ARTICLE | doi:10.20944/preprints202302.0435.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning; remote sensing; Sentinel-1; Sentinel-2; SNAP; land cover classification; change detection; urban heritage; historic architecture clusters
Online: 27 February 2023 (03:24:59 CET)
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 bridge technological innovation with conserving and restoring heritage buildings. The paper presents 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-discipline study of heritage buildings towards the creation of an online HBIM platform for urban monitoring.
ARTICLE | doi:10.20944/preprints201609.0055.v1
Subject: Arts And Humanities, Archaeology Keywords: change detection; Cultural Heritage; texture analysis
Online: 18 September 2016 (08:38:10 CEST)
The intentional damages to local Cultural Heritage sites carried out in recent months by the Islamic State have received wide coverage from the media worldwide. Earth Observation data provide important information to assess these damages in such non-accessible areas, and automated image processing techniques would be needed to speed up the analysis if a fast response is desired. This paper shows the first results of applying fast and robust change detection techniques to sensitive areas, based on the extraction of textural information and robust differences of brightness values related to pre- and post-disaster satellite images. A map highlighting potentially damaged buildings is derived, which could help experts at timely assessing the damages to the Cultural Heritage sites of interest. Encouraging results are obtained for two archaeological sites in Syria and Iraq.