為因應全球氣候變遷與都市化加劇的熱島效應，永續的城市降溫方式成為應對高溫、從本質上降低機械冷卻需求與提升環境韌性的關鍵。其中風廊作為自然為基礎的解決方法（Nature-Based Solutions, NBS）之一，透過促進自然風的流動以達到緩解城市高溫、改善空氣品質和減緩疾病傳播等多重效益。然而，現有研究多聚焦於指認城市內合適的風廊道位置，提出街道和建築尺度的風廊規劃，少有以整體城市尺度探討不同類型應用風廊的潛力與適用的都市規劃手段；另外過去臺灣在進行空間規劃時，也較少對都市發展方向進行有目的的規劃。因此，本研究基於熱島效應下風廊的規劃需求與概念，探討風環境與建成區面積、道路、建築高度、河流、綠地和冷熱源等土地使用的交互關係，檢視時空變遷下的都市發展，以期探索未來在考量風場環境的情況下對都市進行規劃的可能性。本研究以四個階段進行，首先藉由核密度分析指認臺南市建成區密度中心；接著，透過基於地理資訊系統的方向環域分析辨別都市發展方向，再以方位角面積分析進行道路和河流方向統計，最終再結合河流、綠地與樓地板面積比例等8個變數透過階層式集群分析，將49個子研究區分為市中心高溫密集型、沿海淺山混和型、中部平原均值型和通風發展潛力最佳之北側高潛力通透型共4群，並依據不同類型特徵，延伸各區域的冷熱源分析及未來都市規劃相應的建議與討論。本研究旨在探討以風環境改善城市地區的熱島效應，檢視現有都市發展並提供未來進行以自然環境條件促進減緩與調適的政策制定及空間規劃的基礎，提升都市永續性及整體生活品質。

In response to the intensified urban heat island effect driven by global climate change and urbanization, sustainable cooling is key to reducing mechanical cooling demand and enhancing environmental resilience. Among them, wind corridors, as Nature-Based Solutions, facilitate natural airflow to mitigate urban heat and reduce disease transmission. However, most studies focus on corridor locations and street- or building-scale designs, with few examining city-scale potential of corridor types and applicable planning measures. In addition, spatial planning in Taiwan has rarely considered directional factors in development strategies. Therefore, the study examines interactions between wind environments and land use—built-up area, road and river orientation, building height, green space, and thermal sources—under the UHI context, aiming to explore planning possibilities that account for wind conditions. In terms of methodology, the research first identified high-density built-up centers in Tainan City using kernel density analysis, then determined urban growth directions through GIS-based directional sector analysis, followed by azimuthal statistical analysis of roads and rivers. Finally, combining eight variables, including river, green space, and floor area ratio, hierarchical cluster analysis classified 49 subareas into four types: dense urban-core heat concentration, coastal–foothill mixed, central plain average, and highly permeable northern high-potential. Based on these typologies, thermal source analysis and corresponding planning suggestions were developed. The study provides a foundation for climate-responsive planning and policy that leverage natural conditions to enhance sustainability, livability.

1. 中央氣象署(2023)。中華民國 112 年氣候資料年報第一部分–地面資料。
2. 內政部建築研究所 (2018)。跨不同地況區域之風廊建置分析及都市通風環境評估成果報告書。內政部。
3. 李娟、李苗裔、龍瀛、黨安榮 (2016) 。基於百度熱力圖的中國多中心城市分析。上海城市規劃，3，30-36。
4. 林子平、蔡沛淇、歐星妤、張洲滄(2023)。熱島效應緩解策略之風廊系統的指認與應用。土木水利，第五十卷(第一期)，24–29。https://doi.org/10.6653/MoCICHE.202302_50(1).0005
5. 東京都都市整備局 (2020)。風の道確保等に関するガイドライン。東京都。https://www.toshiseibi.metro.tokyo.lg.jp/documents/d/toshiseibi/pdf_seisaku_guideline2020_pdf_siryo_07
6. 邱彥穎(2024)。二元水迴圈系統觀點下水資源NBS潛力之空間分群特徵 —以台南市鹽水溪流域為例（博碩士論文，國立成功大學，臺南市，台灣）。取自https://hdl.handle.net/11296/z6p473
7. 陳怡伶(2025)。 都市風廊指認與風速驗證及推估。未出版之碩士論文。國立成功大學建築學系，臺南市。
8. 許晃雄、王俊寓、王柳臻、吳威德、李欣輯、李思瑩、李時雨、林子平、林靜君、侯淸賢、凃柏安、施意敏、洪若雅、洪景山、紀佳法、張雅惠、陳正達、陳永明、陳保中、……、羅資婷(2024a)。暖化趨勢下的臺灣極端高溫與衝擊。新北市：國家災害防救科技中心。
9. 許晃雄、王嘉琪、陳正達、李明旭、詹士樑 (2024b)。國家氣候變遷科學報告2024：現象、衝擊與調適 [許晃雄、李明旭 主編]。國家科學及技術委員會與環境部聯合出版。
10. 新北市政府(2013)。《新北市板橋（江翠北側地區）都市設計審議原則》。
11. 臺中市政府(2020)。《臺中市都市更新建築容積獎勵辦法》。
12. 臺中市政府都市發展局(2023)。永續城鄉宜居環境—臺中都市熱島效應空間策略計畫成果報告書。
13. 臺北市政府(2024)。擬定「臺北市開發基地體感降溫專案」細部計畫案。
14. 臺南市政府(2017)。《高速鐵路臺南車站特定區(公三、公六、產業專用區)都市設計準則(配合沙崙綠能科學城計畫)》。
15. 臺南市政府(2022)。臺南市氣候變遷調適計畫 2020修正版。臺南市政府。https://w3fs.tainan.gov.tw/001/Upload/159/ebook/ebook_512594//pdf/full.pdf
16. 臺南市政府環境保護局(2024)。臺南市氣候變遷調適執行方案(初稿)。臺南市政府。
17. 環境部(2023)。國家氣候變遷調適行動計畫（112-115 年）（核定本）。
18. 黨冰、房小怡、呂紅亮、程宸、杜吳鵬、劉勇洪、張碩、楊帆(2017)基於氣象研究的城市通風廊道構建初探——以南京江北新區為例。氣象，Vol. 43，Issue (9): 1130-1137. DOI: 10.7519/j.issn.1000-0526.2017.09.010
19. Ahmed, A. S. (2011). Investigation of wind characteristics and wind energy potential at Ras Ghareb, Egypt. Renewable & Sustainable Energy Reviews, 15(6), 2750-2755. https://doi.org/10.1016/j.rser.2011.04.003
20. Arif, M., & Gupta, K. (2020a). Application of graph-based model for the quantification of transport network in periurban interface of Burdwan City India. Spatial Information Research, 28(4), 447–457. https:// doi. org/10. 1007/s41324- 019- 00305-w
21. Arif, M., & Gupta, K. (2020b). Spatial development planning in peri-urban space of Burdwan City, West Bengal, India: Statutory infrastructure as mediating factors.SN Applied Sciences, 2(11), 1–19. https:// doi. org/ 10. 1007/ s42452- 020- 03587-0
22. Arif, M., Sengupta, S., Mohinuddin, S. K., & Gupta, K. (2023). Dynamics of land use and land cover change in peri urban area of Burdwan city, India: a remote sensing and GIS based approach. Geojournal, 88(4), 4189-4213. https://doi.org/10.1007/s10708-023-10860-3
23. Athukorala, D., & Murayama, Y. (2021). Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban-Rural Gradient. Remote Sensing, 13(7). https://doi.org/ARTN 139610.3390/rs13071396
24. Boeing, G. (2019). Urban spatial order: street network orientation, configuration, and entropy. Applied Network Science, 4(1). https://doi.org/ARTN 67 10.1007/s41109-019-0189-1
25. Chang, S. Z., Jiang, Q. G., & Zhao, Y. (2018). Integrating CFD and GIS into the Development of Urban Ventilation Corridors: A Case Study in Changchun City, China. Sustainability, 10(6). https://doi.org/ARTN 181410.3390/su10061814
26. Chen, YC., Lin, TP. & Lin, CT.(2017). A simple approach for the development of urban climatic maps based on the urban characteristics in Tainan, Taiwan. Int J Biometeorol 61, 1029–1041. https://doi.org/10.1007/s00484-016-1282-0
27. Deribew, K. T. (2020). Spatiotemporal analysis of urban growth on forest and agricultural land using geospatial techniques and Shannon entropy method in the satellite town of Ethiopia, the western fringe of Addis Ababa city. Ecological Processes, 9(1). https://doi.org/ARTN 4610.1186/s13717-020-00248-3
28. Du, P., Gui, H. Q., Zhang, J. S., Liu, J. G., Yu, T. Z., Wang, J., Cheng, Y., & Shi, Z. B. (2018). Number size distribution of atmospheric particles in a suburban Beijing in the summer and winter of 2015. Atmospheric Environment, 186, 32-44. https:// doi.org/ 10.1016/ j.atmosenv.2018.05.023
29. Energy Sector Management Assistance Program. (2020). Primer for Cool Cities: Reducing Excessive Urban Heat–With a Focus on Passive Measures. World Bank.
30. Estoque, R. C., Murayama, Y., & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349-359. https://doi.org/10.1016/j.scitotenv.2016.10.195
31. European Commission（2020）.Nature-Based Solutions & Re-Naturing Cities. European Union. doi: 10.2777/440514
32. Fang, Y. H., Gu, K. K., Qian, Z., Sun, Z., Wang, Y. Z., & Wang, A. (2021). Performance evaluation on multi-scenario urban ventilation corridors based on least cost path. Journal of Urban Management, 10(1), 3-15. https://doi.org/10.1016/j.jum.2020.06.006
33. Fovell, R. G., & Fovell, M. Y. C. (1993). Climate Zones of the Conterminous United-States Defined Using Cluster-Analysis. Journal of Climate, 6(11), 2103-2135. https://doi.org/Doi10.1175/1520-0442(1993)006<2103:Czotcu>2.0.Co;2
34. Heusinger, J., & Sailor, D. J. (2019). Heat and Cold Roses of US Cities: a New Tool for Optimizing Urban Climate. Sustainable Cities and Society, 51. https://doi.org/ARTN 10177710.1016/j.scs.2019.101777
35. Hsieh, C. M., & Huang, H. C. (2016). Mitigating urban heat islands: A method to identify potential wind corridor for cooling and ventilation. Computers Environment and Urban Systems, 57, 130-143. https://doi.org/10.1016/j.compenvurbsys.2016.02.005
36. Jung, W. K., & Kim, G. (2024). Reduction of Fine Dust and Alleviation of Heat Island Effect: An Analysis of Cold Air Flow in Pohang City, South Korea. Land, 13(3). https://doi.org/ARTN 34710.3390/land13030347
37. Kim, T. S., Park, K. A., Li, X. F., Mouche, A. A., Chapron, B., & Lee, M. J. (2017). Observation of Wind Direction Change on the Sea Surface Temperature Front Using High-Resolution Full Polarimetric SAR Data. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(6), 2599-2607. https://doi.org/10.1109/Jstars.2017.2660858
38. Lai, S. X., Zhao, Y. J., Fan, Y. F., & Ge, J. (2021). Characteristics of daytime land surface temperature in wind corridor: A case study of a hot summer and warm winter city. Journal of Building Engineering, 44. https://doi.org/ARTN 103370 10.1016/j.jobe.2021.103370
39. Lau, T. K., Tsai, P. C., Ou, H. Y., & Lin, T. P. (2024). Efficient and cost-effective method for identifying urban ventilation corridors using a heuristic search algorithm. Sustainable Cities and Society, 101. https://doi.org/ARTN 10514410.1016/j.scs.2023.105144
40. Lea A. Ruefenacht & Juan Angel Aacero (2017).Strategies for Cooling Singapore. Singapore : Cooling Singapore.
41. Liu Shuyu, Song Daifeng, Wang Shaosen (2015).The Evolution of Urban Climatic Map and Corresponding Guidance for Urban Planning in Germany. Urban Planning International , 30(3) , 84-90.
42. Mosammam, H., Nia, J., Khani, H., et al. (2017). Monitoring land use change and measuring urban sprawl based on its spatial forms the case of Qom City. Egypt Journal Remote Sensing Space Science, 20(1), 103–116. https://doi.org/10.1016/j.ejrs.2016.08.002
43. Pes, M. P., Pereira, E. B., Marengo, J. A., Martins, F. R., Heinemann, D., & Schmidt, M. (2017). Climate trends on the extreme winds in Brazil. Renewable Energy, 109, 110-120. https://doi.org/10.1016/j.renene.2016.12.101
44. Phelan, P. E., Kaloush, K., Miner, M., Golden, J., Phelan, B., Silva, H., & Taylor, R. A. (2015). Urban Heat Island: Mechanisms, Implications, and Possible Remedies. Annual Review of Environment and Resources, Vol 40, 40, 285-307. https://doi.org/10.1146/annurev-environ-102014-021155
45. Ratto, G., Berri, G. J., & Maronna, R. (2014). On the application of hierarchical cluster analysis for synthesizing low-level wind fields obtained with a mesoscale boundary layer model. Meteorological Applications, 21(3), 708-716. https://doi.org/10.1002/met.1396
46. Ratto, G., Maronna, R., & Berri, G. (2010). Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata, Argentina. Boundary-Layer Meteorology, 137(3), 477-492. https://doi.org/10.1007/s10546-010-9539-3
47. Ren, C., Yang, R. Z., Cheng, C., Xing, P., Fang, X. Y., Zhang, S., Wang, H. F., Shi, Y., Zhang, X. Y., Kwok, Y. T., & Ng, E. (2018). Creating breathing cities by adopting urban ventilation assessment and wind corridor plan - The implementation in Chinese cities. Journal of Wind Engineering and Industrial Aerodynamics, 182, 170-188. https://doi.org/10.1016/j.jweia.2018.09.023
48. Sobstyl, J. M., Emig, T., Qomi, M. J. A., Ulm, F. J., & Pellenq, R. J. M. (2018). Role of City Texture in Urban Heat Islands at Nighttime. Physical Review Letters, 120(10). https://doi.org/ARTN 10870110.1103/PhysRevLett.120.108701
49. Son, J. M., Eum, J. H., & Kim, S. (2022). Wind corridor planning and management strategies using cold air characteristics: The application in Korean cities. Sustainable Cities and Society, 77. https://doi.org/ARTN 10351210.1016/j.scs.2021.103512
50. United Nations Environment Programme (2021). Beating the Heat: A Sustainable Cooling Handbook for Cities. Nairobi.
51. Wang, L., Hou, C., Zhang, Y. C., & He, J. (2024). Measuring solar radiation and spatio-temporal distribution in different street network direction through solar trajectories and street view images. International Journal of Applied Earth Observation and Geoinformation, 132. https://doi.org/ARTN 10405810.1016/j.jag.2024.104058
52. Wang, X. J., Liu, G. X., Xiang, A. C., Xiao, S. M., Lin, D. R., Lin, Y. B., & Lu, Y. (2023). Terrain gradient response of landscape ecological environment to land use and land cover change in the hilly watershed in South China. Ecological Indicators, 146. https://doi.org/ARTN 10979710.1016/j.ecolind.2022.109797
53. Woldesemayat, E. M., & Genovese, P. V. (2021). Monitoring Urban Expansion and Urban Green Spaces Change in Addis Ababa: Directional and Zonal Analysis Integrated with Landscape Expansion Index. Forests, 12(4). https://doi.org/ARTN 38910.3390/f12040389
54. World Bank(2022). Piloting Nature-based Solutions for Urban Cooling Overview. Washington, DC: World Bank.
55. World Meteorological Organization(2024).European State of the Climate 2023.
56. Yang, Y. Y., Liu, Y. S., Li, Y. R., & Du, G. M. (2018). Quantifying spatio-temporal patterns of urban expansion in Beijing during 1985-2013 with rural-urban development transformation. Land Use Policy, 74, 220-230. https://doi.org/10.1016/j.landusepol.2017.07.004
57. Zhang, S. W., Kwok, K. C. S., Liu, H. H., Jiang, Y. C., Dong, K. J., & Wang, B. (2021). A CFD study of wind assessment in urban topology with complex wind flow. Sustainable Cities and Society, 71. https://doi.org/ARTN 10300610.1016/j.scs.2021.103006
58. Zhang, S., Fang, X. Y., Cheng, C., Chen, J., Guo, F. X., Yu, Y., & Yang, S. S. (2024). Multi-Scale Urban Natural Ventilation Climate Guidance: A Case Study in the Shijiazhuang Metropolitan Area. Atmosphere, 15(6). https://doi.org/ARTN 67610.3390/atmos15060676