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  4. An Application of Machine Learning Algorithms by Synergetic Use of SAR and Optical Data for Monitoring Historic Clusters in Cypriot Cities
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An Application of Machine Learning Algorithms by Synergetic Use of SAR and Optical Data for Monitoring Historic Clusters in Cypriot Cities

Journal
Energies
Date Issued
April 1, 2023
Author(s)
Tzima, Maria Spyridoula  
Agapiou, Athos  
Lysandrou, Vasiliki  
Artopoulos, Georgios  
Fokaides, Paris  
Chrysostomou, Charalambos  
DOI
10.3390/en16083461
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.
Subjects

change detection

historic architecture...

land cover classifica...

machine learning

remote sensing

Sentinel-1

Sentinel-2

SNAP

urban heritage

File(s)
Thumbnail Image
Name

energies-16-03461.pdf

Size

13.82 MB

Format

Adobe PDF

Checksum (MD5)

739f3776a3087b0b5813dff2af8ae5ee

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