Automated Extraction of Digital Terrain Models, Roads and Buildings Using Airborne Lidar Data

223 Pages·2004·17.2 MB·English

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

ª YONG HU 2003

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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

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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.
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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.
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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

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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

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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
6.2 RECOMMENDATIONS FOR FUTURE WORK……………………..………152

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REFERENCES…………………………………………..……………………………..154

APPENDIX A: AIRBORNE LIDAR TECHNOLOGY………………………….…….167

A.1 AIRBORNE LIDAR MAPPING.…………………………………………..167

A.2 LIDAR MAPPING APPLICATIONS..…………………………………….174

APPENDIX B: BASIC ALGORITHMS AND CONCEPTS…………………….…….176
B.1 IMAGE PROCESSING ALGORITHMS…………………..…………..…..176

B.2 GEOMETRY AND NUMERICAL ALGORITHMS………………………187

B.3 QUALITY MEASURES…………..………………………………………. 190

APPENDIX C: LIDAR EXPERT AND ITS APPLICATIONS.……………………….191
C.1 LIDAR EXPERT……..……………………………………..………….…..191

C.2 3-D CITY MODELS………………………………………………………..192
C.3 PIPELINE SAFETY MANAGEMENT……………………………………195

C.4 AIRFIELD SAFETY MANAGEMENT……………………..……………. 200
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LIST OF TABLES

Table Title Page

3.1 Information about five lidar datasets.………………………………….. 62
3.2 Information related with DTM generation.……………………………. 62
3.3 Geoid heights relative to WGS84 ellipsoid (downtown Toronto)…….. 73
3.4 Geoid heights relative to WGS84 ellipsoid (Whitecourt)……………... 77
3.5 Overall accuracies for generated DTMs……………………………….. 79
3.6 Accuracies at building and tree surroundings…………………………. 79

4.1 Information of the lidar dataset (Downtown Toronto).………………... 88
4.2 Number of road pixels during road classification………………..……. 97
4.3 Information about the grid road models ..……………………………... 99
4.4 System performance evaluation……………………………………….. 107

5.1 System performance evaluation……………………………………….. 140
5.2 Statistical data of building extraction results………………………….. 141

A.1 Major characteristics of typical lidar systems……..…………………... 168
A.2 Reflectivity of infrared laser…………………………………………... 172

C.1 Risk levels of four risk factors………………………………………… 204
C.2 Pair-wise comparison of the relative importance of factors…………… 205
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