Cited 0 time in
Data-Driven Analysis Of Spatial Patterns Through Large-Scale Datasets Of Building Floor Plan
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Maeng, Hoyoung | - |
| dc.contributor.author | Hyun, Kyung Hoon | - |
| dc.date.accessioned | 2022-07-07T00:33:03Z | - |
| dc.date.available | 2022-07-07T00:33:03Z | - |
| dc.date.created | 2021-05-14 | - |
| dc.date.issued | 2021-03 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/142235 | - |
| dc.description.abstract | This paper introduces a unique quantitative analysis method and results that are differentiated from those in existing studies. We analyzed five types of information in floor plan images: the silhouette, number of rooms, room area, and direct and indirect room connectivity. Furthermore, the analysis used a large-scale apartment unit dataset consisting of 33,892 units. We present convincing and objective spatial pattern analysis results of Korean apartments by quantitatively analyzing a large-scale dataset. It is expected that the analysis results will clarify the characteristics of the residential environment of Korean apartments. The results suggest that changes in lifestyles lead to the modularization of bedrooms, increased numbers of private bathrooms and balconies with corridors as junctions, and the diversification of room layouts. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) | - |
| dc.title | Data-Driven Analysis Of Spatial Patterns Through Large-Scale Datasets Of Building Floor Plan | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Hyun, Kyung Hoon | - |
| dc.identifier.scopusid | 2-s2.0-85104663837 | - |
| dc.identifier.bibliographicCitation | Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, v.1, pp.301 - 310 | - |
| dc.relation.isPartOf | Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia | - |
| dc.citation.title | Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia | - |
| dc.citation.volume | 1 | - |
| dc.citation.startPage | 301 | - |
| dc.citation.endPage | 310 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Proceeding | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordPlus | Apartment houses | - |
| dc.subject.keywordPlus | Architectural design | - |
| dc.subject.keywordPlus | Floors | - |
| dc.subject.keywordPlus | Houses | - |
| dc.subject.keywordPlus | Large dataset | - |
| dc.subject.keywordPlus | Modular construction | - |
| dc.subject.keywordPlus | Building floors | - |
| dc.subject.keywordPlus | Data-driven analysis | - |
| dc.subject.keywordPlus | Large-scale dataset | - |
| dc.subject.keywordPlus | Large-scale datasets | - |
| dc.subject.keywordPlus | Modularizations | - |
| dc.subject.keywordPlus | Residential environment | - |
| dc.subject.keywordPlus | Spatial pattern analysis | - |
| dc.subject.keywordPlus | Spatial patterns | - |
| dc.subject.keywordPlus | Spatial variables measurement | - |
| dc.subject.keywordAuthor | Floor Plan Analysis | - |
| dc.subject.keywordAuthor | Design Quantification | - |
| dc.subject.keywordAuthor | Residential Layout | - |
| dc.subject.keywordAuthor | Spatial Pattern Analysis | - |
| dc.subject.keywordAuthor | Semantic Fingerprint | - |
| dc.identifier.url | http://papers.cumincad.org/data/works/att/caadria2021_155.pdf | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1366
COPYRIGHT © 2024 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
