博碩士論文 88342012 詳細資訊


姓名 邵怡誠(Yi-chen Shao)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 空載光達資料中地面點選取及房屋偵測
(Ground Point Selection and Building Detection from Airborne LiDAR Data)
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摘要(中) 本文旨在研究自空載光達資料中選取地面點與房屋偵測。在第一個主題中,先陳述空載
光達的系統、誤差來源及資料特徵,回顧並比較數種主要的過濾方法及其特性。本文在考量地形的高度、斜率及區域特徵後,提出一個創新的斜率式「爬升及滑行演算法」來選取光達資料中的地面點,該法具有區部搜尋又能涵蓋全區的優點。本文為提昇處理的效率及資料精度,建立一個在虛擬網格式初始表面模型上選取地面點的架構,並配合一個再搜尋步驟來獲取更細節的地形特徵。其中考量橋面點易遭誤判為地面的一部份,也增加了一個偵測並除橋面點的步驟。
第二個主題是自地面以上的點群中偵測房屋區塊。首先依據房屋的高度、尺寸及面積等先驗知識偵測房屋候選區,此時候選區塊主要為房屋及樹木二大類,隨後基於屋頂面具有斜率連續特性的假設,分析10個以斜率差為基礎的區塊紋理,最後採監督式及監督式分類來偵測房屋區。
本文使用二組資料測試驗證選取地面點的架構是否有效。第一組資料是取自國際航遙測學會的第三工作群第三小組,第二組資料則涵蓋了南台灣數種不同地形特徵。文中評估了選取地面點的錯誤量及參數的敏感度,也與數個知名的過濾法比較成果,同時也分析了地形特徵的保留程度。實驗成果顯示該處理架構可適用於多種不同地形特徵。為驗證房屋偵測架構的有效性,文中同時使用在台灣的都市及鄉村二個實驗區。實驗成果顯示,均調及微小斜率差機率等二個紋理特徵均可適用於房屋偵測。
摘要(英) In the dissertation, ground points are selected and building regions are detected from airborne Light Detection and Ranging (LiDAR) data. In the first part of the paper the system, error sources, and the data features of the airborne LiDAR are described after which several major filtering algorithms and their characteristics are reviewed and compared. A novel slope-based climbing-and-sliding (CAS) method is developed to select ground points from airborne LIDAR data which takes into consideration the features of height, slope and area of the region of bare earth. In the proposed method not only is a local search performed but the merits of a global treatment are preserved. A scheme is proposed to improve the efficiency and accuracy where the ground points in the initial surface model are selected based on a novel pseudo-grid. After this a back selection step is performed to retrieve detailed terrain features. Considering that bridges have tended to be misclassified as parts of the ground, an additional detection step is included to remove bridge points.
In the second part of the dissertation, building regions in the set of above-ground points are detected. Prior knowledge of such things as the height, size, and area of the buildings, is employed to first remove extraneous points or regions and to detect building candidates. Building and tree are two main dominate classes in the candidates. Based on the assumption that buildings roofs are piece-wise continuous, ten region-based textures based on directional slope difference are analyzed. At the last, an unsupervised classification is performed for the building detection.
The filtering error of the generated DEM is evaluated, as well as the test of parameter sensitivity. The processing results are quantitatively compared with several recognized counterparts in the literature. The presentation of the terrain features is also analyzed. The experimental results demonstrate that the proposed scheme can be applied to diverse terrain types. To validate the detection scheme, two data sets including urban and rural areas in Taiwan are tested. The experimental results indicate that two features of homogeneity and probability of a small slope difference preserve most information and thus are most suitable for the detection.
關鍵字(中) ★ 分類
★ 房屋偵測
★ 數值高程模型
★ 雷射掃描
★ 空載光達
關鍵字(英) ★ laser scanning
★ airboren LiDAR
★ classification
★ building detection
★ DEM
論文目次 摘要 i
ABSTRACT ii
誌謝 iv
List of Figures viii
List of Acronyms xii
1. Introduction 1
1-1 Backgrounds 1
1-2 Definition of Terms 4
1-3 Research Methods and Objectives 8
1-4 Contribution of this Study 9
1-5 Outline of the Dissertation 10
2. Related Work on Terrain Reconstruction and Building Detection from Airborne LiDAR Data 12
2-1 Airborne LiDAR Data 12
2-1-1 Airborne LiDAR System 12
2-1-2 Sources of ALS Data Error 16
2-1-3 Features of ALS Data 18
2-2 Related Works on Filtering 22
2-2-1 Surface-based Concept 26
2-2-2 Region-based Concept 27
2-2-3 Slope-based Concept 29
2-2-4 Discussion of Filtering Methods 30
2-3 Related Works on Building Detection 34
2-3-1 Methods Developed for Building Detection 34
2-3-2 Discussion of Building Detection Methods 39
3. Ground Point Selection from Airborne LiDAR Data 40
3-1 Proposed Methods for Ground Point Selection 40
3-1-1 CAS Method 40
3-1-1-1 Concept behind the CAS Method 41
3-1-1-2 CAS Process 43
3-1-2 Bridge Detection 44
3-2 Implementation of Ground Point Selection 46
3-2-1 Generation of Initial Surface Model 49
3-2-2 Noise Removal 51
3-2-3 Searching for Ground Points 53
3-2-4 Bridge Removal 57
3-2-5 Back Selection of Ground Points 60
4. Building Detection from Airborne LiDAR Data 64
4-1 Proposed Method for Building Detection 64
4-1-1 Prior Knowledge 65
4-1-2 Directional Slope Difference 65
4-1-3 Computation of Region-Based Texture 68
4-2 Implementation of Building Detection 72
4-2-1 Generation of nDSM 74
4-2-2 Pre-process to Detect Building Candidates 75
4-2-3 Building Detection 76
5. Experimental Results 79
5-1 Definition of Errors 79
5-2 Validation of Ground Point Selection 81
5-2-1 Testing with ISPRS Data 82
5-2-2 Testing with Taiwan Data 93
5-3 Validation of Building Detection 100
5-3-1 Pre-processing Results for Building Candidates 102
5-3-2 Detection Results by the Classification of Region Textures 106
5-4 Summary 112
5-4-1 Advantages and Limitations of Ground Point Selection 113
5-4-2 Advantages and Limitations of Building Detection 115
6. Conclusion and Future Work 117
6.1 Conclusion 117
6.2 Future work 119
References 121
Appendix A: ISPRS Data Sets 130
A-1 Characteristics of the ISPRS filter test data 130
A-2 Shaded relief maps of the ISPRS test sites 131
A-3 Shaded relief maps of the DSM and DEM of test Samples 135
Appendix B: Taiwan Data Sets and the Generated DEM 140
B-1 Characteristics of Taiwan Data Sets 140
B-2 Shaded relief maps of the Taiwan test sites 141
B-3 Shaded relief maps of the DSM and DEM of test Samples 143
Appendix C: Classification Results of the Test Data 147
C-1 Characteristics of the test data for building detection 147
C-2 Classification results and the error analysis for test Area A 149
C-3 Classification results and the error analysis for test Area B 152
Curriculum Vitae 155
參考文獻 [1] Ackermann, F., “Airborne laser scanning — present status and future expectations”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 64–67, 1999.
[2] Airborne laser mapping (ALM), “Airborne laser mapping: a reference on an emerging technology”, URL: http://Airbornelasermapping.com/ALMID.html. (last date accessed: 2006/11/27).
[3] Burtch, R., “Lidar principles and applications”, IMAGIN Conference: Geography on the Move, Travers, MI, 13 p., April 2002.
[4] Hu, Y., “Automated extraction of digital terrain models, roads and buildings using airborne lidar data”, Ph. D. Dissertation, University of Calgary, Calgary, UCGE Report No. 20187, 206 p., 2003.
[5] Baltsavias, E. P., “A comparison between photogrammetry and laser scanning”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 83–94, 1999a.
[6] Huising, E. J. and L. M. Gomes Pereira, “Errors and accuracy estimates of laser data acquired by various laser scanning systems for topographic application”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 53, No. 5, pp. 245–261, 1998.
[7] Flood, M., “LIDAR activities and research priorities in the commercial sector”, International Archives of Photogrammetry and Remote Sensing, XXXIV, WG IV/3, Annapolis, Maryland, pp. 3–7, 2001.
[8] Sithole, G. and G. Vosselman, “Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 59, p. 85–101, 2004.
[9] Haala, N. and M. Hahn, “Data fusion for the detection and reconstruction of buildings”, Automatic Extraction of Man-Made Objects from Aerial and Space Image, Birkhauser Press, pp. 211–220, 1995.
[10] Henricsson, O., “The role of color attributes and similarity grouping in 3-d building reconstruction”, Computer Vision and Image Understanding, Vol. 72, pp. 163–184, 1998.
[11] Paparoditis, Cord, M., M. Jordan, and J. Cocquerez, “Building detection and reconstruction from mid- and high-resolution aerial imagery”, Computer Vision and Image Understanding, Vol. 72, pp. 122–142, 1998.
[12] Fujii, K. and T. Arikawa, “Urban object reconstruction using airborne laser elevation image and aerial image”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 40, pp.2234–2240, 2002.
[13] Rottensteiner, F. and C. Briese, “A new method for building extraction in urban areas from high-resolution lidar data”, International Archives of Photogrammetry and Remote Sensing, Vol. 34, Graz, 7 p., unpaginated CD-ROM, 2002.
[14] Haugerud, R. A. and D. J. Harding, “Some algorithms for virtual deforestation (VDF) of LIDAR topographic survey data”, International Archives of the Photogrammetry and Remote Sensing, Vol. 34 (Pt. 3/W4), pp. 211–218, 2001.
[15] Sithole, G. and G. Vosselman, “Comparison of filtering algorithms”, Workshop: 3−D reconstruction from airborne laserscanner and InSAR data, 29 p., 2003, URL: http://www.geo.tudelft.nl/frs/isprs/filtertest/. (last date accessed: 2003/10/ 15)
[16] Lindenberger, J., “Methods and results of high precision airborne laser profiling”, Proceeding of the 43rd Photogrammetric Week at Stuttgart University, Stuttgart, Germany, pp. 83–92, September 1991.
[17] Sithole, G., “Segmentation and classification of airborne laser scanner data”, Ph.D. Thesis. Technical University of Delft, The Netherlands. Publications on Geodesy, 59. Publication of Netherlands Geodetic Commission. ISBN 90 6132 292 8, 184 p., 2005.
[18] Baltsavias, E. P., “Airborne laser scanning: existing systems and firms and other resources”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 164–198, 1999b.
[19] Wehr, A. and U. Lohr, “Airborne laser scanning - an introduction and overview”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 68–82, 1999.
[20] Baltsavias, E. P., “Airborne laser scanning - relations and formulas”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54: pp. 199–214, 1999c.
[21] Axelsson, P., “DEM generation from laser scanner data using adaptive TIN models”, International Archives of the Photogrammetry and Remote Sensing, Vol. XXXIII (Pt. B4/1), pp. 110–117, 2000.
[22] Hu, Y. and C.-V. Tao, “Hierarchical recovery of digital terrain models from single and multiple return LiDAR data”, Photogrammetry Engineering & Remote Sensing, Vol. 71, No. 4, pp. 425–433, April 2005.
[23] Schenk, T., “Modeling and Recovering Systematic Errors in Airborne Laser Scanners”, OEEPE Workshop on Airborne Laserscanning and Interferometric SAR for Detailed Digital Elevation Models, Stockholm, pp. 40–48, 2001.
[24] Mohamed, A., “Navigating the ground from air: active monitoring with GPS/INS geo-referenced lidar”, ION Conference, Anaheim, pp. 593–601, January 2003.
[25] Katzenbeisser, R., “About the calibration of lidar sensors”, ISPRS Workshop on 3-D Reconstruction from Airborne Laserscanner and InSAR Data. Dresden, Germany, 6 p., unpaginated CD-ROM, October 2003.
[26] Kornus, W. and A. Ruiz, “Strip adjustment of LIDAR data”, ISPRS Workshop on 3-D Reconstruction from Airborne Laserscanner and InSAR Data. Dresden, Germany, 4 p., unpaginated CD-ROM, Oct. 2003.
[27] Liu, J. K., “On the systematic error handling of airborne laser scanning: from system calibration to data Adjustment”, PhD dissertation, Department of Civil Engineering, National Chiao Tung University, Taiwan, 115 p, 2005.
[28] Optech, 2002. ALTM Airborne Laser Terrain Mappers, Optech Inc., URL: http://www.optech.on.ca/. (last date accessed: 2003/5/ 12)
[29] Airborne LIDAR The Technology, URL: http://www.ncgia.ucsb.edu/ncrst/ meetings/20030415MSN/presentations/Scarpace1.ppt. (last date accessed: 2003/05/12)
[30] Song, J. H., S. H. Han, K. Yu, and Y. Kim, “Assessing the possibility of land-cover classification using lidar intensity data”, International Archives of Photogrammetry and Remote Sensing, Graz, vol. 34, 4 p., September 2002.
[31] Schiewe J., “Region-based information extraction from laser scanning data and optical imagery”, Proceedings of OEEPE workshop on airborne laserscanning and interferometric SAR for detailed digital elevation models 1–3 March 2001, Stockholm, Sweden, OEEPE Publication no. 40, 7 p. , unpaginated CD-ROM, 2001.
[32] Kraus, K. and N. Pfeifer, “Determination of terrain models in wooded areas with airborne laser scanner data”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 53, No. 4, pp. 193–203, 1998.
[33] Pfeifer, N., P. Stadler, and C. Briese, “Derivation of digital terrain models in the SCOP++ environment”, Proc. OEEPE workshop on Airborne Laserscanning and Interferometric SAR for Detailed Digital Elevation Models, Stockholm, Sweden, OEEPE Publication no. 40, 13 p., unpaginated CD–ROM, March 2001.
[34] Elmqvist, M., “Ground estimation of laser radar data using active shape models”, Proc. OEEPE workshop on Airborne Laserscanning and Interferometric SAR for Detailed Digital Elevation Models, OEEPE Publication no. 40, 8 p., unpaginated CD-ROM, March 2001.
[35] Sohn, G. and I. Dowman, “Terrain surface reconstruction by the use of tetrahedron model with the MDL criterion”, International Archives of the Photogrammetry and Remote Sensing, Vol. 34, Part 3A, pp. 336–344, 2002.
[36] Krzystek, P., “Filtering of laser scanning data in forest areas using finite elements”, Workshop: 3-D reconstruction from airborne laser scanner and InSAR data, 6 p., unpaginated CD–ROM, 2003.
[37] Kilian, J., N. Haala, and M. Englich, “Capture and evaluation of airborne laser scanner data”, International Archives of Photogrammetry and Remote Sensing, Vol. 31, Part B3, Vienna, Austria, pp. 383–388, 1996.
[38] Brovelli, M. A., M. Cannata, and U. M. Longoni, “Managing and processing LIDAR data within GRASS”, Proc. GRASS Users Conference, Trento, Italy, University of Trento, Italy, 29 p., unpaginated CD-ROM, September 2002.
[39] Wack, R. and A. Wimmer, “Digital terrain models from airborne laser scanner data — a grid based approach”, International Archives of the Photogrammetry and Remote Sensing, Vol. 34, Part 3B, pp. 293–296, 2002.
[40] Petzold, B., P. Reiss, and W. Stössel, “Laser scanning - surveying and mapping agencies are using a new technique for the derivation of digital terrain models”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 95–104, 1999.
[41] Morgan, M. and K. Tempfli, “Automatic building extraction from airborne laser scanning data”, International Archives of the Photogrammetry and Remote Sensing, Vol. 33, Part B3, pp. 616–622, 2000.
[42] Zhang, K. and S.-C. Chen, “A progressive morphological filter for removing non-ground measurements from airborne LIDAR data”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, No. 4, pp. 871–882, April 2003.
[43] Lohmann P., A. Koch, and M. Schaeffer, “Approaches to the filtering of laser scanner data”, Proceedings of XIXth Congress of the International Society of Photogrammetry and Remote Sensing, Amsterdam, The Netherlands, pp. 534–547, July 2000.
[44] Masaharua, H. and K. Ohtsubo, “A filtering method on airborne laser scanner data for complex Terrain”, ISPRS Commission III Symposium Photogrammetric Computer Vision, Graz, Austria, 5p., unpaginated CD-ROM, September 2002.
[45] Qi, C., P. Gong, D. Baldocchi, and G. Xie, “Filtering Airborne Laser Scanning Data with Morphological Methods”, Photogrammetric Engineering & Remote Sensing, Vol. 73, No. 2, pp. 175–185, 2007..
[46] Vosselman, G., “Slope based filtering of laser altimetry data”, International Archives of the Photogrammetry and Remote Sensing, Vol. 33, Part B3, pp. 935– 942, 2000.
[47] Sithole, G., “Filtering of laser altimetry data using a slope adaptive filter”, International Archives of the Photogrammetry and Remote Sensing, Vol. 34, Part B3/W4, pp. 203–210, 2001.
[48] Roggero, M., “Airborne laser scanning: clustering in raw data”, International Archives of the Photogrammetry and Remote Sensing, Vol. 34, Part B3/W4, pp. 227–232, 2001.
[49] Shan, J. and A. Sampath, “Urban DEM generation from raw LiDAR data: a labeling algorithm and its performance”, Photogrammetry Engineering & Remote Sensing, Vol. 71, No. 2, pp. 217–226, February 2005.
[50] Meng. X, “A slope- and elevation-based filter to remove non-ground measurements from airborne LIDAR data”, ISPRS WG III/3, III/4, V/3 Workshop "Laser scanning 2005", the Netherlands, 23 p., September 2005.
[51] Sithole, G. and G. Vosselman, “Filtering of airborne laser scanner data based on segmented point clouds”, ISPRS WG III/3, III/4, V/3 Workshop "Laser scanning 2005", the Netherlands, pp. 66–71, September 2005.
[52] Peng, M.-H., “DTM generation and error assessment for airborne LIDAR data”, Ph.D. Thesis Dissertation, Department of Civil Engineering, National Chiao Tung University, Taiwan, 117p., 2005.
[53] Haala, N. and C. Brenner, “Extraction of buildings and trees in urban environments”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp.130–137, 1999.
[54] Lu, Y.-H., J.-C. Trinder, and K. Kubik, ”Automatic building detection using the dempster-shafer algorithm”, Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 4, pp. 395–403, 2006..
[55] Brunn A., and U. Weidner, “Extracting buildings from digital surface models”, International Archives of Photogrammetry and Remote Sensing, Vol. 32, Stuttgart, 8p., 1997.
[56] Alharthy, A., and Bethel, J., “Heuristic filtering and 3D feature extraction from LIDAR data” , IAPRS, Vol. 33, pp. 29-35, Graz, Austria, 2002.
[57] Hofmann, A. D., H. Mass, and A. Streilein, “Knowledge-based building detection based on laser scanner data and topographic map information”, International Archives of the Photogrammetry and Remote Sensing, Vol. 34, Part 3A+B, pp.163–169, 2002.
[58] Matikainen, L., J. Hyyppä, and H. Hyyppä, “Automatic Detection of Buildings from Laser Scanner data for Map Updating”, Workshop '3-D reconstruction from airborne laserscanner and InSAR data, Dresden, Germany, pp. 218-224, October 2003.
[59] Schiewe J., “Integration of multi-sensor data for landscape modeling using a region based approach”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol.57, pp.371–379, 2003.
[60] Ma, R., “DEM Generation and building detection from Lidar data”, Photogrammetry Engineering & Remote Sensing, Vol.71, No.7, pp.847-854, 2005.
[61] Tarsha-Kurdi, F., T. Landes, P. Grussenmeyer, and E. Smigiel, ”New approach for automatic detection of buildings in airborne laser scanner data using first echo only”, ISPRS Symposium of Commission III, Photogrammetric Computer Vision and Image Analysis, 6p., unpaginated-CDROM, 2006.
[62] Sithole, G. and G. Vosselman, “Bridge detection in aorne laser scanner data”, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 61, p. 33–46, 2006.
[63] Cho, W., Y.-S. Jwa., H.-J. Chang, and S.-H. Lee, “Pseudo-grid based building extraction using airborne LIDAR data”, XXth ISPRS Congress, "Geo-Imagery Bridging Continents", Istanbul, Turkey, 4pp. URL: http://www.isprs.org/istanbul2004/comm3/comm3.html, July 2004. (last date accessed 2006/11/27).
[64] Dougherty, Edward R., An introduction to morphological image processing, SPIE Optical Engineering Press, Center for Imaging Science Rochester Institute of Technology, 1992.
[65] Haralick, R. M., K. Shanmugan, and I. Dinstei, “Texture features for image classification”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-8, pp.610-621, 1973.
[66] Unser, M., “Sum and difference histograms for texture classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-8. No. 1, pp. 118–125, 1986.
[67] Oude Elberink, S. and H.-G. Mass, 2000, “The use of anisotropic height texture measures for the segmentation of airborne laser scanner data”, International Archives of Photogrammetry and Remote Sensing, Vol. 33, Part B3, pp. 678–684.
[68] Matikainen, L., J. Hyyppä, and H. Kaartinen, “Automatic detection of changes from laser scanner and aerial image data for updating building maps”, Proceedings of the XXth International ISPRS Congress, Istanbul, Turkey, pp. 434-439, July 2004.
[69] Lillesand, T. M. and R. W. Kiefer, Remote sensing and image interpretation, John Wiley & Sons, Inc. New York, 2000.
[70] ISPRS III Working Group 3, ISPRS Test on extracting DEMs from point clouds: “A comparison of existing automatic filters”, URL: http://www.geo.tudelft.nl/frs/isprs/filtertest/ (last date accessed: 2004/03/30)
[71] Flood, M., “Product definitions and guidelines for use in specifying Lidar deliverables”, Photogrammetry Engineering & Remote Sensing, Vol.68, No. 12, highlight article, 7 p., 2002. URL: http://www.asprs.org/asprs/publications/ pe&rs/2002journal/december/highlight.html (last date accessed: 2004/04/21)
指導教授 陳良健(Liang-chien Chen) 審核日期 2007-7-21
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