Clustering analysis of the nineteen most populous Hungarian cities using Urban Atlas Building Height Data from Copernicus Land Monitoring Service's 10m raster maps

Tóth, Zsolt György (2024) Clustering analysis of the nineteen most populous Hungarian cities using Urban Atlas Building Height Data from Copernicus Land Monitoring Service's 10m raster maps. In: Wood 4 Sustainability. Soproni Egyetem Kiadó, Sopron, pp. 191-199. ISBN 9789633345412

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Absztrakt (kivonat)

This pilot study delves into the clustering of Hungarian cities based on building height data extracted from Copernicus Building Height 2012 (BH2012) raster maps. BH2012 raster maps have proven overall reliability, yet their potential for city classification and clustering re-mains underexplored in the literature. While previous studies often prioritize sociological-historical analyses, this research takes a data-driven approach, emphasizing the significance of building height as a fundamental indicator of urban character. By employing four distinct clustering methods, including both legislative criteria and univariate k-means algorithms, this study aims to elucidate underlying patterns in the distribution of building heights across ma-jor Hungarian cities. The univariate k-means clustering approach yields more coherent clus-ters compared to methods based on regulatory frameworks, underscoring the efficacy of data-driven methodologies in capturing nuanced urban characteristics.

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Soproni Egyetem

Mű tipusa:	Könyv része
SWORD Depositor:	Teszt Sword
Felhasználó:	Csaba Horváth
A mű MTMT azonosítója:	MTMT:35997678
Dátum:	20 Már 2025 07:52
Utolsó módosítás:	20 Már 2025 07:52
URI:	http://publicatio.uni-sopron.hu/id/eprint/3511

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