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Digital Excavation of Mediatized Urban Heritage: Automated Recognition of Buildings in Image Sources
[Zeitschriftenartikel]
Abstract Digital technologies provide novel ways of visualizing cities and buildings. They also facilitate new methods of analyzing the built environment, ranging from artificial intelligence (AI) to crowdsourced citizen participation. Digital representations of cities have become so refined that they challe... mehr
Digital technologies provide novel ways of visualizing cities and buildings. They also facilitate new methods of analyzing the built environment, ranging from artificial intelligence (AI) to crowdsourced citizen participation. Digital representations of cities have become so refined that they challenge our perception of the real. However, computers have not yet become able to detect and analyze the visible features of built structures depicted in photographs or other media. Recent scientific advances mean that it is possible for this new field of computer vision to serve as a critical aid to research. Neural networks now meet the challenge of identifying and analyzing building elements, buildings and urban landscapes. The development and refinement of these technologies requires more attention, simultaneously, investigation is needed in regard to the use and meaning of these methods for historical research. For example, the use of AI raises questions about the ways in which computer-based image recognition reproduces biases of contemporary practice. It also invites reflection on how mixed methods, integrating quantitative and qualitative approaches, can be established and used in research in the humanities. Finally, it opens new perspectives on the role of crowdsourcing in both knowledge dissemination and shared research. Attempts to analyze historical big data with the latest methods of deep learning, to involve many people - laymen and experts - in research via crowdsourcing and to deal with partly unknown visual material have provided a better understanding of what is possible. The article presents findings from the ongoing research project ArchiMediaL, which is at the forefront of the analysis of historical mediatizations of the built environment. It demonstrates how the combination of crowdsourcing, historical big data and deep learning simultaneously raises questions and provides solutions in the field of architectural and urban planning history.... weniger
Thesaurusschlagwörter
Stadt; Gebäude; Visualisierung; Digitalisierung; künstliche Intelligenz; Stadtentwicklung; Architektur; historische Entwicklung
Klassifikation
Raumplanung und Regionalforschung
Naturwissenschaften, Technik(wissenschaften), angewandte Wissenschaften
Freie Schlagwörter
automated image content recognition; big data; computer vision; crowdsourcing; image repositories; urban heritage
Sprache Dokument
Englisch
Publikationsjahr
2020
Seitenangabe
S. 24-34
Zeitschriftentitel
Urban Planning, 5 (2020) 2
Heftthema
Visual Communication in Urban Design and Planning: The Impact of Mediatisation(s) on the Construction of Urban Futures
ISSN
2183-7635
Status
Veröffentlichungsversion; begutachtet (peer reviewed)