大眾運輸場站與周邊土地相互作用，捷運場站的設置提升周遭可及性，進而影響周邊土地使用與活動；同時，都市活動影響捷運場站的設置及運量，都市土地活動與大眾運輸系統相互作用，並且反映於都市現象，難以拆分其因果關係。其中，運輸系統與土地使用發生互動之地區可視為該場站之站域。目前對運輸場站的服務範圍多以最適步行距離為定義作為捷運場站影響範圍而呈現同心圓的站域形態，並且TOD土地使用管制亦以環域為主要概念，並以場站周邊等距的涵蓋範圍作為主要規劃場域。然觀察捷運場站周遭的發展少有同心圓的站域型態，Foda & Osman (2010) 證明等距同心圓之定義方法高估其實際服務範圍，難以反應場站實際空間的發展差異，而使都市計畫土地使用管制缺乏具地區發展差異之發展與管制策略，因此本研究欲探討場站與周邊土地的實際互動範圍。
臺北市作為全臺發展捷運系統最為完整之地區，捷運系統之使用已逾二十年，對於周邊之影響亦最為顯著，本研究選定臺北市作為研究範疇，探討捷運場站與周邊土地互動之關係。本研究透過POI點位的爬取作為土地使用現況資料庫，反映該地當前吸引力，配合樓層數與容積率反映該地土地使用強度。藉由探索式資料分析觀察場站周邊現象，並運用半變異圖探討捷運場站與周邊各向屬性的距離遞減效應，利用各屬性與場站互動的臨界距離界定實際的場站站域，探討捷運場站之站域形態。
研究成果包括1.藉由臺北市POI點位的建置，反映土地使用實際現況；2.透過半變異圖之分析得知捷運場站的影響範圍，驗證環域之影響範圍無法以一概全地代表捷運場站之站域；並且 3.臺北市捷運場站周邊不僅限於點狀發展，然政策之訂定忽略目前發展形態，而4.與捷運場站相互影響之程度又以土地使用較建成環境顯著。

MRT stations whose allocation and volume are affected by urban activities can elevate the accessibility, and affect the land use. The interaction between land use and transit happens in the scope called catchment area, and the correlation of them are inseparable. Current research of MRT station catchment area are mostly defined by the buffer of most suitable walking distance. However, the practical service area which uses the buffer method highly overestimates, and it is difficult to show the differences between each station, so the land use regulations are often lack of the regional difference.
This study chooses Taipei City as the research area to discuss the interaction between land use and transit. Taipei MRT is the most complete MRT network in Taiwan and has significantly impacted on its surrounding area. POI of Taipei was used as the land use database to show the attraction of those places and the floor area ratio and the building floor were used to show the intensity of the land use. With the application of distance decay effect, the semi-variograms are used to discuss the range of the interaction by any directions.
The result includes the following points, first, the semi-variograms verify the buffer area can’t wholly represent the catchment area; second, the development pattern of MRT station surrounding area not only regard the station as the core, but the current plan ignores development pattern; third, the correlation of MRT station and surroundings land use is more significant than the correlation of MRT station and building environment.

1. 毛蒋興、閆小培(2004)。國外城市交通系統與土地利用互動關係研究。城市交通，28(7)。
2. 王一帆(2005)。捷運沿線土地使用變遷之影響因素分析—臺北捷運板南線之實證研究。國立交通大學交通運輸研究所碩士論文，新竹市。
3. 白仁德、劉人華(2014)。大眾運輸導向建成環境特性對捷運運量影響之研究－以臺北捷運為實證對象。建築與規劃學報，15(2&3)，111-127。
4. 王俞翔(2012)。應用GIS分析大眾捷運系統與都市人文空間結構變遷關係之研究─高雄市之個案探討。東海大學行政管理暨政策學系碩士論文，臺中市。
5. 吳雅萱(2013)。捷運站周邊土地混合使用型態之研究。國立成功大學都市計劃研究所碩士論文，臺南市。
6. 李怡婷(2005)。大眾運輸導向發展策略對捷運站區房地產價格之影響分析。國立成功大學都市計劃研究所碩士論文，臺南市。
7. 李家儂(2006)。交通運輸與土地使用整合規劃之演變~大眾運輸導向發展的都市發展模式。土地問題研究季刊，5(3)，70-83。
8. 李家儂、賴宗裕(2007)。臺北都會區大眾運輸導向發展目標體系與策略之建構。地理學報，48(1)，19-42。
9. 李家儂、謝翊楷(2015)。以空間型構法則及步行導向理念檢視 TOD 區內土地使用配置的合理性。運輸計劃季刊，(44)，1-24。
10. 卓易霆(2013)。大眾運輸導向發展觀點下空間特性之研究─以臺北市為例。國立成功大學都市計劃研究所碩士論文，臺南市。
11. 林楨家、蕭博正(2006)。臺北市土地混合使用特性對旅次發生之影響。台灣土地研究，9(1)，89-115。
12. 邱辰(2015)。從空間角度分析公共自行車系統對站點周邊土地活動影響。國立臺灣大學土木工程研究所碩士論文，臺北市。
13. 姜世國(2004)。都市區範圍界定方法探討。地理與地理信息科學，20(1)，67-72。
14. 翁維泰(2010)。捷運系統開發對土地使用與價值之影響：以可及性分析為基礎。國立臺北大學都市計劃研究所碩士論文，新北市。
15. 張笛箏(2007)。捷運站區土地使用變遷之模擬分析-以臺北捷運木柵線為例。國立交通大學交通運輸研究所碩士論文，新竹市。
16. 張學孔、錢學陶、杜雲龍(2000)。大眾運輸導向之都市發展策略。捷運技術半年刊。
17. 黃書偉(2008)。土地混合使用空間型態量測與其影響因素之研究。國立成功大學都市計劃研究所博士論文，臺南市。
18. 劉漢奎、陳建良(2012)。都市公園綠地外部性之空間分析──以臺中市為例。國立彰化師範大學文學院學報，(6)，243-257。
19. 蔡岳霖(2001)。捷運系統營運前後車站周邊地區商業發展之變化。國立交通大學交通運輸研究所碩士論文，新竹市。
20. 謝琦強、莊翰華(2009)。台中市都市土地使用強度「區位特性」之研究－以容積移轉制度為例。地理研究，(51)，23-43。
21. Alonso, W. (1964). Location and land use. Harvard university press.
22. Alshalalfah, B., & Shalaby, A. (2007). Case Study: Relationship of Walk Access Distance to Transit with Service, Travel, and Personal Characteristics. Journal of Urban Planning and Development, 133(2), 114-118.
23. Ann, S., Jiang, M., Mothafer, G. I., & Yamamoto, T. (2019). Examination on the influence area of transit-oriented development: considering multimodal accessibility in New Delhi, India. Sustainability, 11(9), 2621
24. Anselin, L. (1996). Interactive techniques and exploratory spatial data analysis.
25. Badoe, D. A., & Miller, E. J. (2000). Transportation–land-use interaction: empirical findings in North America, and their implications for modeling. Transportation Research Part D: Transport and Environment, 5(4), 235-263.
26. Behne, S. (2019). lxml - XML and HTML with Python.
Retrieved from https://lxml.de/credits.html
27. Bennett, D. G., & Gade, O. (1979). Geographic perspectives in migration research. A bibliographical survey. University of North Carolina at Chapel Hill, Department of Geography.
28. Biba, S., Curtin, K. M., & Manca, G. (2010). A new method for determining the population with walking access to transit. International Journal of Geographical Information Science, 24(3), 347-364.
29. Burgess, T., & Webster, R. (1980). Optimal interpolation and isarithmic mapping of soil properties: I the semi‐variogram and punctual kriging. Journal of soil science, 31(2), 315-331.
30. Canepa, B. (2007). Bursting the Bubble: Determining the Transit-Oriented Development’s Walkable Limits. Transportation Research Record, 1992(1), 28–34.
31. Cervero, R. (1993). Ridership impacts of transit-focused development in California.
32. Cervero, R., & Duncan, M. (2002). Land value impacts of rail transit services in Los Angeles County. Report prepared for National Association of Realtors Urban Land Institute.
33. Cervero, R., & Kockelman, K. (1997). Travel demand and the 3Ds: Density, diversity, and design. Transportation research. Part D: Transport and environment, 2(3), 199-219.
34. Cervero, R., & Landis, J. (1995). The transportation-land use connection still matters. Access Magazine, 1(7), 2-10.
35. Chakraborty, A., & Mishra, S. (2013). Land use and transit ridership connections: Implications for state-level planning agencies. Land Use Policy, 30(1), 458-469.
36. Cheng, C.-L., & Agrawal, A. W. (2010). TTSAT: A new approach to mapping transit accessibility. Journal of Public Transportation, 13(1), 4.
37. Curran, P. J., & Atkinson, P. M. (1998). Geostatistics and remote sensing. Progress in Physical Geography, 22(1), 61-78.
38. De Vries, J. J., Nijkamp, P., & Rietveld, P. (2009). Exponential or power distance-decay for commuting? An alternative specification. Environment and planning A, 41(2), 461-480.
39. Foda, M. A., & Osman, A. O. (2010). Using GIS for measuring transit stop accessibility considering actual pedestrian road network. Journal of Public Transportation, 13(4), 2.
40. Fotheringham, A. S. (1981). Spatial structure and distance‐decay parameters. Annals of the Association of American Geographers, 71(3), 425-436.
41. Gandhi, V. (2008). Semivariogram Modeling. In S. Shekhar & H. Xiong (Eds.), Encyclopedia of GIS (pp. 1042-1046). Boston, MA: Springer US.
42. Gatzlaff, D. H., & Smith, M. T. (1993). The impact of the Miami Metrorail on the value of residences near station locations. Land Economics, 54-66.
43. Giuliano, G. (2004). Land use impacts of transportation investments. The geography of urban transportation, 3, 237-273.
44. Gould, P. (1981). Letting the data speak for themselves. Annals of the Association of American Geographers, 71(2), 166-176.
45. Greenwald, M. J., & Boarnet, M. G. (2001). Built environment as determinant of walking behavior: Analyzing nonwork pedestrian travel in Portland, Oregon. Transportation Research Record, 1780(1), 33-41.
46. Gutiérrez, J., & García-Palomares, J. C. (2008). Distance-Measure Impacts on the Calculation of Transport Service Areas Using GIS. Environment and Planning B: Planning and Design, 35(3), 480-503.
47. Handy, S. (2005). Smart growth and the transportation-land use connection: What does the research tell us?. International regional science review, 28(2), 146-167.
48. Handy, S. L., Boarnet, M. G., Ewing, R., & Killingsworth, R. E. (2002). How the built environment affects physical activity: views from urban planning. American journal of preventive medicine, 23(2), 64-73.
49. Jiang, Y., Christopher Zegras, P., & Mehndiratta, S. (2012). Walk the line: station context, corridor type and bus rapid transit walk access in Jinan, China. Journal of Transport Geography, 20(1), 1-14.
50. Knight, R. L., & Trygg, L. L. (1977). Evidence of land use impacts of rapid transit systems. Transportation, 6(3), 231-247.
51. Kuby, M., Barranda, A., & Upchurch, C. (2004). Factors influencing light-rail station boardings in the United States. Transportation Research Part A: Policy and Practice, 38(3), 223-247.
52. Leinhardt, G., & Leinhardt, S. (1980). Chapter 3: Exploratory data analysis: New tools for the analysis of empirical data. Review of research in education, 8(1), 85-157.
53. Lin, J.-J., & Shin, T.-Y. (2008). Does Transit-Oriented Development Affect Metro Ridership?: Evidence from Taipei, Taiwan. Transportation Research Record, 2063(1), 149-158.
54. Loutzenheiser, D. R. (1997). Pedestrian Access to Transit: Model of Walk Trips and Their Design and Urban Form Determinants Around Bay Area Rapid Transit Stations. Transportation Research Record, 1604(1), 40-49.
55. Mälicke, M. (2020). SciKit-GStat: A scipy flavored geostatistical analysis toolbox written in Python. Paper presented at the EGU General Assembly Conference Abstracts.
56. Matheron, G. (1963). Principles of geostatistics. Economic geology, 58(8), 1246-1266.
57. Nekola, J. C., & White, P. S. (1999). The distance decay of similarity in biogeography and ecology. Journal of biogeography, 26(4), 867-878.
58. O'Sullivan, S., & Morrall, J. (1996). Walking Distances to and from Light-Rail Transit Stations. Transportation Research Record, 1538(1), 19-26.
59. Olea, R. A. (2006). A six-step practical approach to semivariogram modeling. Stochastic Environmental Research and Risk Assessment, 20(5), 307-318.
60. Pan, H., & Zhang, M. (2008). Rail transit impacts on land use: Evidence from Shanghai, China. Transportation Research Record, 2048(1), 16-25.
61. Ripley, B. D. (1991). Statistical inference for spatial processes: Cambridge university press.
62. Ryan, S., & Frank, L. F. (2009). Pedestrian environments and transit ridership. Journal of Public Transportation, 12(1), 3.
63. Seo, K., Golub, A., & Kuby, M. (2014). Combined impacts of highways and light rail transit on residential property values: a spatial hedonic price model for Phoenix, Arizona. Journal of Transport Geography, 41, 53-62.
64. Sohn, K., & Shim, H. (2010). Factors generating boardings at metro stations in the Seoul metropolitan area. Cities, 27(5), 358-368.
65. Sung, H., & Oh, J.-T. (2011). Transit-oriented development in a high-density city: Identifying its association with transit ridership in Seoul, Korea. Cities, 28(1), 70-82.
66. Taylor, B. D., & Fink, C. N. (2003). The factors influencing transit ridership: A review and analysis of the ridership literature.
67. Taylor, P. J., & Openshaw, S. (1975). Distance decay in spatial interactions. In Concepts and techniques in modern geography.
68. Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic geography, 46(sup1), 234-240.
69. Tong, X., Wang, Y., Chan, E. H., & Zhou, Q. (2018). Correlation between transit-oriented development (TOD), land use catchment areas, and local environmental transformation. Sustainability, 10(12), 4622.
70. Tukey, J. W. (1977). Exploratory data analysis (Vol. 2, pp. 131-160).
71. Tukey, J. W. (1980). We need both exploratory and confirmatory. The American Statistician, 34(1), 23-25.
72. Vessali, K. V. (1996). Land use impacts of rapid transit: A review of the empirical literature. Berkeley Planning Journal, 11(1).
73. Wheaton, B., Muthén, B., Alwin, D. F., & Summers, G. F. (1977). Assessing Reliability and Stability in Panel Models. Sociological Methodology, 8, 84-136.
74. Zhao, F., Chow, L.-F., Li, M.-T., Ubaka, I., & Gan, A. (2003). Forecasting transit walk accessibility: Regression model alternative to buffer method. Transportation Research Record, 1835(1), 34-41.
75. Zhao, J., Deng, W., Song, Y., & Zhu, Y. (2013). What influences Metro station ridership in China? Insights from Nanjing. Cities, 35, 114-124.
76. Zimmerman, D. L. (1993). Another look at anisotropy in geostatistics. Mathematical Geology, 25(4), 453-470.