整合形狀及光譜資訊於房屋模型之變遷偵測

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：20

、訪客IP：18.223.112.12

姓名

黃智遠(Chih-Yuan Huang) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

整合形狀及光譜資訊於房屋模型之變遷偵測
(The Integration of Shape and Spectral Information for Change Detection of Building Models)

相關論文

★ 中華二號衛星影像幾何模擬及方位重建	★ 立體航測影像直線與圓弧輪廓建物半自動之三維模型重建
★ 含房屋之中華二號衛星影像幾何模擬及校正	★ 空照立體像對中半自動化矩形人工建物重建之研究
★ 近景數化影像半自動式混凝土裂縫量測	★ 建築物幾何模塑及其於航照影像正射化之應用
★ EROS A 衛星影像幾何改正之研究	★ IKONOS衛星影像正射改正之研究
★ 時間序列之混凝土影像半自動裂縫變遷偵測	★ 由EROS A衛星立體對影像產生正射影像及數值地表模型之研究
★ 多重疊航照立體對半自動房屋模型重建	★ 結合光達資料與數位空照影像重建三維建物模型
★ 高解析力衛星影像真實正射改正及遮蔽區域補償	★ 多航帶推掃式衛星方位平差及影像正射化
★ 結合光達資料與大比例尺向量圖重建三維建物模型	★ 空載三線式掃描儀影像立體定位之研究

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

建置三維房屋模型的目的，在於提供真實物空間三維資訊與決策支援，如都市規劃更新、災害應變、建設管理等。由於房屋模型的建立仍未完全自動化，且房屋改變迅速，若進行變遷偵測，針對有變遷的房屋區域進行重新建置，將可減少資料更新所需的成本且提升效率。因此，為能有效更新，房屋模型之變遷偵測是重要的研究課題。傳統上常利用多時期影像之光譜差異進行變遷偵測，此方法僅有二維光譜資訊而缺乏三維形狀資訊。隨著光達系統成熟，使三維形狀資訊取得容易。本研究使用後期光達點雲及航照影像進行前期房屋模型之變遷偵測。
主要工作項目包含：(1)資料前處理，(2)判定原房屋模型變遷型態，(3)偵測新建與有變遷之房屋，(4)產生後期房屋區域。資料前處理，進行資料之套合，及剔除地面與植生區域之光達點雲，且計算前後期高程差異。判定原房屋模型變遷型態，結合光譜及形狀資訊進行判定；本研究設定五種變遷型態，分別為未改變、主結構改變、副結構改變、拆除、及植生遮蔽。第三步驟剔除非房屋光達點，找出新建與有變遷之房屋點雲。最後，利用未改變的區域及新建與有變遷之光達點產生後期房屋區域。
本研究成果於判定原房屋模型變遷型態部分，可達85%整體精度。產生之後期房屋區域以像元為單位之驗證顯示整體精度為96%，以區塊為單位之驗證顯示誤授率為4%及漏授率為13%。並且，為詳細了解影響研究成果的因素，本研究亦針對所有錯誤例進行分析。

摘要(英)

3D building model provides spatial information for city planning, construction, and management. Because the reconstruction of building models is still not fully automatic and the cities change rapidly, it would be more preferable to maintain a building database that firstly detect the changes followed by a reconstruction procedure. Therefore, change detection of building model is an important issue for efficiently updating. Traditionally, change detection is usually done using multi-temporal images through the spectral analyses. Those images provide two-dimensional spectral information without including shape in the third dimension. As the availability and quality of emerging LIDAR systems that make the acquisition of shape information convenient, we use new LIDAR point clouds and aerial photos to detect changes for old building model.
The proposed scheme comprises four major parts: (1) data pre-processing, (2) detecting changes on old building areas, (3) finding new or changed buildings, and (4) generation of new building regions. The first step performs the spatial registration for the different types of data. In addition, we remove LIDAR points in ground and vegetation areas. In the second step, we integrate shape and spectral information to determine the change type of building models. We set five change types in this research, namely, unchanged, main-structure changed, micro-structure changed, demolished, and vegetation occluded. In the third step, we search for new or changed buildings by removing non-building points. Finally, we use unchanged building regions and new or changed building points to derive new building regions.
The validation for determination of change type shows that the results can reach 85% overall accuracy. The results for new building regions reach 96% overall accuracy by pixel-based validation. In region-based validation, the commission and omission errors are 4% and 13%, respectively. To provide comprehensive observations, those unreliable results are scrutinized.

關鍵字(中)

★ 光達點雲
★ 影像
★ 多時期
★ 變遷偵測
★ 房屋模型

關鍵字(英)

★ Building Model
★ LIDAR
★ Image
★ Multi-temporal
★ Change Detection

論文目次

摘要 I
Abstract III
致謝 V
表目錄 XIV
第一章前言 1
1.1 研究背景 1
1.2 文獻回顧 6
1.2.1 判定變遷的方法 7
1.2.2 使用的資料 11
1.2.3 採取的基礎單元 17
1.3 變遷型態 21
1.4 研究目的 26
1.5 研究內容 28
第二章研究方法 30
2.1 前處理 30
2.2 判定原房屋模型變遷型態 44
2.3 偵測新建及有變遷房屋 48
2.4 產生後期房屋區域 51
第三章實驗成果與分析 63
3.1 測試區資料介紹 63
3.2 前處理之成果 71
3.3 判定原房屋模型變遷型態之成果 96
3.4 偵測新建及有變遷房屋之成果 104
3.5 產生後期房屋區域之成果 106
3.6 精度分析 116
3.6.1 判定原房屋模型變遷型態之精度評估 116
3.6.2 產生後期房屋區域之精度評估 121
3.7 錯誤因子分析 139
3.7.1 判定原房屋模型變遷型態之錯誤因子分析 140
3.7.2 產生後期房屋區域之錯誤因子分析 149
3.8 實驗成果摘要 166
第四章結論與建議 173
參考文獻 176

參考文獻

王冠華，2006，「多重疊航照立體對半自動房屋模型重建」，碩士論文，國立中央大學土木工程研究所。
王晉倫，蕭國鑫，游明芳，陳大科，劉進金，2005，”空載LiDAR資料應用於地形變化偵測”，內政部「辦理LIDAR測區之高精度及高解析度數值地形測繪、資料庫見至與應用推廣工作案」成果發表暨應用研討會，237-246頁。
史天元，彭淼祥，2003，空載光達數據檢查：以農委會台灣地區測試
新竹部分為例，URL：http://140.137.13.100/Conference/DERC001/pdf/A100.pdf。
李唐宇，2007，「結合多元資料重建三維房屋模型」，碩士論文，國立中央大學土木工程研究所。
李訢卉，2007，「整合房屋、道路及地形模型之高解析影像正射改正」，碩士論文，國立中央大學土木工程研究所。
周明中，2005，「紋理輔助高解析度衛星影像分析應用於偵測入侵性植物分布之研究」，碩士論文，國立中央大學土木工程研究所。
張小紅，2002，「機載激光掃描測高數據濾波及地物提取」，博士論文，武漢大學。
郭志奕，2005，「結合光達資料與大比例尺向量圖重建三維建物模型」，碩士論文，國立中央大學土木工程研究所。
湯美華，2006，「空載光達點雲及地形圖輔助生產真實正射影像之研究」，碩士論文，國立成功大學測量及空間資訊學系。
雲冠群，2008，「基於角點偵測技術應用於光達資料之建物輪廓提取」，碩士論文，國立中山大學海洋環境及工程學系研究所。
謝其亨，2006，「結合光達點雲及航照影像重建直線與圓弧輪廓建物」，碩士論文，國立中央大學土木工程研究所。
Ackermann, F.,1999. Airborne Laser Scanning - present status and future expectations, ISPRS Journal of Photogrammetry & Remote Sensing, Vol.54, pp.64-67.
Bailloeul, T., Duan, J., Prinet, V., and Serra, B., 2003. Urban Digital Map Updating From Satellite High Resolution Images Using GIS Data as A Priori Knowledge, in Proceedings of the 2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, pp. 283–287, IEEE/ISPRS, Berlin, Germany, May 2003.
Ceresola, S., Fusiello, A., Bicego, M., Belussi, A., and Murino, V., 2005. Automatic Updating of Urban Vector Maps, Lecture Notes in Computer Science, International Conference on Image Analysis and Processing, Vol. 3617, pp.1133-1139.
Chen, L. C., and Rau, J. Y., 2002, “Geometrical Building Modeling and ItsApplication to the Ortho-Rectification for Aerial Images”, Ph. D. National Central University, Taiwan.
Curran, P.J., 1988. The Semivalqogram in Remote Sensing: An Introduction, Remote Sensing of Environment, Vol. 24, pp.493-507.
Danahy, J., 1999. Visualization Data Needs in UrbanEnvironmental Planning and Design, Proceedings of the Photogrammetric Week, Karlsrnhe, pp.351-365.
Girardeau-Montaut, D., Roux, M., Marc, R., and Thibault, G., 2005. Change Detection on Points Cloud Data Acquired with a Ground Laser Scanner, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 36, part 3/W19, pp.30-35.
Golias, N.A. and Dutton, R.W., 1997. Delaunay triangulation and 3D adaptive mesh generation, Finite Element in Analysis and Design, Vol. 25, pp.331-341.
Gruen, A., and Wang, X., 1998. CC-Modeler-atopology generator for 3-D city models, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 53, pp.286-295.
Hatger, C. and Brenner, C., 2003. Extraction of Road Geometry Parameters From Laser Scanning and Existing Databases, ISPRS working group III/3 workshop `3-D reconstruction from airborne laserscanner and InSAR data'. IAPRS, Dresden, Germany.
Hazel, G.G., 2001. Object-Level Change Detection in Spectral Imagery, IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, NO. 3, pp.553-561.
Jung, F., 2004. Detecting Building Changes from Multitemporal Aerial Stereopairs, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 58, pp.187-201.
Knudsen, T. and Olsen, B.P., 2003. Automated Change Detection for Updates of Digital Map Databases, Photogrammetric Engineering and Remote Sensing, Vol. 69, No.11, pp.1289-1296.
Leica Geosystems, 2006. Leica Geosystems brochure of ALS50-II, http://gi.leica-geosystems.com/default.aspx(accessed 6, Jun, 2006).
Matikainen, L., Hyyppä, J., and Hyyppä, H., 2003. Automatic Detection of Buildings from Laser Scanner Data for Map Updating, International Archives of Photogrammetry, Remote sensing and Spatial Information Sciences, Vol. 34, part 3/W13, pp.218-224.
Matikainen, L., Hyyppä, J., and Hyyppä, H., 2004. Automatic Detection of Changes from Laser Scanner and Aerial Image Data for Updating Building Maps, International Archives of Photogrammetry, Remote sensing and Spatial Information Sciences, Vol. 35, part B2, pp.434-439.
Metternicht, G., 1999. Change detection assessment using fuzzy sets and remotely sensed data: an application of toptgraphic map revision, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 54, pp.221-233.
Mortenson, M.E., 1999. Mathematic for Computer Graphics Application, Industrial Press, New York, 2nd edition, pp. 202-204.
Murakami, H., Nakagawa, K., Hasegawa, H., and Shibata, T., 1999. Change Detection of Buildings Using an Airborne Laser Scanner, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 54, pp.148-152.
Rau, J.Y., and Chen, L.C., 2003. Robust Reconstruction of Building Models from Three-Dimensional Line Segments, Photogrammetry Engineering and Remote Sensing, Vol. 69, No. 2, pp.181-188.
Rottensteiner, F., Trinder, J., Clode, S., and Kubik, K., 2003. Building Detection Using LIDAR Data and Multi-spectral Images, in: Proc. APRS Conference on Digital Image Computing: Techniques and Applications, DICTA, Sydney, December 2003, vol. 2, pp.673-682.
Rottensteiner, F., Trinder, J., Clode, S., and Kubik, K., 2007. Building detection by fusion of airborne laser scanner data and multi-spectral images: Performance evaluation and sensitivity analysis, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 62, pp.135-149.
Rowe, N.C. and Grewe, L.L., 2001. Change Detection for Linear Features in Aerial Photographs Using Edge-Finding, IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, No. 7, pp.1608-1612.
Sampath, A., and Shan, J., 2007. Building Boundary Tracing and Regularization from Airborne Lidar Point Clouds, Photogrammetric Engineering and Remote Sensing, Vol. 73, No. 7, pp.805-812.
Siebe, E., and Buning, U., 1997. Application of Digital Photogrammetric Products for Cellnlar Radio Network Planning, Proceedings of the Photogrammetric Week, Karlsruhe, pp.159-164.
Skrlatos, D., 1999. Orthophotograph Production in Urban Areas, Photogrammtric Record, Vol. 16, No. 94, pp.643-650.
Suveg, I., and Vosselman, G., 2004. Reconstruction of 3D building models from aerial images and maps, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 58, pp.202-224.
Taillendier, F., 2005. Automatic Building Reconstruction from Cadastral Maps and Aerial Images, International Archives of Photogrammetry and Remote Sensing, Vol. 36, part3/W24, pp.105-110.
Taillendier, F., and Deriche, R., 2004. Automatic building reconstructionfrom aerial images: a generic Bayesian framework, InternationalArchives of Photogrammetry and Remote Sensing, Vol.35, part B3, pp.343-348.
Teo, T.A., Chen, L.C., Rau, J.Y., and Chen, S.J., 2007, Building Reconstruction using a Split-Shape-Merge Method, Asian Journal of Geoinformatics, Vol. 7, No. 3, pp.31-34.
Tseng, Y.H., and Wang, S., 2003. Semiautomatic building extraction based on CSG model-image fitting, Photogrammetric Engineering & Remote Sensing, Vol. 69, No. 2, pp.171-179.
Tuong, T.V., Matsuoka, M., and Yamazaki, F., 2004. LIDAR-based Change Detection of Buildings in Dense Urban Areas, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Vol. 5, pp.3413-3416.
Tuong, T.V., Matsuoka, M., and Yamazaki, F., 2004. LiDAR Signatures to Update Japanese Building Inventory Database, 25th Asian Conference on Remote Sensing.
Vicent, L., 1993, Morphological Grayscale Reconstruction in image analysis: applications and efficient algorithms, IEEE Transactions on Image Processing, Vol. 2, No. 2, pp.176-201.
Volz, S.and D. Klinec, 1999, Nexus: the Development of a Platform for Location Aware Application, Proceedings of the third Turkish-German Joint Geodetic Days, Vol. 2, Istanbul, pp.599-608.
Vögtle, T. and Steinle, E., 2004. Detection and Recognition of Changes in Building Geometry Derived from Multitemporal Laserscanning Data, International Archives of Photogrammetry and Remote Sensing, Vol. 35, part B2, pp.428-433.
Vu, T.T., Matsuoka, M., Yamazaki, F., 2004. LIDAR-based Change Detection of Buildings in Dense Urban Areas, IEEE International Geoscience and Remote Sensing Symposium, Vol. 5, pp.3413-3416.
Vu, T.T., Matsuoka, M., Yamazaki, F., 2004. LiDAR Signatures to Update Japanese Building Inventory Database, 25th Asian Conference on Remote Sensing.
Walter V., 2004. Object-based classification of remote sensing data for change detection, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 58, pp.225-238.
Walter V., 2004. Object-based Evaluation of LIDAR and Multispectral Data for Automatic Change Detection in GIS Databases, International Archives of Photogrammetry and Remote Sensing, Vol. 35, part B2, pp.723-728.
Zhou, G., W.R. Chen, J.A. Kelmelis, and D.Y. Zhang, 2005. A comprehensive study on urban true orthorestification, IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, No. 9, pp.2138-2147.

指導教授

陳良健(Liang-Chien Chen)

審核日期

2008-7-17

推文