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題名 利用最小一乘法在地籍坐標轉換資料偵錯之研究
Outlier Detection in Cadastral Coordinate Transformation Using Least Absolute Deviation作者 林怡君
Lin, Yi Chun貢獻者 林老生
Lin, Lao Sheng
林怡君
Lin, Yi Chun關鍵詞 地籍坐標轉換
最小一乘法
最小二乘法
資料偵錯
Cadastral Coordinate Transformation
Least Absolute Deviation(LAD)
Least Squares(LS)
Outlier Detection日期 2012 上傳時間 1-四月-2014 11:19:58 (UTC+8) 摘要 臺灣現行之地籍坐標系統,依不同的建立時期與地球原子,主要有TWD67(Taiwan Datum 1967)和TWD97(Taiwan Datum 1997)兩種。為了地籍資料管理、操作及運用之便利,常需執行坐標轉換。根據不同需求,有各種不同的坐標轉換方法,通常使用最小二乘法求解坐標轉換參數。然而,最小二乘法計算方便,但僅適用於資料含有偶然誤差的情形。因此,不論使用何種坐標轉換方法,資料本身是否已完全剔除錯誤,對轉換後之坐標精度有一定程度的影響。最小一乘法為平差方法之一,其平差結果不易受粗差的影響,故穩健性強。由於最小一乘法之目標函數中,含有絕對值不可直接微分求解的問題,所以限制其實用性;然而,該問題隨著軟體的開發而克服,故目前在參數估計及資料偵錯上皆有良好的成效。因此,本研究之目的為依據最小一乘法之特性,使用此平差方法於地籍坐標轉換中,測試其資料偵錯能力及穩健性。此外,並比較以最小一乘法與常用的最小二乘法坐標轉換後成果之差異、優缺點及適用情形。依據研究目的,為檢測地籍坐標資料的品質,以確保地籍坐標轉換的精度,本研究先模擬三個不同大小之實驗區及含不同大小與數量粗差之參考點與檢核點坐標資料,以測試最小一乘法與最小二乘法的穩健性及資料偵錯能力。另一方面,亦使用真實地籍資料,來探討此兩種方法於真實地籍坐標轉換時之資料偵錯能力與適用性。而坐標轉換方法則分別採用四參數及六參數兩種,以比較不同坐標轉換方法與平差方式之成果。根據本研究成果顯示,最小一乘法於地籍坐標轉換時,具有不易受粗差影響平差結果之穩健性,以及可由點位殘差中判斷出粗差之位置及大小的偵錯能力。另一方面,最小二乘法平差結果易受粗差的影響,不具有抗差性及偵錯能力。然而,在坐標資料不含有粗差的情形中,最小二乘法之成果則較最小一乘法為佳或相當。因此,為提升地籍坐標轉換之精度,建議未來在執行地籍坐標轉換時,先以最小一乘法執行資料偵錯,待錯誤坐標剔除後,再以最小二乘法求取坐標轉換參數。
There are two coordinate systems with different geodetic datum in Taiwan region, i.e., TWD67 (Taiwan Datum 1967) and TWD97 (Taiwan Datum 1997). In order to maintain the consistency of cadastral coordinates, it is necessary to transform one coordinate system to another. However, no matter what transformation method was used, the accuracy of the result is highly depended on the data quality. Since the uncertainty about whether outliers exist or not, so the outlier detection of data becomes an important work before coordinate transformation. The LAD(Least Absolute Deviation) method was affected by nearly very little or none from outliers. Thus, this method has been successfully used for outlier measurements detection in other fields. Therefore, LAD method was used to detect outliers in cadastral coordinate transformation in this study. This method provides an examination to ensure the quality of cadastral coordinates before converting one coordinate system to another. So, the accuracy of coordinate transformation can be increased. Then, the coordinate transformation results of LAD method and LS (Least Squares) method in the aspects of outlier detection ability and the accuracy of coordinate transformation were compared.On one hand, three varied sizes of simulating test areas, which contains different magnitude of outliers, at numbers of reference points and check points were placed, for checking the robustness and outlier detection ability in LAD and LS methods. On the other hand, data of real test areas were also used. Then, results from different coordinate transformation and adjustment methods were compared and analyzed, by using 4 and 6 parameter coordinate transformation respectively.The test results show that LAD method is more robust than LS method, and outliers can be detected easily from the residuals of reference points. While LS method is affected by outliers and the outlier detection ability is weaker than LS method. However, if the data contain none outliers, the coordinate transformation results by using LS method is better than LAD method. Therefore, it is suggested to using LAD method firstly. Then, after deleting all the outliers, one can use LS method to calculate coordinate transformation parameters.參考文獻 一、中文參考文獻王文峰,2006,「基於LINGO的最小一乘線性回歸的參數估計」,『貴州財經學院學報』,6:106-108。王奕鈞,2006,「神經網路應用於地籍坐標轉換之研究」,國立政治大學地政學系碩士論文:臺北。王福昌、胡順田、張艷芳,2007,「最小一乘回歸係數估計及其MATLAB實現」,『防災科技學院學報』,9(4)。方述誠,1993,「線性優化及擴展—理論與演算法」,『數學傳播』,17(1)。方述誠、S. 普森普拉,1994,『線性優化及擴展—理論與演算法』,北京:科學出版社。肖建華、楊緯隆、李軍,2006,「基於Matlab的最小一乘回歸的線性規劃實現」,『五邑大學學報(自然科學版)』,20(1)。何維信,2009,『測量學』第六版,臺北:宏泰出版社。李哲仁,2001,「完全最小二乘法平差於坐標轉換之研究」,國立成功大學測量工程學系碩士論文:台南。吳孟旭,2008,「應於VRS-RTK技術於圖根點重測時坐標轉換之探討-以彰化縣市地區為例」,國立中興大學土木工程學系測量資訊組碩士學位論文:台中。吳亞翰,2009,「藉由附有面積限制條件的坐標轉換以提升圖解區土地複丈效率之研究」,國立中興大學土木工程學系碩士學位論文:台中。林老生,2012,「e-GPS水準測量精度研究」,『臺灣土地研究』,15(2):35-58。岳東杰、黃騰,1999,「GPS高程的抗差擬合推估」,『河海大學學報』,27(6):90-93。梁勇、郭祿光、樊功瑜,1990,「穩健估計在測量平差中的應用」,『同濟大學學報』,18(4):467-474。章棟恩、馬玉蘭、徐美萍、李雙,2008,『MATLAB高等數學實驗』,北京:電子工業出版社。陳世平,2003,「數值法辦理圖解地籍圖數化區之土地複丈作業研究--以農地重測區為例」,逢甲大學土地管理學系碩士在職專班碩士論文:台中。張裕民,1993,「以穩健推估法進行測量平差之研究」,四海學報,8:33-50。許皓寧,2003,「臺北市地籍資料TWD67與TWD97坐標轉換之比較研究」,國立中興大學土木工程學系碩士論文:台中。馮守平、石澤、鄧瑾,2008,「一元線性回歸模型中參數估計的幾種方法比較」,『統計與決策』,24:152-153。楊鳳芸、張旭東,2005,「採用抗差推估法剔除GPS高程數據粗差」,『測繪通報』,10:9-11。臺北市政府地政處測量大隊,2004,「臺北市TWD67地籍坐標系統轉換為TWD97坐標系統作業總報告」。溫豐文,2012,『土地法』修訂版,臺北:三民書局。鄭彩堂,2002,「以限制條件及附加參數法轉助圖解區土地複丈之研究」,國立中興大學土木工程學系碩士論文:台中。顧樂民,2011,「曲線擬合的最小一乘法」,『同濟大學學報(自然科學版),39(9)。二、外文參考文獻Bektas, S. and Y. Sisman, 2010, “The comparison of L1 and L2-norm minimization methods”, International Journal of the Physical Sciences, 5 (11): 1721-1727.Bidabad, B. (2005, January). L1 Norm Based Data Analysis and Related Methods (1632-1989), on the World Wide Web: http://www.bidabad.com/doc/l1-article1.pdf. Calitz, M. F. and H. Rüther, 1996, “Least Absolute Deviation (LAD) image matching”, ISPRS Journal of Photogrammetry & Remote Sensing, 51: 223-229.Chen, K., Z. Ying, H. Zhang and L. Zhao, 2006, “Analysis of least absolute deviation”, Oxford Journals, Life Sciences & Mathematics & Physical Sciences, Biometrika, 95 (1): 107-122.Dasgupta, M. and SK Mishra, (2007, November). Least absolute deviation estimation of linear econometric models: A literature review, Munich Personal RePEc Archive, 7 (1781), on the World Wide Web: http://mpra.ub.uni-muenchen.de/1781/.Fang, S. C. and S. Puthenpura, 1993, “Linear Optimization and Extensions - Theory and Algorithms”, Prentice Hall, Inc. , Federal Geographic Data Committee (FGDC), 1998, “Geospatial Positioning Accuracy Standards Part 3. National Standard for Special Data Accuracy”, Washington, D.C: 1-28.Fu, H., M. K. Ng, M. Nikolova and J. L. Barlow, 2004, “Efficient Minimization Methods of Mixed L2-L1 and L1-L1 Norms for Image Restoration”, Siam Journal On Scientific Computing, Report CMLA No 2004-14.Ghilani, C. D. and P. R. Wolf, 2010, “Adjustment Computations: Spatial Data Analysis”, 5th Edition, John Wiley & Sons, Inc.Khodabandeh, A. and A. R. Amiri-Simkooei, 2011, “Recursive algorithm for l1 norm estimation in linear models”, Journal of Surveying Engineering, 137 (1): 1-8.Kuzmanovi´c, I., K. Sabo, R. Scitovski, and I. Vazler, 2009, “The best least absolute deviation linear regression: properties and two efficient methods”, Aplimat - Journal of Applied Mathematics, 2 (3): 227-240.Li, Y. and G. R. Arce, 2004, “A Maximum Likelihood Approach to Least Absolute Deviation Regression”, EURASIP Journal on Applied Signal Processing, Hindawi Publishing Corporation, 12: 1762–1769.Neuman, E. (2013, March). Tutorial 6: Linear Programming with MATLAB, on the World Wide Web: http://www.math.siu.edu/matlab/tutorial6.pdf.Nobakhti, A., Wang H. and Chai T., 2009, “Algorithm for very fast computation of Least Absolute Value regression”, American Control Conference, Hyatt Regency Riverfront, St. Louis, MO, USA, June 10-12.Pfeil, W. A., 2006, “Statistical teaching aids”, Project Number: JP-0501. Sisman, Y., 2011, “Parameter estimation and outlier detection with different estimation methods”, Scientific Research and Essays, 6 (7): 1620-1626.Soliman, S. A., S. Persaud, K. EI-Nagar and M. E. EI-Hawary, 1997, “Application of least absolute value parameter estimation based on linear programming to shorbterm load forecasting”, International Journal of Electrical Power & Energy Systems, 19 (3): 209-216.Wolf, P. R. and B. A. Dewitt, 2004,”Elements of Photogrammetry: with Application in GIS”, 3rd edition, McGraw-Hill.Yetkin, M. and C. Inal, 2011, “L1 Norm Minimization in GPS Networks”, Survey Review, 43, 323: 523-532.三、網頁參考文獻國土資訊系統─土地基本資料庫全球資訊網,取用日期2012年12月,http://law.moj.gov.tw/LawClass/LawAll.aspx?PCode=D0060053。全國法規資料庫(地籍測量實施規則),取用日期2012年12月,http://law.moj.gov.tw/LawClass/LawAll.aspx?PCode=D0060053。內政部地政司衛星測量中心,取用日期2013年6月,http://www.gps.moi.gov.tw/SSCenter/Introduce/InfoPage.aspx。國家圖書館臺灣鄉土書目資料庫,取用日期2013年8月,http://localdoc.ncl.edu.tw/tmld/browse_map.jsp?map=2001。Math Works. Retrieved May 17, 2013 on the World Wide Web: http://www.mathworks.com/. 描述 碩士
國立政治大學
地政研究所
100257029
101資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100257029 資料類型 thesis dc.contributor.advisor 林老生 zh_TW dc.contributor.advisor Lin, Lao Sheng en_US dc.contributor.author (作者) 林怡君 zh_TW dc.contributor.author (作者) Lin, Yi Chun en_US dc.creator (作者) 林怡君 zh_TW dc.creator (作者) Lin, Yi Chun en_US dc.date (日期) 2012 en_US dc.date.accessioned 1-四月-2014 11:19:58 (UTC+8) - dc.date.available 1-四月-2014 11:19:58 (UTC+8) - dc.date.issued (上傳時間) 1-四月-2014 11:19:58 (UTC+8) - dc.identifier (其他 識別碼) G0100257029 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/65095 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 地政研究所 zh_TW dc.description (描述) 100257029 zh_TW dc.description (描述) 101 zh_TW dc.description.abstract (摘要) 臺灣現行之地籍坐標系統,依不同的建立時期與地球原子,主要有TWD67(Taiwan Datum 1967)和TWD97(Taiwan Datum 1997)兩種。為了地籍資料管理、操作及運用之便利,常需執行坐標轉換。根據不同需求,有各種不同的坐標轉換方法,通常使用最小二乘法求解坐標轉換參數。然而,最小二乘法計算方便,但僅適用於資料含有偶然誤差的情形。因此,不論使用何種坐標轉換方法,資料本身是否已完全剔除錯誤,對轉換後之坐標精度有一定程度的影響。最小一乘法為平差方法之一,其平差結果不易受粗差的影響,故穩健性強。由於最小一乘法之目標函數中,含有絕對值不可直接微分求解的問題,所以限制其實用性;然而,該問題隨著軟體的開發而克服,故目前在參數估計及資料偵錯上皆有良好的成效。因此,本研究之目的為依據最小一乘法之特性,使用此平差方法於地籍坐標轉換中,測試其資料偵錯能力及穩健性。此外,並比較以最小一乘法與常用的最小二乘法坐標轉換後成果之差異、優缺點及適用情形。依據研究目的,為檢測地籍坐標資料的品質,以確保地籍坐標轉換的精度,本研究先模擬三個不同大小之實驗區及含不同大小與數量粗差之參考點與檢核點坐標資料,以測試最小一乘法與最小二乘法的穩健性及資料偵錯能力。另一方面,亦使用真實地籍資料,來探討此兩種方法於真實地籍坐標轉換時之資料偵錯能力與適用性。而坐標轉換方法則分別採用四參數及六參數兩種,以比較不同坐標轉換方法與平差方式之成果。根據本研究成果顯示,最小一乘法於地籍坐標轉換時,具有不易受粗差影響平差結果之穩健性,以及可由點位殘差中判斷出粗差之位置及大小的偵錯能力。另一方面,最小二乘法平差結果易受粗差的影響,不具有抗差性及偵錯能力。然而,在坐標資料不含有粗差的情形中,最小二乘法之成果則較最小一乘法為佳或相當。因此,為提升地籍坐標轉換之精度,建議未來在執行地籍坐標轉換時,先以最小一乘法執行資料偵錯,待錯誤坐標剔除後,再以最小二乘法求取坐標轉換參數。 zh_TW dc.description.abstract (摘要) There are two coordinate systems with different geodetic datum in Taiwan region, i.e., TWD67 (Taiwan Datum 1967) and TWD97 (Taiwan Datum 1997). In order to maintain the consistency of cadastral coordinates, it is necessary to transform one coordinate system to another. However, no matter what transformation method was used, the accuracy of the result is highly depended on the data quality. Since the uncertainty about whether outliers exist or not, so the outlier detection of data becomes an important work before coordinate transformation. The LAD(Least Absolute Deviation) method was affected by nearly very little or none from outliers. Thus, this method has been successfully used for outlier measurements detection in other fields. Therefore, LAD method was used to detect outliers in cadastral coordinate transformation in this study. This method provides an examination to ensure the quality of cadastral coordinates before converting one coordinate system to another. So, the accuracy of coordinate transformation can be increased. Then, the coordinate transformation results of LAD method and LS (Least Squares) method in the aspects of outlier detection ability and the accuracy of coordinate transformation were compared.On one hand, three varied sizes of simulating test areas, which contains different magnitude of outliers, at numbers of reference points and check points were placed, for checking the robustness and outlier detection ability in LAD and LS methods. On the other hand, data of real test areas were also used. Then, results from different coordinate transformation and adjustment methods were compared and analyzed, by using 4 and 6 parameter coordinate transformation respectively.The test results show that LAD method is more robust than LS method, and outliers can be detected easily from the residuals of reference points. While LS method is affected by outliers and the outlier detection ability is weaker than LS method. However, if the data contain none outliers, the coordinate transformation results by using LS method is better than LAD method. Therefore, it is suggested to using LAD method firstly. Then, after deleting all the outliers, one can use LS method to calculate coordinate transformation parameters. en_US dc.description.tableofcontents 摘要 IAbstract III目錄 V圖目錄 VII表目錄 IX第一章 緒論 1第一節 前言 1第二節 研究動機 3第三節 研究目的 5第四節 研究流程 6第五節 論文架構 7第二章 文獻回顧與理論基礎 9第一節 應用最小二乘法於地籍坐標轉換 9一、相關文獻 9二、應用最小二乘法於地籍坐標轉換 11三、四參數轉換 12四、六參數轉換 14第二節 最小一乘法 16一、源起 16二、理論基礎 17三、最小一乘法與最小二乘法之特性比較 17四、應用最小一乘法於測量之相關文獻 18第三節 線性規劃基本原理 20一、標準型線性規劃 20二、單形法基本原理 21三、解決LAD目標函數含有絕對值的方法 23四、以MATLAB之linprog函數解算線性規劃問題 23第四節 利用最小一乘法求解地籍坐標轉換參數 28一、將四參數及六參數坐標轉換觀測方程式轉換為矩陣形式 28二、將四、六參數坐標轉換化為線性規劃標準型 29三、解算成果 31第三章 實驗方法與資料處理 33第一節 實驗資料 33一、模擬資料 33二、真實資料 39第二節 實驗方法 42一、模擬資料 43二、真實資料 44三、精度檢核 45第三節 資料處理 47一、參考點與檢核點數量比例原則 47三、參考點與檢核點之選點原則 51第四章 實驗成果與分析 55第一節 模擬資料實驗成果(1)-參考點與檢核點的TWD67坐標存在粗差的狀況 …………………………………………………………………..55一、單一參考點之TWD67坐標中加入不同大小之粗差 55二、數個參考點之TWD67坐標加入不同粗差數量 81三、參考點和檢核點之TWD67坐標中皆加入粗差 101第二節 模擬資料實驗成果(2)-參考點的TWD97坐標存在粗差的狀況 107第三節 模擬資料實驗成果(3)-參考點的TWD67坐標與TWD97坐標同時存在粗差的狀況 113第四節 真實資料實驗成果 119一、花蓮縣主權段實驗區 119二、臺中市實驗區 127第五章 結論與建議 133第一節 結論 133一、最小一乘法於地籍坐標轉換時之穩健性與資料偵錯能力 133二、應用最小一乘法於真實資料之地籍坐標轉換 134三、應用最小一乘法與最小二乘法於地籍坐標轉換成果比較 135第二節 建議 136參考文獻 139一、中文參考文獻 139二、外文參考文獻 140三、網頁參考文獻 142 zh_TW dc.format.extent 5330619 bytes - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0100257029 en_US dc.subject (關鍵詞) 地籍坐標轉換 zh_TW dc.subject (關鍵詞) 最小一乘法 zh_TW dc.subject (關鍵詞) 最小二乘法 zh_TW dc.subject (關鍵詞) 資料偵錯 zh_TW dc.subject (關鍵詞) Cadastral Coordinate Transformation en_US dc.subject (關鍵詞) Least Absolute Deviation(LAD) en_US dc.subject (關鍵詞) Least Squares(LS) en_US dc.subject (關鍵詞) Outlier Detection en_US dc.title (題名) 利用最小一乘法在地籍坐標轉換資料偵錯之研究 zh_TW dc.title (題名) Outlier Detection in Cadastral Coordinate Transformation Using Least Absolute Deviation en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 一、中文參考文獻王文峰,2006,「基於LINGO的最小一乘線性回歸的參數估計」,『貴州財經學院學報』,6:106-108。王奕鈞,2006,「神經網路應用於地籍坐標轉換之研究」,國立政治大學地政學系碩士論文:臺北。王福昌、胡順田、張艷芳,2007,「最小一乘回歸係數估計及其MATLAB實現」,『防災科技學院學報』,9(4)。方述誠,1993,「線性優化及擴展—理論與演算法」,『數學傳播』,17(1)。方述誠、S. 普森普拉,1994,『線性優化及擴展—理論與演算法』,北京:科學出版社。肖建華、楊緯隆、李軍,2006,「基於Matlab的最小一乘回歸的線性規劃實現」,『五邑大學學報(自然科學版)』,20(1)。何維信,2009,『測量學』第六版,臺北:宏泰出版社。李哲仁,2001,「完全最小二乘法平差於坐標轉換之研究」,國立成功大學測量工程學系碩士論文:台南。吳孟旭,2008,「應於VRS-RTK技術於圖根點重測時坐標轉換之探討-以彰化縣市地區為例」,國立中興大學土木工程學系測量資訊組碩士學位論文:台中。吳亞翰,2009,「藉由附有面積限制條件的坐標轉換以提升圖解區土地複丈效率之研究」,國立中興大學土木工程學系碩士學位論文:台中。林老生,2012,「e-GPS水準測量精度研究」,『臺灣土地研究』,15(2):35-58。岳東杰、黃騰,1999,「GPS高程的抗差擬合推估」,『河海大學學報』,27(6):90-93。梁勇、郭祿光、樊功瑜,1990,「穩健估計在測量平差中的應用」,『同濟大學學報』,18(4):467-474。章棟恩、馬玉蘭、徐美萍、李雙,2008,『MATLAB高等數學實驗』,北京:電子工業出版社。陳世平,2003,「數值法辦理圖解地籍圖數化區之土地複丈作業研究--以農地重測區為例」,逢甲大學土地管理學系碩士在職專班碩士論文:台中。張裕民,1993,「以穩健推估法進行測量平差之研究」,四海學報,8:33-50。許皓寧,2003,「臺北市地籍資料TWD67與TWD97坐標轉換之比較研究」,國立中興大學土木工程學系碩士論文:台中。馮守平、石澤、鄧瑾,2008,「一元線性回歸模型中參數估計的幾種方法比較」,『統計與決策』,24:152-153。楊鳳芸、張旭東,2005,「採用抗差推估法剔除GPS高程數據粗差」,『測繪通報』,10:9-11。臺北市政府地政處測量大隊,2004,「臺北市TWD67地籍坐標系統轉換為TWD97坐標系統作業總報告」。溫豐文,2012,『土地法』修訂版,臺北:三民書局。鄭彩堂,2002,「以限制條件及附加參數法轉助圖解區土地複丈之研究」,國立中興大學土木工程學系碩士論文:台中。顧樂民,2011,「曲線擬合的最小一乘法」,『同濟大學學報(自然科學版),39(9)。二、外文參考文獻Bektas, S. and Y. 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