
Urban landscapes are affected by direct human activities across different economic sectors and artificial and anthropogenic disasters. These events significantly alter the typical appearance of cities, including the layout of avenues, streets, public spaces, and industrial areas that are densely packed with infrastructure. Geoinformation technologies and remote sensing methods allow us to understand and assess the consequences of a disaster. This work focuses on using modern technologies to identify damaged and destroyed buildings in Kharkiv city due to hostilities, regardless of their purpose. The synthesis of remote sensing data and open sources allows for more accurate and qualitative detection of building destruction to organize measures for its further restoration. The research describes a methodology for using free high- and medium-resolution remote sensing data in combination with social media and open registers to identify objects of destruction caused by shelling. Based on the results obtained, it can be concluded that additional independent sources must verify the classification of radar data. This will allow us to get a more reliable result.
Autor / Author: | Kin, Danylo; Lazorenko, Nadiia; Karpinskyi, Yurii; Lyashchenko, Anatoliy; Pliushch, Tetiana; Pomortseva, Оlena |
Institution / Institution: | Kyiv National University of Construction and Architecture, Kyiv/Ukraine; Kyiv National University of Construction and Architecture, Kyiv/Ukraine; Kyiv National University of Construction and Architecture, Kyiv/Ukraine; Kyiv National University of Construction and Architecture, Kyiv/Ukraine; Kyiv National University of Construction and Architecture, Kyiv/Ukraine; V.N. Karazin Kharkiv National University, Kharkiv/Ukraine |
Seitenzahl / Pages: | 10 |
Sprache / Language: | Englisch |
Veröffentlichung / Publication: | JoDLA – Journal of Digital Landscape Architecture, 10-2025 |
Tagung / Conference: | Digital Landscape Architecture 2025 – Collaboration |
Veranstaltungsort, -datum / Venue, Date: | Dessau Campus of Anhalt University, Germany 04-06-25 - 07-06-25 |
Schlüsselwörter (de): | |
Keywords (en): | Geoinformation modelling, change detections, geospatial analysis, remote sensing, damaged buildings |
Paper review type: | Full Paper Review |
DOI: | doi:10.14627/537754032 |
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