Special Issue "Remote Sensing, Metric Survey and Spatial Information Technologies for Heritage Management"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (10 August 2021).

Special Issue Editors

Prof. Dr. Fulvio Rinaudo
E-Mail Website
Guest Editor
Prof. Dr. José Luis Lerma
E-Mail Website
Guest Editor
Universitat Politècnica de València - Dpto. de Ingeniería Cartográfica Geodesia y Fotogrametría, Camino de Vera, s/n - 46022 Valencia, Spain
Interests: photogrammetry; laser scanning; virtual archaeology; CH documentation

Special Issue Information

Dear Colleagues,

The technological development of Remote Sensing, Photogrammtery, and the disciplines that are today grouped under Geomatics (e.g., GIS, HBIM) offers, every year, new ideas and new products that can help with the documentation, intervention, monitoring, and day-by-day management of cultural heritage assets.

Cultural Heritage assets are today extremely in danger due to different natural and human factors (e.g., climate change, earthquakes, hydrogeological risks, wars, urban development). The experts involved in cultural heritage management (documentation, intervention, day-by-day management) are continuously looking for the best possible solutions to their needs, by considering both technical and economic aspects.

Mile-stone, in all the Geomatics disciplines, is the quality assessment of the provided data (both metric and semantic ones) which is the first information that the users of Geomatics data have to know to understand correct and affordable uses of those data.

The proposed Special Issue of Remote Sensing aims to explore the potentialities of the new primary data for metric and semantic description of cultural heritage assets (e.g., landscapes, urban centers, buildings, sculptures, paintings, books, underground and underwater resources) and the new tools to manage all those data in a coherent and effective way to describe their basic physical properties and to monitor their changes over the times.

Prof. Dr. Fulvio Rinaudo
Prof. Dr. José Luis Lerma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Remote sensing
  • Photogrammetry
  • GIS and HBIM
  • Quality assessment
  • Satellite image processing
  • Aerial image processing
  • Terrestrial and underwater image processing
  • CH documentation
  • CH monitoring

Published Papers (4 papers)

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Article
From Acquisition to Presentation—The Potential of Semantics to Support the Safeguard of Cultural Heritage
Remote Sens. 2021, 13(11), 2226; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13112226 - 07 Jun 2021
Viewed by 703
Abstract
The signature of the 2019 Declaration of Cooperation on advancing the digitization of cultural heritage in Europe shows the important role that the 3D digitization process plays in the safeguard and sustainability of cultural heritage. The digitization also aims at sharing and presenting [...] Read more.
The signature of the 2019 Declaration of Cooperation on advancing the digitization of cultural heritage in Europe shows the important role that the 3D digitization process plays in the safeguard and sustainability of cultural heritage. The digitization also aims at sharing and presenting cultural heritage. However, the processing steps of data acquisition to its presentation requires an interdisciplinary collaboration, where understanding and collaborative work is difficult due to the presence of different expert knowledge involved. This study proposes an end-to-end method from the cultural data acquisition to its presentation thanks to explicit semantics representing the different fields of expert knowledge intervening in this process. This method is composed of three knowledge-based processing steps: (i) a recommendation process of acquisition technology to support cultural data acquisition; (ii) an object recognition process to structure the unstructured acquired data; and (iii) an enrichment process based on Linked Open Data to document cultural objects with further information, such as geospatial, cultural, and historical information. The proposed method was applied in two case studies concerning the watermills of Ephesos terrace house 2 and the first Sacro Monte chapel in Varallo. These application cases show the proposed method’s ability to recognize and document digitized cultural objects in different contexts thanks to the semantics. Full article
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Article
From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage
Remote Sens. 2020, 12(7), 1094; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071094 - 29 Mar 2020
Cited by 16 | Viewed by 1792
Abstract
Building Information Modelling (BIM) is a globally adapted methodology by government organisations and builders who conceive the integration of the organisation, planning, development and the digital construction model into a single project. In the case of a heritage building, the Historic Building Information [...] Read more.
Building Information Modelling (BIM) is a globally adapted methodology by government organisations and builders who conceive the integration of the organisation, planning, development and the digital construction model into a single project. In the case of a heritage building, the Historic Building Information Modelling (HBIM) approach is able to cover the comprehensive restoration of the building. In contrast to BIM applied to new buildings, HBIM can address different models which represent either periods of historical interpretation, restoration phases or records of heritage assets over time. Great efforts are currently being made to automatically reconstitute the geometry of cultural heritage elements from data acquisition techniques such as Terrestrial Laser Scanning (TLS) or Structure From Motion (SfM) into BIM (Scan-to-BIM). Hence, this work advances on the parametric modelling from remote sensing point cloud data, which is carried out under the Rhino+Grasshopper-ArchiCAD combination. This workflow enables the automatic conversion of TLS and SFM point cloud data into textured 3D meshes and thus BIM objects to be included in the HBIM project. The accuracy assessment of this workflow yields a standard deviation value of 68.28 pixels, which is lower than other author’s precision but suffices for the automatic HBIM of the case study in this research. Full article
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Article
Dominant Color Extraction with K-Means for Camera Characterization in Cultural Heritage Documentation
Remote Sens. 2020, 12(3), 520; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12030520 - 05 Feb 2020
Cited by 1 | Viewed by 1189
Abstract
The camera characterization procedure has been recognized as a convenient methodology to correct color recordings in cultural heritage documentation and preservation tasks. Instead of using a whole color checker as a training sample set, in this paper, we introduce a novel framework named [...] Read more.
The camera characterization procedure has been recognized as a convenient methodology to correct color recordings in cultural heritage documentation and preservation tasks. Instead of using a whole color checker as a training sample set, in this paper, we introduce a novel framework named the Patch Adaptive Selection with K-Means (P-ASK) to extract a subset of dominant colors from a digital image and automatically identify their corresponding chips in the color chart used as characterizing colorimetric reference. We tested the methodology on a set of rock art painting images captured with a number of digital cameras. The characterization approach based on the P-ASK framework allows the reduction of the training sample size and a better color adjustment to the chromatic range of the input scene. In addition, the computing time required for model training is less than in the regular approach with all color chips, and obtained average color differences Δ E a b * lower than two CIELAB units. Furthermore, the graphic and numeric results obtained for the characterized images are encouraging and confirms that the P-ASK framework based on the K-means algorithm is suitable for automatic patch selection for camera characterization purposes. Full article
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Technical Note
Preliminary Archeological Site Survey by UAV-Borne Lidar: A Case Study
Remote Sens. 2021, 13(3), 332; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13030332 - 20 Jan 2021
Cited by 1 | Viewed by 901
Abstract
Preliminary analysis of an archaeological site requires the acquisition of information by several diverse diagnostic techniques. Remote sensing plays an important role especially in spatially extended and not easily accessible sites for the purposes of preventive and rescue archaeology, landscape archaeology, and intervention [...] Read more.
Preliminary analysis of an archaeological site requires the acquisition of information by several diverse diagnostic techniques. Remote sensing plays an important role especially in spatially extended and not easily accessible sites for the purposes of preventive and rescue archaeology, landscape archaeology, and intervention planning. In this paper, we present a case study of a detailed topographic survey based on a light detection and ranging (LiDAR) sensor carried by an unmanned aerial vehicle (UAV; also known as drone). The high-resolution digital terrain model, obtained from the cloud of points automatically labeled as ground, was searched exhaustively by an expert operator looking for entrances to prehistoric hypogea. The study documents the usefulness of such a technique to reveal anthropogenic structures hidden by vegetation and perform fast topographic documentation of the ground surface. Full article
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