Please use this identifier to cite or link to this item: https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-37-2020
Title: EXPLORATION of OPEN DATA in SOUTHEAST ASIA to GENERATE 3D BUILDING MODELS
Authors: Biljecki, F. 
Issue Date: 2020
Publisher: Copernicus GmbH
Citation: Biljecki, F. (2020). EXPLORATION of OPEN DATA in SOUTHEAST ASIA to GENERATE 3D BUILDING MODELS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 6 (4/W1) : 37-44. ScholarBank@NUS Repository. https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-37-2020
Rights: Attribution 4.0 International
Abstract: This article investigates the current status of generating 3D building models across 11 countries in Southeast Asia from publicly available data, primarily volunteered geoinformation (OpenStreetMap). The following countries are analysed: Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor-Leste, and Vietnam. This cross-country study includes multiple spatial levels of analysis: country, town, and micro-level (smaller neighbourhood). The main finding is that authoritative data to generate 3D building models is almost non-existent while building completeness in OpenStreetMap is highly heterogeneous, yielding location-dependent conclusions. While in general just a fraction of mapped buildings has height information and none of the administrative areas provides sufficient information to generate 3D building models, on a micro-level some areas are fully complete, providing a high potential to generate 3D building models on a precinct scale, which may be useful for certain spatial analyses. Furthermore, some areas have high building completeness, requiring only half of the work necessary for the extrusion: the collection of building height attributes. As a part of this work, a semantic 3D building model of a selected set of buildings in Singapore has been generated and released as open data (CityJSON), and the developed code was open-sourced. © Authors 2020.
Source Title: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
URI: https://scholarbank.nus.edu.sg/handle/10635/199711
ISSN: 2194-9042
DOI: 10.5194/isprs-annals-VI-4-W1-2020-37-2020
Rights: Attribution 4.0 International
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