Thông tin tài nguyên

The spatial configuration of local climate zones reveals effects on wayfinding in human walking

pmc-PMC10490918.pdf · Phiên bản 1 · 18 trang

18
Bản gốc
Trang 17 · Đoạn 39Vị trí nguồn

20. Middel A., Ha¨ b K., Brazel A. J., Martin C. A., & Guhathakurta S. (2014). Impact of urban form and design on mid-afternoon microclimate in Phoenix Local Climate Zones. Landscape and Urban Planning, 122, 16–28. https://doi.org/10.1016/j.landurbplan.2013.11.004 21. Shi Y., Ren C., Lau K. K. L., & Ng E. (2019). Investigating the influence of urban land use and landscape pattern on PM2.5 spatial variation using mobile monitoring and WUDAPT. Landscape and Urban Plan- ning, 189, 15–26. https://doi.org/10.1016/J.LANDURBPLAN.2019.04.004 22. Simanjuntak R. M., Kuffer M., & Reckien D. (2019). Object-based image analysis to map local climate zones: The case of Bandung, Indonesia. Applied Geography, 106, 108–121. https://doi.org/10.1016/J. APGEOG.2019.04.001 23. Hui E. C. M., Li X., Chen T., & Lang W. (2020). Deciphering the spatial structure of China’s megacity region: A new bay area—The Guangdong-Hong Kong-Macao Greater Bay Area in the making. Cities, 105, 102168. https://doi.org/10.1016/j.cities.2018.10.011 24. Liu F., Zhao Y., Muhammad R., Liu X., & Chen M. (2020). Impervious Surface Expansion: A Key Indica- tor for Environment and Urban Agglomeration—A Case Study of Guangdong-Hong Kong-Macao Greater Bay Area by Using Landsat Data. Journal of Sensors. https://doi.org/10.1155/2020/3896589 25. Hillier B., & Hanson J. (1984). The Social Logic of Space. Cambridge University Press. 26. Peponis J., Zimring C., & Choi Y. K. (1990). Finding the building in wayfinding. Environment and Behav- ior, 22(5), 555–590.

Trang 17 · Đoạn 40Vị trí nguồn

27. Girotto, S., & Haq, S. (2003). Ability and intelligibility: Wayfinding and environmental cognition in the designed. 4th International Space Syntax Symposium. 28. Zabihi A., Safizadeh M., & Marzbali M. H. (2021). Wayfinding in hospital landscape: syntactical analysis of planting design in hospitals in Kerman, Iran. Journal of Facilities Management. https://doi.org/10. 1108/JFM-12-2020-0089 29. Cooper C. H. V., & Chiaradia A. J. F. (2020). sDNA: 3-d spatial network analysis for GIS, CAD, Com- mand Line & Python. SoftwareX, 12, 100525. https://doi.org/10.1016/j.softx.2020.100525 30. He S., Yu S., Wei P., & Fang C. (2019). A spatial design network analysis of street networks and the locations of leisure entertainment activities: A case study of Wuhan, China. Sustainable Cities and Soci- ety, 44, 880–887. https://doi.org/10.1016/j.scs.2018.11.007 31. Zheng S., & Zheng J. (2014). Assessing the completeness and positional accuracy of OpenStreetMap in China. In Thematic cartography for the society (pp. 171–189). https://doi.org/10.1007/978-3-319- 08180-9_14 32. Haklay M. (2010). How good is volunteered geographical information? A comparative study of Open- StreetMap and ordnance survey datasets. Environment and Planning B: Planning and Design, 37(4), 682–703. https://doi.org/10.1068/b35097 33. Brovelli M. A., Minghini M., Molinari M. E., & Zamboni G. (2016). Positional accuracy assessment of the OpenStreetMap buildings layer through automatic homologous pairs detection: the method and a case

Trang 17 · Đoạn 41Vị trí nguồn

study. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sci- ences, XLI-B2, 615–620. https://doi.org/10.5194/isprsarchives-XLI-B2-615-2016 34. Girres J.-F., & Touya G. (2010). Quality Assessment of the French OpenStreetMap Dataset. Transac- tions in GIS, 14(4), 435–459. https://doi.org/10.1111/j.1467-9671.2010.01203.xï 35. Xu F. F., Lin B. Y., Lu Q., Huang Y., & Zhu K. Q. (2016). Cross-region Traffic Prediction for China on OpenStreetMap. ISPRS International Journal of Geo-Information, 5(12), 232. https://doi.org/10.1145/ 3003965.3003972 36. Penn A. (2003). Space syntax and spatial cognition: Or why the axial line? Environment and Behavior, 35(1), 30–65. https://doi.org/10.1177/0013916502238864 37. Ma F. (2020). Spatial equity analysis of urban green space based on spatial design network analysis (sDNA): A case study of central Jinan, China. Sustainable Cities and Society, 60(May), 102256. https:// doi.org/10.1016/j.scs.2020.102256 38. Demuzere M., Kittner J., & Bechtel B. (2021). LCZ Generator: A Web Application to Create Local Cli- mate Zone Maps. Frontiers in Environmental Science, 9. https://doi.org/10.3389/fenvs.2021.637455 39. Bechtel B., Alexander P. J., Bo¨hner J., Ching J., Conrad O., Feddema J., et al (2015). Mapping local cli- mate zones for a worldwide database of the form and function of cities. ISPRS International Journal of Geo-Information, 4(1), 199–219. https://doi.org/10.3390/ijgi4010199 40. Conrad O., Bechtel B., Bock M., Dietrich H., Fischer E., Gerlitz L., et al (2015). System for Automated

Trang 17 · Đoạn 42Vị trí nguồn

Geoscientific Analyses (SAGA) v. 2.1.4. Geoscientific Model Development, 8(7), 1991–2007. https:// doi.org/10.5194/gmd-8-1991-2015 41. Ren C., Cai M., Li X., Zhang L., Wang R., Xu Y., et al (2019). Assessment of Local Climate Zone Classi- fication Maps of Cities in China and Feasible Refinements. Scientific Reports, 9(1), 1–11. https://doi. org/10.1038/s41598-019-55444-9 PMID: 31827216 PLOS ONE The spatial configuration for wayfinding PLOS ONE | https://doi.org/10.1371/journal.pone.0289780 September 8, 2023 17 / 18