Valorisation of history and landscape for promoting the memory of WWI

Nocerino, Erica; Menna, Fabio; Toschi, I.; Morabito, Daniele; Remondino, Fabio; Rodríguez‐Gonzálvez, Pablo

doi:10.1016/j.culher.2017.07.007

Cited by 20 publications

(21 citation statements)

References 14 publications

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“…In the last 20 years, various research activities, based on active and passive sensors, provided reliable methodologies for the acquisition and generation of dense point clouds and textured 3D models of heritage structures [1,2]. These 3D data are typically used for accurate documentation, digital preservation, and visualisation [3][4][5][6]. Nowadays, the amount of available 3D datasets has exponentially increased but, at the same time, it is becoming very important to enrich point clouds with semantic information of the digitised objects [7,8].…”

Section: Introductionmentioning

confidence: 99%

A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification

et al. 2020

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The recent years saw an extensive use of 3D point cloud data for heritage documentation, valorisation and visualisation. Although rich in metric quality, these 3D data lack structured information such as semantics and hierarchy between parts. In this context, the introduction of point cloud classification methods can play an essential role for better data usage, model definition, analysis and conservation. The paper aims to extend a machine learning (ML) classification method with a multi-level and multi-resolution (MLMR) approach. The proposed MLMR approach improves the learning process and optimises 3D classification results through a hierarchical concept. The MLMR procedure is tested and evaluated on two large-scale and complex datasets: the Pomposa Abbey (Italy) and the Milan Cathedral (Italy). Classification results show the reliability and replicability of the developed method, allowing the identification of the necessary architectural classes at each geometric resolution.

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Section: Introductionmentioning

confidence: 99%

A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification

et al. 2020

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“…The scope of application of PMMSs is diverse: from cultural heritage constructions [13] and civil structures to industrial sites [14], indoor spaces [15], and natural environments [16]. PMMSs contain two groups of sensors that act in a synchronized way to reconstruct the scene three-dimensionally: navigation and remote sensing modules.…”

Section: Introductionmentioning

confidence: 99%

Validation of Portable Mobile Mapping System for Inspection Tasks in Thermal and Fluid–Mechanical Facilities

et al. 2019

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The three-dimensional registration of industrial facilities has a great importance for maintenance, inspection, and safety tasks and it is a starting point for new improvements and expansions in the industrial facilities context. In this paper, a comparison between the results obtained using a novel portable mobile mapping system (PMMS) and a static terrestrial laser scanner (TLS), widely used for 3D reconstruction in civil and industrial scenarios, is carried out. This comparison is performed in the context of industrial inspection tasks, specifically in the thermal and fluid-mechanics facilities in a hospital. The comparison addresses the general reconstruction of a machine room, focusing on the quantitative and qualitative analysis of different elements (e.g., valves, regulation systems, burner systems and tanks, etc.). The validation of the PMMS is provided considering the TLS as ground truth and applying a robust statistical analysis. Results come to confirm the suitability of the PMMS to perform inspection tasks in industrial facilities.

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“…However, the main problem remains when these CH elements only exist partially due to different reasons. In this case, 3D modeling or anastylosis approaches [16] are the best way to reconstruct the whole CH element [17,18], but require human expertise and knowledge about available historical documentation, as well as the verification of the suggested reconstruction through additional information, such as historical documents, images, records, etc. The expert and informal knowledge underlying the interpretation of historical data and its circumstances is vital for a correct reconstruction of the CH element [19].…”

Section: Introductionmentioning

confidence: 99%

Diachronic Reconstruction and Visualization of Lost Cultural Heritage Sites

Rodríguez‐Gonzálvez

Campo

Muñoz-Nieto

et al. 2019

IJGI

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Cultural heritage (CH) documentation is essential for the study and promotion of CH assets/sites, and provides a way of transmitting knowledge about heritage to future generations. The integration of the fourth dimension into geospatial datasets enables generating a diachronic model of CH elements, namely, a set of three-dimensional (3D) models to represent their evolution in various historical phases. The enhanced four-dimensional (4D) modeling (3D plus time) pursues a better understanding of the CH scenario, enriching historical hypotheses as well as contributing to the conservation and decision-making process. Although new geomatic techniques have reduced the amount of fieldwork, when put together, the geometric and temporal dimensions imply the interpretation of heterogeneous historical information sources and their integration. However, this situation could reach a critical point when the study elements are no longer present. The main challenge is to harmonize the different historical and archaeological data sources that are available with the current remains in order to graphically rebuild and model the lost CH assets with a high degree of reliability. Moreover, 4D web visualization is a great way to disclose the CH information and cultural identity. Additionally, it will serve as a basis to perform simulations of possible future risks or changes that can happen during planned or hypothetical restoration processes. This paper aims to examine the study case of a diachronic reconstruction by means of a mobile laser system (MLS) and reverse modeling techniques for a lost urban CH element: the citadel or Alcázar gate of Ávila. Within this aim, the final model is evaluated in terms of the consistency of the historical sources to assess its suitability considering the constructive interpretations that are required to integrate heterogenous data sources. Moreover, geometric modeling is evaluated regarding the current remains and its surroundings. Finally, a web 4D viewer is presented for its dissemination and publicity. This paper is an extended and improved version of our paper that was published in the 2018 ISPRS Technical Commission II Symposium, Riva del Garda, Italy, 3–7 June 2018.

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Valorisation of history and landscape for promoting the memory of WWI

Cited by 20 publications

References 14 publications

A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification

A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification

Validation of Portable Mobile Mapping System for Inspection Tasks in Thermal and Fluid–Mechanical Facilities

Diachronic Reconstruction and Visualization of Lost Cultural Heritage Sites

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