| 研究生: |
林敬樺 Lin, Ching-Hua |
|---|---|
| 論文名稱: |
以行為者基礎模型探討鐵路立體化周邊都市土地使用變遷-以員林車站為例 An Agent-Based Model to Study the Elevated Railway Impact on Urban Land Use Change: A Case Study of Yuanlin Station |
| 指導教授: |
鄭皓騰
Cheng, Hao-Teng |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 都市計劃學系 Department of Urban Planning |
| 論文出版年: | 2021 |
| 畢業學年度: | 109 |
| 語文別: | 中文 |
| 論文頁數: | 147 |
| 中文關鍵詞: | 行為者基礎模型 、都市土地使用變遷 、鐵路立體化 、中小型城市 、員林 |
| 外文關鍵詞: | Agent-based Model, Urban Land Use Change, Railway Grade Separation, Small & Medium-sized city, Yuanlin |
| 相關次數: | 點閱:350 下載:40 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
由於國內產業發展政策與資源分配不均,導致許多都會區以外中小型城市受磁吸作用,整體都市呈現人口衰退與萎縮現象,而地方政府為解決市中心人口大量外移問題,通常會動用都市計畫手段透過市中心大規模公共資源投入,來吸引新的人潮回流中心商業區。而近年我國鐵路立體化政策即屬一例,透過沿線鐵路立體化以及車站更新,來縫合市中心都市發展,並藉此來促進車站周邊都市土地產生量便與質變的結果。然而該項政策除大都會區之外,同樣包括像員林、屏東等中小型城市,該類型城市現況皆面臨著人口衰退與都市萎縮現象,故許多學者對此公共建設將帶來多少土地變遷效益帶有一定疑慮。
此外過去研究通常著重於土地呈現的結果,反而忽略個人偏好選擇以及社會不同群體間對話所產生的行為模式,且人類本身對於周遭環境認知牽涉到多重面向影響,在單一因子對於決策者本身影響即具有階層性差異,甚至對於不同決策者具不同比較上區別,落在單一土地上也因空間條件不同在區位的選擇上也具異質性,故在現實中對於因子的階層性高低,對應到不同決策者的影響程度差異,其實很難整合至同一模式中或沒辦法完整呈現,以至於對於模式解釋程度上產生一定的差距。
故本研究將探討中小型城市市中心受到立體化建設後,車站周邊土地使用強度變化情形,並嘗試建立立體化車站周邊的土地使用變遷模擬架構,並依該架構模式預測未來車站周邊土地變化趨勢,同時去釐清都市土地的變遷驅動力以及不同決策者間的互動關係以及階層性差異。
本研究選取彰化員林車站周邊500公尺範圍,以95年與107年國土利用調查作為鐵路立體化前後土地使用狀態,運用多項Logit模式與行為者基礎模型建構土地強度轉換模式,以及各因子之顯著性檢定操作成果,作為影響土地使用因素程度之參考;行為者設定上則選擇政府、開發商與居民三者作為都市土地變遷關鍵決策者,依照相鄰土地使用型態與因子變數計算網格效用與門檻值,進而模擬不同決策者評估土地效用值後選擇高低種強度使用;最終模擬結果透過整體正確率與實際土地使用比較進行檢定與校估,以利後續策略情境模擬。
研究結果顯示,立體化本身對於中小型城市車站周邊土地使用強度變化,具有一定強度增加的趨勢,然而該趨勢呈現集中在特定強度土地發展且具有明顯前後站差異,更甚至有都市穿孔問題;同時本研究所建構之土地使用變遷模擬架構,能夠有效表達都市土地變遷過程中,各種群體間與土地對話結果,整體而言模行解釋力良好;並且在本模式中,各驅動因子劃分為不同階層等級,以及對應到前後站拆分進行模擬,對於模式的整體正確率有所提高,代表因子階層權重對於決策者以及土地本身是具有一定的影響力。本研究可作為後續研究者本身、地方政府規劃者與都市決策者三方在模型上的整合,以及中小型城市立體化政策評估與制定上之參考。
This study explores the change of intensity of land use around the station after the railway grade separation construction of the center of the small and medium-sized city, and tries to construct a simulation framework, and predicts the future trend of land use around the station, while clarifying the driving forces of change and different decision makers. The interaction between the two and the hierarchical differences.
The study selected the Yuanlin Station, Changhua, Taiwan from 2006 to 2018, the land intensity change before and after the railway grade separation, combined with ABM and MNL to construct land conversion model. The results show that the railway grade separation has a certain increase for the change of land use intensity around stations in small and medium-sized cities, and this trend presents two transformation phenomena with obvious differences in the development of the front and rear stations; at the same time, the land use changes constructed by this research institute. The simulation framework can effectively express the results of dialogue between various groups of people and the land in the process of urban land changes; and in this model, the driving factors are divided into different levels, and the simulations are gradually carried out corresponding to the front and rear stations, which is correct for the overall model The rate has increased, and the weight of the representative factor class has a certain influence on decision-makers and the land itself. The follow-up can be used as a reference for the researcher, local government planners and urban decision makers on the model integration, as well as for the evaluation and compilation of the railway grade separation policy of small and medium-sized cities.
丁志堅. (2002). 屏東平原土地利用變遷分析與模式建立. (博士). 國立臺灣大學, 台北市.
王一帆. (2006). 捷運沿線土地使用變遷之影響因素分析—台北捷運板南線之實證研究. (碩士). 國立交通大學, 新竹市.
王彥傑. (2005). 建築投資業土地開發評估:層級分析法及模糊層級分析法之比較研究. 中原大學,
王思樺. (2010). 整合生態系統與行為者基礎模型之都市周邊土地利用變遷模擬. (博士). 國立臺北大學, 新北市.
伊藤智洋, & 窪田亜矢. (2019). バンコク郊外駅周辺地域における駅開業前後での商業施設の変化に関する研究. 都市計画論文集, 54(3), 1430-1437.
吳閔翰. (2019). 高速鐵路車站地區都市發展之系統動態模擬-以新竹縣竹北市為例. (碩士). 國立成功大學, 台南市.
李永展, 藍逸之, & 莊翰華. (2005). 全球經濟變遷, 發展型國家與台灣城鄉規劃之重探. JOURNAL OF GEOGRAPHICAL SCIENCE, 40, 69-97.
李家儂, & 謝翊楷. (2016). 以階層線性模式探討TOD規劃效益對土地開發之影響. 臺灣土地研究, 19(1), 1-38. doi:10.6677/JTLR.201605_19(1).0001
林孟瑤. (2011). 捷運場站周邊土地使用變遷與影響因素之研究. (碩士). 國立成功大學, 台南市.
邱創彥. (2012). 高洪災風險集水區土地使用變遷研究─以曾文、南化集水區為例. 國立成功大學,
邱瑩. (2008). 中型都市公共運輸發展政策及策略之探討─以花蓮市為例. (碩士). 國立成功大學, 台南市.
徐國城. (2007). 由國土計畫法之立法意涵探詢台灣地區城鄉空間發展方向. 土地問題研究季刊, 6(3), 98-111.
張笛箏. (2007). 捷運站區土地使用變遷之模擬分析-以台北捷運木柵線為例. (碩士). 國立交通大學, 新竹市.
張舜淵. (2019). 鐵路立體化建設對交通及都市發展之影響分析. 臺灣: 交通部運輸研究所.
張學聖, & 林孟瑤. (2011). 捷運場站周邊土地使用變遷之初探─以臺北木柵線為例. 建築與規劃學報, 12(3), 199-213. doi:10.30054/JAP.201112.0002
張曜麟. (2005). 都市土地使用變遷之研究. (博士). 國立成功大學, 台南市.
曹晉瑜. (2008). 汽車共用制度與需求推估之研究. 臺灣大學土木工程學研究所學位論文, 1-112.
莊雅仲, & 陳淑容. (2016). 中型城市發展與城鄉新連結. 文化研究(22), 123-146. doi:10.6752/JCS.201603_(22).0005
陳志仁. (2010). 臺北都會區鐵路地下化建設效益評估報告 (初版 ed.). 新北市: 交通部鐵路改建工程局.
馮正民. (2006). 台北都會區土地使用變遷模式之研究---子計畫二: 都會區重大交通建設對土地使用變遷之影響分析 (II). 交通大學交通運輸研究所
黃偉茹. (2018). 從鄉城關係思考國土計畫鄉村地區整體規劃: 借鏡歐盟. 土地問題研究季刊, 17(3), 65-76.
葉淑婷. (2010). 台灣區域重大交通建設對家戶區域間遷移與住宅區位之聯合選擇決策. 成功大學都市計劃學系學位論文, 1-61.
鄒克萬, & 張曜麟. (2004). 都市土地使用變遷空間動態模型之研究. JOURNAL OF GEOGRAPHICAL SCIENCE, 35, 35-51.
鄒克萬, 顧嘉安, & 郭幸福. (2014). 以馬可夫鍊細胞自動機模型模擬極端洪水對都市土地利用型態之影響:以台北市為例. 都市與計劃, 41(1), 43-66. doi:10.6128/CP.41.1.43
劉小蘭, 沈育生, & 蔡杰廷. (2016). 都會區綠地變遷趨勢及其驅動因素之探討-以臺北都會區為例. 都市與計劃, 43(2), 189-227. doi:10.6128/CP.43.2.189
蔡佩璇. (2009). 土地使用分區管制對都市土地使用變遷之影響. (碩士). 國立成功大學, 台南市.
鄭祈全, 吳治達, & 王素芬. (2005). 應用Markov和Logit模式監測地景變遷之研究. 臺灣林業科學, 20(1), 29-36. doi:10.7075/TJFS.200503.0029
賴世剛, & 陳志閣. (2006). 分區管制對台北都會區土地使用變遷的影響: 一電腦模擬.
簡庭妤. (2014). 以人口及產業變遷觀點探討台灣萎縮城市類型之研究. (碩士). 國立成功大學, 台南市.
顏子揚. (2006). 捷運沿線土地使用變遷模擬模式之建構與應用. (碩士). 國立交通大學, 新竹市.
羅明琪. (1995). 區域發展結構下中、小型城市功能角色之研究--以北部區域為例. (碩士). 文化大學, 台北市.
顧嘉安. (2020). 以agent-based model模擬都市發展複雜時空動態之初探. 都市與計劃, 47(2), 149-172. doi:10.6128/CP.202006_47(2).0002
Adam, B. (2006). Medium-sized cities in urban regions. European Planning Studies, 14(4), 547-555. doi:10.1080/09654310500421220
Baerwald, T. J. (1978). The Emergence of a New "Downtown". Geographical Review, 68(3), 308-318. doi:10.2307/215049
Batunova, E., & Gunko, M. (2018). Urban shrinkage: an unspoken challenge of spatial planning in Russian small and medium-sized cities. European Planning Studies, 26(8), 1580-1597. doi:10.1080/09654313.2018.1484891
Berke, P., & Kaiser, E. J. (2006). Urban land use planning: University of Illinois Press.
Bernoulli, D. (1954). Exposition of a New Theory on the Measurement of Risk. Econometrica, 22(1), 23-36. doi:10.2307/1909829
Bonabeau, E. (2002). Agent-Based Modeling: Methods And Techniques for Simulating Human Systems. Proceedings of the National Academy of Sciences of the United States of America, 99 Suppl 3, 7280-7287. doi:10.1073/pnas.082080899
Briassoulis, H. (2000). Analysis of Land Use Change: Theoretical and Modeling Approaches: Regional Research Institute, West Virginia University.
Briassoulis, H. (2019). Analysis of land use change: theoretical and modeling approaches.
Bruinsma, F., Pels, E., Priemus, H., Rietveld, P., & Van Wee, B. (2008). Railway development. Impact on urban dynamics.
Cascetta, E., & Pagliara, F. (2008). Integrated railways-based policies: the Regional Metro System (RMS) project of Naples and Campania. Transport Policy, 15(2), 81-93.
Cervero, R., & Landis, J. (1997). Twenty years of the Bay Area Rapid Transit system: Land use and development impacts. Transportation Research Part A: Policy and Practice, 31(4), 309-333.
Cheng, J., & Masser, I. (2003). Modelling urban growth patterns: a multiscale perspective. Environment and Planning A, 35(4), 679-704.
Clark, A. S. (2010). THE POLITICAL INSTITUTIONAL DETERMINANTS OF LAND-USE CHANGE AND SPRAWL
A CONCEPTUAL MODEL. Theoretical and Empirical Researches in Urban Management, 5(7 (16)), 5-18.
Cui, J., Broere, W., & Lin, D. (2021). Underground space utilisation for urban renewal. Tunnelling and Underground Space Technology, 108, 103726.
Donnelly, R., Upton, W. J., & Knudson, B. (2018). Oregon's Transportation and Land Use Model Integration Program. Journal of Transport and Land Use, 11(1), 19-30.
Edwards, W. (1954). The theory of decision making. Psychological bulletin, 51(4), 380.
Ettema, D., de Jong, K., Timmermans, H., & Bakema, A. (2007). PUMA: multi-agent modelling of urban systems. In Modelling land-use change (pp. 237-258): Springer.
Feng, Y., & Tong, X. (2018). Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules. GIScience & Remote Sensing, 55(5), 678-698.
Fragkias, M., & Seto, K. (2007). Urban Land-Use Change, Models, Uncertainty, and Policymaking in Rapidly Growing Developing World Cities. In (pp. 139-160).
Gomes, E., Banos, A., Abrantes, P., Rocha, J., & Schläpfer, M. (2020). Future land use changes in a peri-urban context: Local stakeholder views. Science of The Total Environment, 718, 137381.
González, I., D’Souza, G., & Ismailova, Z. (2018). Agent-Based Modeling: An Application to Natural Resource Management. Journal of Environmental Protection, 09, 991-1019. doi:10.4236/jep.2018.99062
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., . . . Deangelis, D. (2006). A Standard Protocol for Describing Individual-Based and Agent Based Models. Ecological Modelling, 198, 115-126. doi:10.1016/j.ecolmodel.2006.04.023
Grimm, V., Berger, U., DeAngelis, D. L., Polhill, J. G., Giske, J., & Railsback, S. F. (2010). The ODD protocol: a review and first update. Ecological Modelling, 221(23), 2760-2768.
Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., DeAngelis, D. L., . . . Groeneveld, J. (2020). The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. Journal of Artificial Societies and Social Simulation, 23(2).
Groeneveld, J., Müller, B., Buchmann, C. M., Dressler, G., Guo, C., Hase, N., . . . Schwarz, N. (2017). Theoretical foundations of human decision-making in agent-based land use models – A review. Environmental Modelling & Software, 87, 39-48.
Habitat, U., & RESILIENCY, B. (2008). Sustainable Cities. In: Nairobi.
Hasnat, M. M., Hoque, M. S., & Islam, M. R. (2016). Evaluation of Economic, Environmental and Safety Impact of At-Grade Railway Crossings on Urban City of Developing Country. Global Journal of Research In Engineering.
Hermanns, H. (2002). Markov Chains. In H. Hermanns (Ed.), Interactive Markov Chains: And the Quest for Quantified Quality (pp. 35-55). Berlin, Heidelberg: Springer Berlin Heidelberg.
Higgins, C., Ferguson, M., & Kanaroglou, P. (2014). Light Rail and Land Use Change: Rail Transit's Role in Reshaping and Revitalizing Cities. Journal of Public Transportation, 17, 93-112. doi:10.5038/2375-0901.17.2.5
Hwang, U., & Woo, M. (2020). Analysis of Inter-Relationships between Urban Decline and Urban Sprawl in City-Regions of South Korea. Sustainability, 12(4). doi:10.3390/su12041656
Jjumba, A., & Dragićević, S. (2012). High resolution urban land-use change modeling: Agent iCity approach. Applied Spatial Analysis and Policy, 5(4), 291-315.
Kim, I., Arnhold, S., Ahn, S., Le, Q. B., Kim, S. J., Park, S. J., & Koellner, T. (2019). Land use change and ecosystem services in mountainous watersheds: Predicting the consequences of environmental policies with cellular automata and hydrological modeling. Environmental Modelling & Software, 122, 103982.
Lee, R. J., & Sener, I. N. (2017). The effect of light rail transit on land use in a city without zoning. Journal of Transport and Land Use, 10(1), 541-556.
Levinson, D. M., & Krizek, K. J. (2018). Metropolitan Transport and Land Use: Planning for Place and Plexus: Routledge.
Levy, S., Martens, K., & Van Der Heijden, R. (2016). Agent-based models and self-organisation: addressing common criticisms and the role of agent-based modelling in urban planning. Town Planning Review, 87(3), 321-338.
Ligtenberg, A., Wachowicz, M., Bregt, A. K., Beulens, A., & Kettenis, D. L. (2004). A design and application of a multi-agent system for simulation of multi-actor spatial planning. Journal of Environmental Management, 72(1), 43-55.
Liu, D., Zheng, X., & Wang, H. (2020). Land-use Simulation and Decision-Support system (LandSDS): Seamlessly integrating system dynamics, agent-based model, and cellular automata. Ecological Modelling, 417, 108924.
Liu, X., Li, X., & Anthony, G.-O. Y. (2006). Multi-agent systems for simulating spatial decision behaviors and land-use dynamics. Science in China Series D: Earth Sciences, 49(11), 1184-1194. doi:10.1007/s11430-006-1184-9
Malik, A., & Abdalla, R. (2017). Agent-based modelling for urban sprawl in the region of Waterloo, Ontario, Canada. Modeling Earth Systems and Environment, 3(1), 7. doi:10.1007/s40808-017-0271-6
Micek, O., Feranec, J., & Stych, P. (2020). Land use/land cover data of the urban atlas and the cadastre of real estate: An evaluation study in the Prague Metropolitan Region. Land, 9(5), 153.
Mustafa, A., Cools, M., Saadi, I., & Teller, J. (2017). Coupling agent-based, cellular automata and logistic regression into a hybrid urban expansion model (HUEM). Land Use Policy, 69, 529-540.
Oswalt, P., & Rieniets, T. (2006). Atlas of shrinking cities: Hatje Cantz.
Pallagst, K. (2010). Viewpoint: The planning research agenda: shrinking cities — a challenge for planning cultures. The Town Planning Review, 81(5), i-vi.
Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J., & Deadman, P. (2003). Multi-agent systems for the simulation of land-use and land-cover change: a review. Annals of the association of American Geographers, 93(2), 314-337.
Parker, D. C., Sun, S., Filatova, T., Magliocca, N., Huang, Q., Brown, D. G., & Riolo, R. L. (2012). The implications of alternative developer decision-making strategies on land-use and land-cover in an agent-based land market model.
Reason, J. (2000). Human error: models and management. Bmj, 320(7237), 768-770.
Rimal, B., Zhang, L., Keshtkar, H., Wang, N., & Lin, Y. (2017). Monitoring and Modeling of Spatiotemporal Urban Expansion and Land-Use/Land-Cover Change Using Integrated Markov Chain Cellular Automata Model. ISPRS International Journal of Geo-Information, 6, 288. doi:10.3390/ijgi6090288
Saeedi, S. (2018). Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics. International Journal of Applied Earth Observation and Geoinformation, 68, 214-229.
Schwarz, N., Haase, D., & Seppelt, R. (2010). Omnipresent sprawl? A review of urban simulation models with respect to urban shrinkage. Environment and Planning B: Planning and Design, 37, 265-283. doi:10.1068/b35087
Servillo, L., Atkinson, R., & Hamdouch, A. (2017). Small and Medium-Sized Towns in Europe: Conceptual, Methodological and Policy Issues: SMALL AND MEDIUM-SIZED TOWNS IN EUROPE. Tijdschrift voor economische en sociale geografie. doi:10.1111/tesg.12252
Servillo, L. A., Atkinson, R., Russo, A. P., Sýkora, L., & Demazière, C. (2013). TOWN, small and medium sized towns in Europe–Interim report.
Sfa, F. E., Nemiche, M., & Rayd, H. (2020). A generic macroscopic cellular automata model for land use change: The case of the Drâa valley. Ecological Complexity, 43, 100851.
Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological review, 63(2), 129.
Song, L., Cao, Y., Zhou, W., Su, R., & Qiu, M. (2020). Scale effects and countermeasures of cultivated land changes based on hierarchical linear model. Environmental Monitoring and Assessment, 192(6), 346. doi:10.1007/s10661-020-08334-x
Song, X., Feng, Q., Xia, F., Li, X., & Scheffran, J. (2021). Impacts of changing urban land-use structure on sustainable city growth in China: A population-density dynamics perspective. Habitat International, 107, 102296.
Suwarno, A., van Noordwijk, M., Weikard, H.-P., & Suyamto, D. (2018). Indonesia’s forest conversion moratorium assessed with an agent-based model of Land-Use Change and Ecosystem Services (LUCES). Mitigation and adaptation strategies for global change, 23(2), 211-229.
Tavares, A. O., Monteiro, M., Barros, J. L., & Santos, P. P. (2019). Long-term land-use changes in small/medium-sized cities. Enhancing the general trends and local characteristics. European Planning Studies, 27(7), 1432-1459. doi:10.1080/09654313.2019.1588854
Torres-Reyna, O. (2012). Getting started in Logit and ordered logit regression.
Turner, B. L., Kasperson, R. E., Meyer, W. B., Dow, K. M., Golding, D., Kasperson, J. X., . . . Ratick, S. J. (1990). Two types of global environmental change: Definitional and spatial-scale issues in their human dimensions. Global Environmental Change, 1(1), 14-22.
Turner, B. L., & Meyer, W. B. (1994). Global land-use and land-cover change: an overview. Changes in land use and land cover: a global perspective, 4(3).
Veldkamp, A., & Lambin, E. F. (2001). Predicting land-use change. Agriculture, Ecosystems & Environment, 85(1), 1-6.
Verburg, P. H., Alexander, P., Evans, T., Magliocca, N. R., Malek, Z., Rounsevell, M. D. A., & van Vliet, J. (2019). Beyond land cover change: towards a new generation of land use models. Current Opinion in Environmental Sustainability, 38, 77-85.
Verburg, P. H., Schot, P. P., Dijst, M. J., & Veldkamp, A. (2004). Land use change modelling: current practice and research priorities. GeoJournal, 61(4), 309-324. doi:10.1007/s10708-004-4946-y
Waddell, P. (2011). Integrated Land Use and Transportation Planning and Modelling: Addressing Challenges in Research and Practice. Transport Reviews, 31(2), 209-229. doi:10.1080/01441647.2010.525671
Wahyudi, A. (2017). Modelling urban growth: Integrating both physical and human dimensions in developing world context.
Wegener, M. (2021). Land-use transport interaction models. Handbook of regional science, 229-246.
Wolff, M., Fol, S., Roth, H., & Cunningham-Sabot, E. (2017). Is planning needed? Shrinking cities in the French urban system. Town Planning Review, 88(1), 131-146.
Wolff, M., & Wiechmann, T. (2018). Urban growth and decline: Europe’s shrinking cities in a comparative perspective 1990–2010. European Urban and Regional Studies, 25(2), 122-139.
Won, S. H., & Hwang, C.-s. (2017). A Study on the Change of Urban Land Use According to the Change of Transportation Accessibility. Journal of Cadastre & Land InformatiX, 47(1), 127-142.
Woodcock, I., & Stone, J. (2015). Grade separations and improving intermodal transfer at railway stations in Melbourne. Paper presented at the Australasian Transport Research Forum, Sydney.
Xu, D., Guo, S., Xie, F., Liu, S., & Cao, S. (2017). The impact of rural laborer migration and household structure on household land use arrangements in mountainous areas of Sichuan Province, China. Habitat International, 70, 72-80.
Zhang, H., Zeng, Y., Bian, L., & Yu, X. (2010). Modelling urban expansion using a multi agent-based model in the city of Changsha. Journal of Geographical Sciences, 20(4), 540-556. doi:10.1007/s11442-010-0540-z
Zhao, L., & Shen, L. (2019). The impacts of rail transit on future urban land use development: A case study in Wuhan, China. Transport Policy, 81, 396-405.