||Exploration of Laser Scanning for Exposed Fluvial Gravel Bed Surfaces
||Department of Geomatics
gravel bed roughness
Understanding of the structure of gravel bed surface is vital for the gravel bed roughness and sediment entrainment. A lot of works have been done on the acquisition of gravel bed surface to investigate the gravel bed roughness. Most of these studies only focus on the small sampling area due to the limitation of the instruments that were used to acquire the elevation information of gravel bed surface. Recently, there has been considerable interest in measuring the gravel bed surface over a large area. And, airborne laser scanning (ALS) has become the preferred technology of rapidly acquiring the spatial data for large areas. We use ALS to measure a rive section and investigate the gravel bed roughness derived from ALS data in this dissertation.
Due to large footprint sizes of ALS, the gravel bed surface would be smoother in ALS data, which causes a biased roughness. Moreover, the scaling characteristics of the gravel bed roughness on the change of measurement scale are still lack of empirical investigation. As part of this issue, we use terrestrial laser scanning (TLS) to capture high resolution data at field sites. Chapter 2 presents a two-stage mean-based algorithm for TLS data to generate the digital surface model (DSM). In Chapter 3, we use the regularization method to establish the scaling relations of the gravel bed roughness between TLS-derived DSM and ALS data. In Chapter 4, we explore the gravel bed roughness of ALS data of a river section, and show the flow direction comparison results between the direction of maximum continuity exhibited in the two dimensional variogram surfaces of ALS data and the flow direction derived from a hydrodynamic model at three flow rates.
List of Tables xi
List of Figures xiii
Chapter 1 Introduction 1
1.1 Background and objectives 1
1.2 Contribution 6
1.3 Organization 6
Chapter 2 Mesoscale Terrestrial Laser Scanning of Fluvial Gravel Surfaces 9
2.1 Introduction 10
2.2 Material and Methods 12
2.2.1 Study sites 12
2.2.2 Terrestrial laser scanning 13
2.2.3 Multiple scan strategy 14
2.2.4 DSM generation 16
2.2.5 Manual surface profile collection 23
2.3 Results and Discussion 23
2.3.1 TLS-derived DSM 23
2.3.2 Assessment of TLS-derived DSM 27
2.4 Conclusion 31
2.5 Acknowledgement 32
Chapter 3 Multiscale Geostatistical Estimation of Gravel Bed Roughness From Terrestrial and Airborne Laser Scanning 33
3.1 Introduction 34
3.2 Data 37
3.3 Method 41
3.4 Results and Discussion 45
3.4.1 2-D variogram surfaces 45
3.4.2 Regularization 48
3.5 Conclusion 53
3.6 Acknowledgement 54
Chapter 4 Geostatistical Characterization of Gravel Bed Surface Using Airborne Laser Scanning 55
4.1 Introduction 55
4.2 Data 57
4.2.1 Laser scanning 57
4.2.2 Simulated flow direction 64
4.3 Method 64
4.3.1 Estimation of the gravel bed roughness 64
4.3.2 Flow direction comparison 65
4.4 Results and Discussion 66
4.4.1 2-D variogram surfaces 66
4.4.2 Direction of maximum continuity in area E 71
4.4.3 Comparison of flow direction 73
4.4.4 Regularization 79
4.4.5 Gravel bed roughness 83
4.5 Conclusion 91
Chapter 5 Conclusion 93
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