User Preference Maps: Quantifying the Built Environment
The built environment in which we live holds the potential to provide life experiences that allow pedestrians to observe, feel, learn, and grow through their surroundings in everyday urban spaces. If a city offers opportunities for careful observation and exploration according to users’ preferences,...
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MDPI AG
2024-10-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/14/11/3463 |
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| author | Sanghyun Son Hyoensu Kim |
| author_facet | Sanghyun Son Hyoensu Kim |
| author_sort | Sanghyun Son |
| collection | DOAJ |
| description | The built environment in which we live holds the potential to provide life experiences that allow pedestrians to observe, feel, learn, and grow through their surroundings in everyday urban spaces. If a city offers opportunities for careful observation and exploration according to users’ preferences, it will become more appealing to many people. This study selected Midtown, New York, as the research site and collected a total of seven datasets based on 30 intersections in the area. The data, categorized into three main areas—activity, comfort, and natural elements—were evaluated, visualized, and restructured using a path exploration algorithm to produce a final user-based map. For this, 3D modeling software Rhino version 7, visual programming tool Grasshopper, and Grasshopper verion 2023 plugin programs were used. The final result included 3D route information, quantitative measurement data, and multidimensional visual materials. This approach presents an alternative to traditional route navigation based on uniform criteria and, through data-driven design, is believed to ultimately enhance walkability, activate urban spaces, and contribute to the development of sustainable cities. The scope of related research can further expand as the targets, duration, and methods of data collection continue to evolve and as case studies in various cities increase. |
| format | Article |
| id | doaj-art-576cc1a2e4364054a8c73e3ff73c1d61 |
| institution | OA Journals |
| issn | 2075-5309 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj-art-576cc1a2e4364054a8c73e3ff73c1d612025-08-20T02:28:11ZengMDPI AGBuildings2075-53092024-10-011411346310.3390/buildings14113463User Preference Maps: Quantifying the Built EnvironmentSanghyun Son0Hyoensu Kim1School of Architecture, University of Ulsan, Ulsan 44160, Republic of KoreaSchool of Architecture, University of Ulsan, Ulsan 44160, Republic of KoreaThe built environment in which we live holds the potential to provide life experiences that allow pedestrians to observe, feel, learn, and grow through their surroundings in everyday urban spaces. If a city offers opportunities for careful observation and exploration according to users’ preferences, it will become more appealing to many people. This study selected Midtown, New York, as the research site and collected a total of seven datasets based on 30 intersections in the area. The data, categorized into three main areas—activity, comfort, and natural elements—were evaluated, visualized, and restructured using a path exploration algorithm to produce a final user-based map. For this, 3D modeling software Rhino version 7, visual programming tool Grasshopper, and Grasshopper verion 2023 plugin programs were used. The final result included 3D route information, quantitative measurement data, and multidimensional visual materials. This approach presents an alternative to traditional route navigation based on uniform criteria and, through data-driven design, is believed to ultimately enhance walkability, activate urban spaces, and contribute to the development of sustainable cities. The scope of related research can further expand as the targets, duration, and methods of data collection continue to evolve and as case studies in various cities increase.https://www.mdpi.com/2075-5309/14/11/3463user preference mappedestrian route navigationbuilt environmentdataalgorithm |
| spellingShingle | Sanghyun Son Hyoensu Kim User Preference Maps: Quantifying the Built Environment Buildings user preference map pedestrian route navigation built environment data algorithm |
| title | User Preference Maps: Quantifying the Built Environment |
| title_full | User Preference Maps: Quantifying the Built Environment |
| title_fullStr | User Preference Maps: Quantifying the Built Environment |
| title_full_unstemmed | User Preference Maps: Quantifying the Built Environment |
| title_short | User Preference Maps: Quantifying the Built Environment |
| title_sort | user preference maps quantifying the built environment |
| topic | user preference map pedestrian route navigation built environment data algorithm |
| url | https://www.mdpi.com/2075-5309/14/11/3463 |
| work_keys_str_mv | AT sanghyunson userpreferencemapsquantifyingthebuiltenvironment AT hyoensukim userpreferencemapsquantifyingthebuiltenvironment |