Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30036
Title: An Application of Machine Learning Algorithms by Synergetic Use of SAR and Optical Data for Monitoring Historic Clusters in Cypriot Cities
Authors: Tzima, Maria Spyridoula 
Agapiou, Athos 
Lysandrou, Vasiliki 
Artopoulos, Georgios 
Fokaides, Paris 
Chrysostomou, Charalambos 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: change detection;historic architecture clusters;land cover classification;machine learning;remote sensing;Sentinel-1;Sentinel-2;SNAP;urban heritage
Issue Date: 1-Apr-2023
Source: Energies, 2023, vol. 16, iss. 8
Volume: 16
Issue: 8
Journal: Energies 
Abstract: In an era of rapid technological improvements, state-of-the-art methodologies and tools dedicated to protecting and promoting our cultural heritage should be developed and extensively employed in the contemporary built environment and lifestyle. At the same time, sustainability principles underline the importance of the continuous use of historic or vernacular buildings as part of the building stock of our society. Adopting a holistic, integrated, multi-disciplinary strategy can link technological innovation with the conservation and restoration of heritage buildings. This paper presents the ongoing research and results of the application of Machine Learning methods for the remote monitoring of the built environment of the historic cluster in Cypriot cities. This study is part of an integrated, multi-scale, and multi-disciplinary study of heritage buildings, with the end goal of creating an online HBIM platform for urban monitoring.
URI: https://hdl.handle.net/20.500.14279/30036
ISSN: 19961073
DOI: 10.3390/en16083461
Rights: © by the authors
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation : The Cyprus Institute 
Cyprus University of Technology 
Frederick University 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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