlds were investigated and developed to favour the transmissibility of information at different levels of virtual experience and digital sharing with the aim to archive, tell and implement historical and cultural baggage that over the years risks being lost and not told to future generations.

The paper intends to define the different levels of quality models achieved to assess architectural heritage in fragile contexts as the earth quaked territories, proposing to reverse the BIM logic ‘simple-to-complex’ in favor of a complex-to-simplex one targeted to HBIM. In order to perform a preservation plan, given the complexity of a damaged heritage, the simplification can’t be the starting point, but the synthesis of the detailed levels of understanding obtained: the case study of St. Francesco church, damaged by the earthquake occurred in 2016, is presented to highlight the deliverables submitted as part of the support to the preliminary preservation design project and decision-making process carried out by the research group of the Politecnico di Milano for the Municipality of Arquata del Tronto. The high level of geometry description acquired by the surveying (TLS, MMS, Photogrammetry) has been finalized to analyze the out-of-plumbs and structural behavior, enriched by the diagnostic analysis detecting the materials and construction techniques, supported the recognition of the stratigraphic volume units and construction phases to better understand the transformations across the centuries integrating the direct data sources with the indirect ones (documents, archives). While in the traditional BIM logic the level of enrichment progressively crosses the Level of Development phases (LOD100-500) by adopting a progressive parallel Level of Geometry (LOG100-500), the paper proposes scales model definition (GOA100-50-20-10) and LOG specifications adapted to the LOD (Design Development, Preservation Plan) reversing the logic and introducing a synthesis model that collects the different analysis, a wrap-up model, to be used together with the detailed high scale models (LOG200-300-400-100), for BIM-to-FEA or BIM energetic analysis, and within LOD600 VR.

In the last 20 years, SAR sensors installed on satellites have been increasingly used to monitor large scale phenomena such as subsidence, uplifting, or landslides. Recently several research groups started to investigate the use of remote sensing for damage detection in civil infrastructures. This technique presents in principle several advantages, not least the possibility to monitor a network of structures using the same sensor. However, its implementation for civil engineering projects is still at its infancy and a limited number of applications can be found in literature. The goal of this paper is to investigate the feasibility of using InSAR data for structural health monitoring of bridges with reference to a number of case studies. Data measured by radar satellites with different spatial and temporal resolutions and different frequency bands are processed to extract bridge displacement data and analyzed to identify possible structural damages. The SqueeSAR technique is used to extract displacement time histories from SAR images acquired by radar sensors with different spatial and temporal resolution (TerraSAR-X and RADARSAT 1–2). Displacements are then processed to identify anomalies possibly related to damage. Results show that high-resolution radar data enable the detection of very small structural displacements due to environmental changes, such as temperature variation.