Automated 3D Urban Landscapes Visualization Using Open Data Sources on the Example of the City of Zagreb

Komadina, Adrian; Mihajlović, Željka

doi:10.1007/s42489-022-00102-w

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…While OSM started with a focus on roads, now the community is increasingly spotlighting buildings, and in some locations they are fully mapped, together with attributes (Brovelli & Zamboni 2018;Biljecki 2020). As such, OSM ascended to support a variety of spatial analyses that require building data in academia and beyond (Westrope et al 2014;Cerri et al 2020;Schilling and Tränckner 2020;Braun et al 2021;Ma et al 2022;Zhang et al 2022;Komadina & Mihajlovic 2022). Nevertheless, their completeness, including in developed countries, remains heterogeneous.…”

Section: Openstreetmap and Quality Controlmentioning

confidence: 99%

Mining real estate ads and property transactions for building and amenity data acquisition

Chen

Biljecki

2022

Urban Info

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Acquiring spatial data of fine and dynamic urban features such as buildings remains challenging. This paper brings attention to real estate advertisements and property sales data as valuable and dynamic sources of geoinformation in the built environment, but unutilised in spatial data infrastructures. Given the wealth of information they hold and their user-generated nature, we put forward the idea of real estate data as an instance of implicit volunteered geographic information and bring attention to their spatial aspect, potentially alleviating the challenge of acquiring spatial data of fine and dynamic urban features. We develop a mechanism of facilitating continuous acquisition, maintenance, and quality assurance of building data and associated amenities from real estate data. The results of the experiments conducted in Singapore reveal that one month of property listings provides information on 7% of the national building stock and about half of the residential subset, e.g. age, type, and storeys, which are often not available in sources such as OpenStreetMap, potentially supporting applications such as 3D city modelling and energy simulations. The method may serve as a novel means to spatial data quality control as it detects missing amenities and maps future buildings, which are advertised and transacted before they are built, but it exhibits mixed results in identifying unmapped buildings as ads may contain errors that impede the idea.

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