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«Department of Geomatics Engineering Automated Extraction of Digital Terrain Models, Roads and Buildings Using Airborne Lidar Data (URL: ...»

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UCGE Reports

Number 20187

Department of Geomatics Engineering

Automated Extraction of Digital Terrain Models,

Roads and Buildings Using Airborne Lidar Data

(URL: http://www.geomatics.ucalgary.ca/links/GradTheses.html)

by

Yong Hu

October 2003

THE UNIVERSITY OF CALGARY

Automated Extraction of Digital Terrain Models,

Roads and Buildings Using Airborne Lidar Data

by

YONG HU

A DISSERTATION

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF GEOMATICS ENGINEERING

CALGARY, ALBERTA

OCTOBER, 2003 © YONG HU 2003 · ii ·

UNIVERSITY OF CALGARY

FACULTY OF GRADUATE STUDIES

The undersigned certify that they have read, and recommend to the Faculty of Graduate Studies for acceptance, a thesis entitled “Automated Extraction of Digital Terrain Models, Roads and Buildings Using Airborne Lidar Data” submitted by Yong Hu in partial fulfillment of the requirements for the degree of doctor of philosophy.

______________________________________________________

Supervisor, Dr. Vincent Tao, Geomatics Engineering _______________________________________________________

Co-supervisor, Dr. Michael Collins, Geomatics Engineering ________________________________________________________

Dr. Naser El-Sheimy, Geomatics Engineering ________________________________________________________

Dr. Isabelle Couloigner, Geomatics Engineering ________________________________________________________

Dr. Nigel Waters, Geography ________________________________________________________

Dr. Ahmed Mohamed, Alberta Research Council Inc.

October 3, 2003 Date · iii ·

ABSTRACT

Airborne lidar has become a commercially viable remote sensing platform, and can provide accurate elevation data about both topographic surfaces and non-terrain objects.

Its capability of mapping topography and 3-D models of civil objects is uncommon to other remote sensing technologies. This dissertation presents a collection of algorithms developed for automatically extracting useful information from lidar data exclusively.

The algorithms focus on automated extraction of DTMs, 3-D roads and buildings utilizing single- or multi-return lidar range and intensity data. The hierarchical terrain recovery algorithm can intelligently discriminate between terrain and non-terrain lidar points by adaptive and robust filtering. It processes the range data bottom up and top down to estimate high quality DTMs using the hierarchical strategy. Road ribbons are detected by classifying lidar intensity and height data. The 3-D grid road networks are reconstructed using a sequential Hough transformation, and are verified using road ribbons and lidar-derived DTMs. The attributes of road segments including width, length and slope are computed. Building models are created with a high level of accuracy. The building boundaries are detected by segmenting lidar height data. A sequential linking technique is proposed to reconstruct building boundaries to regular polygons, which are then rectified to be of cartographical quality. Then prismatic models are created for flat roof buildings, and polyhedral models are created for non-flat roof buildings by the incremental selective refining and vertical wall rectification procedures. Many attributes of these building models are derived from the lidar data. These algorithms have been tested using many lidar datasets of varying terrain type, coverage type and point density.

The results show that in most areas the lidar-derived DTMs retain most terrain details and remove non-terrain objects reliably; the road ribbons and grid road networks are sketched well in built-up areas; and the extracted building footprints have high positioning accuracy equivalent to ground-truth data surveyed in field. A toolkit, called Lidar Expert, has been developed to bundle these algorithms and to offer the capability of performing fast information extraction from lidar data.

· iv · ACKNOWLEDGEMENTS

First and foremost, I must thank my parents for their great support and understanding to pursue a goal lasting over thirty years. The fourteen years of studying at same schools and the same university with my little brother are always priceless. I would like to thank God for life itself. All that I have is due to his grace, and I would give glory to him.

I would thank all those who have helped me in my work here at University of Calgary and York University: Drs. Vincent Tao, Yang Gao, Rod Blais, Michael Collins, and Ms.

Lu-Anne Markland. I have learnt a great deal in my time here at University of Calgary, but nothing more important than the values and principles they taught me. Special thanks go to my former advisor, Mr. Zhifeng Tang, for his great help.

I also would thank my fellow graduate students and colleagues in this department and in earth science department, York University, who have made my lives colorful. They are Mr. Zhizhao Liu, Kongzhe Chen, Drs. Longmei Li, Quanke Wang, Chaowei Yang, and Mr. Zhe Liu, Jihong Zhang, Jiun Han Keong, Xiangqian Liao, Junjie Liu, Chaochao Wang, Wentao Zhang, Changlin Ma, Ming Zhong, Chris Wang, Jeff Xu, and Ivan Wang.





I would like to thank my classmates in the past fourteen years: Mr. Chenyin Zhong, Ms.

Yanfen Le, Drs. Yunfeng Jian, Hao Zhao, Chuanzhong Xu, Xiangru Yuan, Wenlong Zheng, and Wanshou Jiang, who have helped me a great deal till today. There are many other people who have helped and encouraged me in my work and life whom I have not mentioned. I want to thank them all for all they have done for me.

Support from Talbert Abrams Grand Award (ASPRS, 2003), The University of Calgary Silver Anniversary Graduate Fellowships (U of C, 2001~2003), Robert E. Altenhofen Memorial Scholarship Award (ASPRS, 2002), Graduate Research Scholarships (U of C, 2000~2001), and Research Assistantships from University of Calgary (1999~2001) and York University (2002~2003) are gratefully appreciated.

·v·

TABLE OF CONTENTS

APPROVAL PAGE.…………………………………………………………………….. iii ABSTRACT...…………………………………………...………………………………. iv ACKNOWLEDGEMENTS..…………………………………………………………...… v TABLE OF CONTENTS..………………………………………………………………..vi LIST OF TABLES...………………………………………………………………………x LIST OF FIGURES...……………………………………………………………………. xi LIST OF ACRONYMS.………………….…………………………………………….. xiv LIST OF SYMBOLS.…………………………………………………………………... xvi CHAPTER ONE: INTRODUCTION……………………………………………………..1

1.1 BACKGROUND...……………………………………………………………….. 1

1.2 AIRBORNE LIDAR TECHNOLOGY.…………………………………………...3

1.3 ISSUES IN AUTOMATED INFORMATION EXTRACTION...……………….. 5

1.4 RESEARCH OBJECTIVES AND METHODOLOGY..……..………………….. 8 1.4.1 Research Objectives…………………………………………….…………8 1.4.2 The Methodology...……..…………………………………………………9

1.5 CONTRIBUTIONS…………………...………………………………………… 10

1.6 OUTLINE OF THE THESIS…………………………………………………….11 CHAPTER TWO: LITERATURE REVIEW…..…………..…………………………… 13

2.1 RELATED TECHNIQUES…………………………..…………………………. 15

2.2 ALGORITHMS FOR DTM GENERATION…………………………………… 17

2.3 ALGORITHMS FOR ROAD EXTRACTION……………………….………….25

2.4 ALGORITHMS FOR BUILDING EXTRACTION………………….………….29

2.5 SUMMARY……………………………………………………………….…….. 36 CHAPTER THREE: DIGITAL TERRAIN MODEL GENERATION…………………. 37

3.1 INTRODUCTION………………………………………………………………. 37 · vi ·

3.2 DTM GENERATION FOR SINGLE-RETURN RANGE DATA………….…...40 3.2.1 Overview of the Proposed Methodology………………………………... 40 3.2.2 Workflow for DTM Generation…………………………………………. 41

3.3 LIDAR IMAGE PROCESSING…………………………………………………42 3.3.1 Create Grid Images……………………………………………………… 42 3.3.2 Process Lidar Images……………………………………………………. 42 3.3.3 Determine the Largest Window Size……………………………………. 43

3.4 HIERARCHICAL TERRAIN RECOVERY ALGORITHM…………………… 43 3.4.1 Generation of Image Pyramids………………………………………….. 43 3.4.2 Hierarchical Recovery of Terrain Surfaces………………………………45 3.4.3 Refinement of DTMs……………………………………………………. 53

3.5 DTM GENERATION FOR BI-RETURN LIDAR DATA………………….….. 55 3.5.1 Identification of Road Points……………………………………………. 55 3.5.2 Derivation of Vegetation Height Models……………………………….. 57 3.5.3 The Modified Methodology.…………………………………………….. 60

3.6 EXPERIMENTS AND EVALUATION.………………………………………..63 3.6.1 DTM Generation Results…….………………………………………….. 63 3.6.2 Quality Assessment.…………………………………………………….. 71

3.7 SUMMARY…………………………..………………………………………….84 CHAPTER FOUR: ROAD EXTRACTION…………….…………………………….…85

4.1 INTRODUCTION…...……..…………………………………………………… 85

4.2 DATA ACQUISITION AND PROCESSING…………………………………...87 4.2.1 Study Area…………………………………………………………….… 87 4.2.2 Lidar Data Pre-processing………………………………………………..88 4.2.3 Generation of the DTM, VSM and DNM……………………………….. 90

4.3 DETECTION OF ROAD RIBBONS …………………………………………... 90 4.3.1 Road Ribbons Detection Using Intensity Data………………………….. 90 4.3.2 Road Ribbons Detection Using Height Data……………………………. 93 4.3.3 Road Ribbons Detection Integrating Intensity and Height Data..…….… 94 4.3.4 Rough Road Network Generation………………………………………..97 · vii ·

4.4 RECONSTRUCTION OF GRID ROAD NETWORKS……………………..…. 98 4.4.1 Sequential Hough Transformation……………………..………………... 98 4.4.2 Procedure for Reconstructing Grid Roads………………………………. 99 4.4.3 3-D Reconstruction Results……………………………………………. 103

4.5 RESULTS EVALUATION……………………………..………….………..… 105

4.6 SUMMARY…………………………………….………….………….……….. 109 CHAPTER FIVE: BUILDING EXTRACTION……………………………….……… 110

5.1 INTRODUCTION…...……..………………………………………………….. 110

5.2 METHODOLOGY OVERVIEW……………………………………………… 114

5.3 BUILDING BOUNDARY DETECTION……………………………………... 116 5.3.1 Detection of Object Boundaries…………………….………….……….116 5.3.2 Classification of Building and Vegetation Objects………….………….117

5.4 RECTANGULAR BOUNDARY RECONSTRUCTION……………………... 118

5.5 ENHANCED HOUGH TRANSFORMATION……………………………….. 120 5.5.1 Grouping Line Points………………………………………………….. 121 5.5.2 Merging Lines……………………………….………….………………122 5.5.3 Splitting Edge Segments.……………………………………………….123

5.6 POLYGONAL BOUNDARY RECONSTRUCTION………………………… 123

5.7 POLYGONAL BOUNDARY RECTIFICATION…………………………….. 126

5.8 BUILDING RECONSTRUCTION……………………………….…………… 129 5.8.1 Roof Hypotheses Tests………………………………………………… 129 5.8.2 Prismatic and Polyhedral Models Generation…………………………..134

5.9 TEST RESULTS AND EVALUATION……………………..………………... 137 5.9.1 Building Extraction Results……………………………….…………… 137 5.9.2 Performance Evaluation………………………………………………...141

5.10 SUMMARY…………………..……………………………………………. 147 CHAPTER SIX: CONCLUSIONS AND RECOMMENDATIONS…………….….… 150

6.1 CONCLUSIONS …...……..……………………………………………………150



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