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題名 以數值高程模型辨識地形之研究
作者 宋秉憲
Soong,Bing Shang
貢獻者 何瑁鎧
宋秉憲
Soong,Bing Shang
關鍵詞 地文分析
字串比對
高通濾波器
hydrologic analysis
string matching
high pass filter
日期 2004
上傳時間 17-Sep-2009 14:07:50 (UTC+8)
摘要 本研究所要討論的是如何以局部區域的數值高程模型資料辨識出所在整體地形的相對應位置。數值高程模型是以網格式的方式描述地表上連續性的起伏變化，以二維陣列儲存地表高度的資料，包含三度空間的特性。
我們從區域地形萃取出線性特徵與點特徵，分別為水系河段與地形上較明顯的凸點與凹點，以水系作為識別每一區域地形的“指紋”，對於地形變化小或河段特徵不明顯之區域尋找其特徵點，配合相關地形參數與整體地形進行比對，並對不同之特徵採用不同比對演算法。我們以物件化的方式表達水系河段與特徵點，將許多圖層的資訊整合於物件中，除了方便資料的管理，也加快了比對的效率。實驗結果顯示，應用此兩種特徵值作為辨識地形依據，可有效辨識出正確位置，也節省許多不必要的比對時間。
The main objective of this thesis is to identify a terrain using partial Digital Elevation Model (DEM) information. DEM is one of the most commonly used data representation models used in Geographical Information Systems. It is a digital model with an array of uniformly spaced elevation data in raster format. One can use DEM to analyze terrain measures including slope, aspect, and other features. In the thesis, we use hydrology analysis to extract the stream networks and use terrain parameter analysis to compute terrain features from the DEM of a small region. This information can be used as the “fingerprints” of the terrain and then compare them with the “fingerprints” in the whole data base in order to identify or to locate the correct location of the region. The KMP string matching algorithm is used to speed up the matching process.
Measurements extracted from DEM through hydrology analysis may not provide significant terrain information for the identification purpose. In this case, other mechanism such as VIP node and algorithm are used to facilitate the identification process.
We embed object oriented concepts in actual implementation. The experimental results show that our mechanism works successfully and the time used in the identification process reduced significantly.
參考文獻 [1]D. S. Mackay and L. E. Band, “Extraction and representation of nested catchment areas from digital elevation models in lake-dominated topography,” Water Resources Research Vol. 34, No. 4, pp. 897-901, 1998.
[2]Chaojun Liang and D. S. Mackay, “A general model of watershed extraction and representation using globally optimal flow paths and up-slope contributing areas,” Geographical Information Science, Vol. 14, No. 4, pp. 337-358, 2000.
[3]Xinliang Xu and Dafang Zhuang, “Automated Extraction of Drainages in China Based on Dem in GIS Environment,” Resources and Environment in the Yangtze Basin, Vol.13, No. 4, pp. 343-348, 2004.
[4]I. Kweon and T. Kanade, “Extracting Topographic Terrain Features from Elevation Maps,” Image Understanding, Vol. 59, No. 2, pp. 171-182, 1994.
[5]徐義人，應用水文學，民國92年。
[6]ESRI. “Spatial Analyst Functional Reference,” ArcGIS Desktop Help.
[7]A. N. Strahler, “Quantitative Analysis of Watershed Geomorphology,” Transactions of the American Geophysical Union, Vol. 8, No. 6, pp. 913-920, 1957.
[8]R. L. Shreve, “Statistical Law of Stream Number,” Journal of Geology, 74 pp. 17-37, 1966.
[9]M. F. Goodchild and K. K. Kemp, eds, NCGIA Core Curriculum in GIS, 1990.
[10]M. Shapiro and J. Westervelt, “An Algebra for GIS and Image Processing,” U.S. Army Construction Engineering Research Laboratory Champaign, 1992.
[11]J. Dozier, A. H. Strahler, “Ground Investigations in Support of Remote Sensing- In Manual of Remote Sensing,” American Society of Photogrammetry, Vol. l, No. 1, pp. 12-32, 1983
[12]B. K. P. Horn, “Hillshading and the Reflectance Map,” Geo-Processing, Vol. 2, pp. 65-146, 1982.
[13]I. Evans, “General Geomorphometry,” Geomorphologic Techniques, pp. 44-56, 1990.
[14]許秋玲，「數值高程模型之地形複雜度量度指標研究─以蝕溝等級為例」，國立台灣大學地理學研究所碩士論文，民國91年。
[15]D. E. Knuth, J. H. Morris, and V. R. Pratt, “Fast Pattern Matching in Strings, ” SIAM J.Comput, Vol. 6, pp. 323-350, 1977.
[16]C. Barral, J. S. Coron, and D. Naccache, “Externalized Fingerprint Matching,” Cryptology ePrint Archive, report 2004/021, 2004.
[17]D. Maltoni, D. Maio, A. K. Jain, and S. Prahakar, “Handbook of Fingerprint Recognition,” 2003.
[18]P. A. Burrough, “Principles of Geographical Information Systems for Land Resources Assessment,” Oxford University Press, 1986.
描述 碩士
國立政治大學
資訊科學學系
92753017
93
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0927530171
資料類型 thesis
dc.contributor.advisor 何瑁鎧zh_TW
dc.contributor.author (Authors) 宋秉憲zh_TW
dc.contributor.author (Authors) Soong,Bing Shangen_US
dc.creator (作者) 宋秉憲zh_TW
dc.creator (作者) Soong,Bing Shangen_US
dc.date (日期) 2004en_US
dc.date.accessioned 17-Sep-2009 14:07:50 (UTC+8)-
dc.date.available 17-Sep-2009 14:07:50 (UTC+8)-
dc.date.issued (上傳時間) 17-Sep-2009 14:07:50 (UTC+8)-
dc.identifier (Other Identifiers) G0927530171en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32720-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 92753017zh_TW
dc.description (描述) 93zh_TW
dc.description.abstract (摘要) 本研究所要討論的是如何以局部區域的數值高程模型資料辨識出所在整體地形的相對應位置。數值高程模型是以網格式的方式描述地表上連續性的起伏變化，以二維陣列儲存地表高度的資料，包含三度空間的特性。
我們從區域地形萃取出線性特徵與點特徵，分別為水系河段與地形上較明顯的凸點與凹點，以水系作為識別每一區域地形的“指紋”，對於地形變化小或河段特徵不明顯之區域尋找其特徵點，配合相關地形參數與整體地形進行比對，並對不同之特徵採用不同比對演算法。我們以物件化的方式表達水系河段與特徵點，將許多圖層的資訊整合於物件中，除了方便資料的管理，也加快了比對的效率。實驗結果顯示，應用此兩種特徵值作為辨識地形依據，可有效辨識出正確位置，也節省許多不必要的比對時間。		zh_TW
dc.description.abstract (摘要) The main objective of this thesis is to identify a terrain using partial Digital Elevation Model (DEM) information. DEM is one of the most commonly used data representation models used in Geographical Information Systems. It is a digital model with an array of uniformly spaced elevation data in raster format. One can use DEM to analyze terrain measures including slope, aspect, and other features. In the thesis, we use hydrology analysis to extract the stream networks and use terrain parameter analysis to compute terrain features from the DEM of a small region. This information can be used as the “fingerprints” of the terrain and then compare them with the “fingerprints” in the whole data base in order to identify or to locate the correct location of the region. The KMP string matching algorithm is used to speed up the matching process.
Measurements extracted from DEM through hydrology analysis may not provide significant terrain information for the identification purpose. In this case, other mechanism such as VIP node and algorithm are used to facilitate the identification process.
We embed object oriented concepts in actual implementation. The experimental results show that our mechanism works successfully and the time used in the identification process reduced significantly.		en_US
dc.description.tableofcontents 第一章 緒論........................................... 1
1.1 簡介.............................................. 1
1.2 問題描述.......................................... 2
1.3 研究動機.......................................... 4
1.4 論文章節結構...................................... 4
第二章 相關研究................. ..................... 6
第三章 地形特徵擷取................................... 8
3.1 數值地形模型...................................... 8
3.2 水文分析.......................................... 10
3.2.1流向分析......................................... 10
3.2.2窪地填補......................................... 13
3.2.3流量累積計算..................................... 14
3.2.4水系河段定義..................................... 15
3.2.5河川分段......................................... 16
3.2.6河川級序分析..................................... 17
3.3重要點特徵......................................... 18
3.4地形參數........................................... 20
3.4.1坡度............................................. 20
3.4.2坡向............................................. 22
3.4.3曲率............................................. 23
第四章 特徵值比對..................................... 25
4.1 河段比對.......................................... 25
4.2 特徵點比對........................................ 28
第五章 系統架構....................................... 33
5.1 特徵值分類........................................ 34
5.2 區域高度資料分析.................................. 35
5.2.1 最小區域面積.................................... 36
5.2.2 選取最具特徵的河段.............................. 36
5.2.3 選取最具特徵點.................................. 37
5.2.4 門檻值問題...................................... 38
5.3 資料庫建置........................................ 39
第六章 實驗........................................... 41
6.1 對地形作水文分析.................................. 41
6.2 對地形作特徵點分析................................ 44
6.3 比較辨識結果...................................... 47
6.3.1 河段比對........................................ 48
6.3.2 特徵點比對...................................... 51
第七章 結論........................................... 55
7.1 結論.............................................. 55
7.2 未來發展.......................................... 57
參考資料.............................................. 58		zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0927530171en_US
dc.subject (關鍵詞) 地文分析zh_TW
dc.subject (關鍵詞) 字串比對zh_TW
dc.subject (關鍵詞) 高通濾波器zh_TW
dc.subject (關鍵詞) hydrologic analysisen_US
dc.subject (關鍵詞) string matchingen_US
dc.subject (關鍵詞) high pass filteren_US
dc.title (題名) 以數值高程模型辨識地形之研究zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1]D. S. Mackay and L. E. Band, “Extraction and representation of nested catchment areas from digital elevation models in lake-dominated topography,” Water Resources Research Vol. 34, No. 4, pp. 897-901, 1998.zh_TW
dc.relation.reference (參考文獻) [2]Chaojun Liang and D. S. Mackay, “A general model of watershed extraction and representation using globally optimal flow paths and up-slope contributing areas,” Geographical Information Science, Vol. 14, No. 4, pp. 337-358, 2000.zh_TW
dc.relation.reference (參考文獻) [3]Xinliang Xu and Dafang Zhuang, “Automated Extraction of Drainages in China Based on Dem in GIS Environment,” Resources and Environment in the Yangtze Basin, Vol.13, No. 4, pp. 343-348, 2004.zh_TW
dc.relation.reference (參考文獻) [4]I. Kweon and T. Kanade, “Extracting Topographic Terrain Features from Elevation Maps,” Image Understanding, Vol. 59, No. 2, pp. 171-182, 1994.zh_TW
dc.relation.reference (參考文獻) [5]徐義人，應用水文學，民國92年。zh_TW
dc.relation.reference (參考文獻) [6]ESRI. “Spatial Analyst Functional Reference,” ArcGIS Desktop Help.zh_TW
dc.relation.reference (參考文獻) [7]A. N. Strahler, “Quantitative Analysis of Watershed Geomorphology,” Transactions of the American Geophysical Union, Vol. 8, No. 6, pp. 913-920, 1957.zh_TW
dc.relation.reference (參考文獻) [8]R. L. Shreve, “Statistical Law of Stream Number,” Journal of Geology, 74 pp. 17-37, 1966.zh_TW
dc.relation.reference (參考文獻) [9]M. F. Goodchild and K. K. Kemp, eds, NCGIA Core Curriculum in GIS, 1990.zh_TW
dc.relation.reference (參考文獻) [10]M. Shapiro and J. Westervelt, “An Algebra for GIS and Image Processing,” U.S. Army Construction Engineering Research Laboratory Champaign, 1992.zh_TW
dc.relation.reference (參考文獻) [11]J. Dozier, A. H. Strahler, “Ground Investigations in Support of Remote Sensing- In Manual of Remote Sensing,” American Society of Photogrammetry, Vol. l, No. 1, pp. 12-32, 1983zh_TW
dc.relation.reference (參考文獻) [12]B. K. P. Horn, “Hillshading and the Reflectance Map,” Geo-Processing, Vol. 2, pp. 65-146, 1982.zh_TW
dc.relation.reference (參考文獻) [13]I. Evans, “General Geomorphometry,” Geomorphologic Techniques, pp. 44-56, 1990.zh_TW
dc.relation.reference (參考文獻) [14]許秋玲，「數值高程模型之地形複雜度量度指標研究─以蝕溝等級為例」，國立台灣大學地理學研究所碩士論文，民國91年。zh_TW
dc.relation.reference (參考文獻) [15]D. E. Knuth, J. H. Morris, and V. R. Pratt, “Fast Pattern Matching in Strings, ” SIAM J.Comput, Vol. 6, pp. 323-350, 1977.zh_TW
dc.relation.reference (參考文獻) [16]C. Barral, J. S. Coron, and D. Naccache, “Externalized Fingerprint Matching,” Cryptology ePrint Archive, report 2004/021, 2004.zh_TW
dc.relation.reference (參考文獻) [17]D. Maltoni, D. Maio, A. K. Jain, and S. Prahakar, “Handbook of Fingerprint Recognition,” 2003.zh_TW
dc.relation.reference (參考文獻) [18]P. A. Burrough, “Principles of Geographical Information Systems for Land Resources Assessment,” Oxford University Press, 1986.zh_TW