研究生: |
林庭嘉 Lin, Ting-Jia |
---|---|
論文名稱: |
不同尺度空間插值法進行人口分佈推估的比較研究 A Comparison of Methods for Spatial Interpolation across Different Spatial Scales |
指導教授: |
張國楨
Chang, Kuo-Chen |
口試委員: | 李萬凱 陳俊愷 |
口試日期: | 2021/07/18 |
學位類別: |
碩士 Master |
系所名稱: |
地理學系 Department of Geography |
論文出版年: | 2021 |
畢業學年度: | 109 |
語文別: | 中文 |
論文頁數: | 38 |
中文關鍵詞: | 最小統計區 、地理資訊系統 、容積率 、建蔽率 、地理加權回歸 |
英文關鍵詞: | Basic Statistical Area, GIS, Floor Area Ratio, Building Coverage Rate, Geographically Weighted Regression |
研究方法: | 實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202101140 |
論文種類: | 學術論文 |
相關次數: | 點閱:118 下載:0 |
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 |
近年來,雲端運算及物聯網應用技術的進步對於社會經濟、醫療公衛、自然科學等領域都具有非常重要的幫助。隨著政府開放資料(open data)之推廣應用,各類型的資料透過加值與開放應用,創造出更多跨領域的應用成果。然而,伴隨豐富且多元的應用對於數據的解析度要求更高,常常會遇到小尺度數據缺少亦或者沒有更細緻的調查數據等問題。因此透過現有的數據經空間內插方式,進而得到更細緻的資料應用。
本研究以戶籍人口分佈資料作為驗證對象在不同尺度下進行空間內插推估分析,搭配與戶籍人口關聯之建蔽率、容積率、樓地板面積等作為推估的輔助資料以此建立人口推估的模型,進而得到更細緻的建築物層級之戶籍人口分佈。研究目標:建立不同尺度下對於人口分佈的推估模式,並找出與戶籍人口關聯之變數,並提供小尺度的單元在戶籍人口上的推估模式。
研究成果顯示:變數中樓地板面積、容積率對於戶籍人口有顯著的相關性,運用地理加權回歸對最小統計單元之戶籍人口推估出建築物層級的戶籍人口分佈,並經過交叉驗證在建築物尺度下推戶籍人口數其推估相對誤差的準確度平均值為3.554766(人)。
In recent years, advances in cloud computing and Internet of Things (IoT) applications have been of great importance to the fields of socio-economic, medical, and public health, and natural science. With the promotion of the application of open data, various types of data can be used to create more cross-disciplinary applications through value-added and open applications.
However, with the abundant and multi-dimensional applications requiring higher resolution of data, there are often problems such as the lack of small-scale data or the absence of more detailed survey data. Therefore penetrates the existing data after the spatial interpolation way, then obtains the most detailed information for application.
In this study, the spatial interpolation of the household register population distribution data is used as the validation object to conduct the spatial interpolation, analysis at different scales, and the building coverage rate, floor area ratio, and floor area associated with the household register population are used as the auxiliary data for the estimation to establish the population estimation model, and to obtain a more detailed distribution of the household register population at the building level. The aim of the study is to develop a model for estimating population distribution at different scales, to identify variables associated with the household register population, and to provide a model for estimating the household register population for small-scale units.
Research results show that: a variable in the floor area, floor area ratio for the population of a significant correlation, using geographically weighted regression to smallest statistical unit census register population to estimate the building level of census register population distribution, and scale through cross certification in building census register population estimate its average relative error of accuracy is 3.554 (people).
英文文獻
Comber, A., Proctor, C., & Anthony, S. (2008). The creation of a national agricultural land use dataset: Combining pycnophylactic interpolation with dasymetric mapping techniques. Transactions in GIS, 12(6), 775–791. https://doi.org/10.1111/j.1467-9671.2008.01130.x.
David J Briggs, Susan Collins , Paul Elliott , Paul Fischer , Simon kingham , Erik Lebret , Karel Pryl , Hans Van Reeuwijk , Kirsty , smallbone & Andre Van Der Veen(1997). Mapping urban air pollution using GIS: a regression-based approach. International Journal of Geographical Information Science, 11:7,699-718, DOI: 10.1080/136588197242158
Daniele Da Re ,Marius Gilbert,Celia Chaiban,Pierre Bourguignon,Weerapong Thanapongtharm,Timothy P. Robinson,Sophie O. Vanwambeke(2020). Downscaling livestock census data using multivariate predictive models: Sensitivity to modifiable areal unit problem.PLoS ONE. 2020;15(1):1–16. https://doi.org/10.1371/journal.pone.0221070
Goovaerts, P. (2000). Geostatistical approaches for ncorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228(1–2), 113–129. https://doi.org/10.1016/S0022-1694(00)00144-X.
Goodchild, M. F., Anselin, L., Deichmann, U. (1993) A framework for the areal interpolation of socioeconomic data, Environment and Planning A, 25(3): 383-397.
Joseph, J., Sharif, H. O., Sunil, T., & Alamgir, H. (2013). Application of validation data for assessing spatial interpolation methods for 8-h ozone or other sparsely monitored constituents. Environmental Pollution, 178, 411–418. https://doi.org/10.1016/j.envpol.2013.03.035.
Liao, Y., Li, D., & Zhang, N. (2018). Comparison of interpolation models for estimating heavy metals in soils under various spatial characteristics and sampling methods.
Transactions in GIS, 22(2), 409–434. https://doi.org/10.1111/tgis.12319.
Mennis, J. (2003). Generating surface models of population using dasymetric mapping.The Professional Geographer, 55(1), 31–42. https://doi.org/10.1111/0033-0124.10042.
Openshaw, S. (1984). The modifiable areal unit problem. Concepts and Techniques
in Modern Geography, England, Norwich.
Rigol, J. P., Jarvis, C. H., & Stuart, N. (2001). Artificial neural networks as a tool for spatial interpolation. International Journal of Geographical Information Science, 15(4),323–343. https://doi.org/10.1080/13658810110038951.
Shi, W. Z., & Tian, Y. (2006). A hybrid interpolation method for the refinement of a regular grid digital elevation model. International Journal of Geographical Information Science, 20(1), 53–67. https://doi.org/10.1080/13658810500286943.
Wen Zeng, &, Alexis Comber(2020).Using household counts as ancillary information for areal interpolation of population: Comparing formal and informal, online data sources.Computers, Environment and Urban Systems,
https://doi.org/10.1016/j.compenvurbsys.2019.101440
中文文獻
雷祖強、葉惠中、楊玫萍、葉吉雄(2012)。路口犯罪監視器設置策略之研究:以台中市水湳派出所管轄範圍為例。都市與計劃, 39(3)。
林美君、蘇明道(2013)。以統計區分類系統為基礎研討人口重分配之效能。中國地理學會會刊,(51),53-66。
溫在弘、劉擇昌、林民浩(2010)。犯罪地圖繪製與熱區分析方法及其應用:以 1998-2007 年台北市住宅竊盜犯罪為例。地理研究,52,43-64。
劉擇昌、游柏輝(2011)。GlS於住宅竊盜犯罪熱區空間分析應用之研究─以台北市大安區為例。犯罪學期刊,14(1),99-140。
林美君、蘇明道 (2012) 統計區分類系統對社經資料在隱私保護與維持空間分布型態之效能分析。國土資訊系統通訊, 84: 23-33.
王庫(2013)。地理權重回歸在土壤 pH 空间预测中的應用。湖南農業大學學报(自然科学版),39(1),1-8。
李萬凱、林建元、孫志鴻、榮峻德。工商及戶口普查資料空間分派模式之建立及運用。建築學報,59,127-144。http://dx.doi.org/10.6377/JA.200703.0127
葉芳秀(2018)。人口特徵對房價影響之分析。國立政治大學財務管理學系研究所碩士論文。
謝心怡(2007)。多層多類別之人口地理分布模式。國立台灣大學生物環境系統工程學系碩士論文。
林美軍(2011)。多層多類分區密度之空間人口重分布模式。國立台灣大學生物環境系統工程學系博士論文。
趙崇軒(2017)。台北市都市發展與少子化所引起的學童便化趨勢之空間差異分析。國立台灣師範大學地理學系研究所碩士論文。
陳彥儒(2020)。應用手機信令軌跡資料推估通勤廊道之時空地震災害風險。國立台灣師範大學地理學系研究所碩士論文。
中華民國都市計劃學會 (1997)。都市計畫作業手冊研究報告。
台灣地理資訊學會 (2008 )。國土資訊系統統計區建置計畫整體規劃暨試作,內政部統計處。