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Key Features:
• A specific focus on management applications in a period of increasing demands on managers to characterize river features and their evolution at different spatial scales
• An integration across all scales of imagery with a clear discussion of both ground based and airborne images
• Includes a wide-range of environmental problems
• Coverage of cutting-edge technology
• Contributions from leading researchers in the field
Foreword, xvii
List of Contributors, xix
1 Introduction: The Growing Use of Imagery in Fundamental and Applied River Sciences, 1
Patrice E. Carbonneau and Herv´e Pi´egay
1.1 Introduction, 1
1.2 Remote sensing, river sciences and management, 2
1.2.1 Key concepts in remote sensing, 2
1.2.2 A short introduction to ‘river friendly’ sensors and platforms, 4
1.2.3 Cost considerations, 7
1.3 Evolution of published work in Fluvial Remote Sensing, 8
1.3.1 Authorships and Journals, 9
1.3.2 Platforms and Sensors, 9
1.3.3 Topical Areas, 10
1.3.4 Spatial and Temporal Resolutions, 14
1.3.5 Summary, 16
1.4 Brief outline of the volume, 16
References, 17
2 Management Applications of Optical Remote Sensing in the Active River Channel, 19
W. Andrew Marcus, Mark A. Fonstad and Carl J. Legleiter
2.1 Introduction, 19
2.2 What can be mapped with optical imagery?, 20
2.3 Flood extent and discharge, 21
2.4 Water depth, 22
2.5 Channel change, 24
2.6 Turbidity and suspended sediment, 25
2.7 Bed sediment, 27
2.8 Biotypes (in-stream habitat units), 29
2.9 Wood, 31
2.10 Submerged aquatic vegetation (SAV) and algae, 31
2.11 Evolving applications, 33
2.12 Management considerations common to river applications, 33
2.13 Accuracy, 35
2.14 Ethical considerations, 36
2.15 Why use optical remote sensing?, 36
References, 38
3 An Introduction to the Physical Basis for Deriving River Information by Optical Remote Sensing, 43
Carl J. Legleiter and Mark A. Fonstad
3.1 Introduction, 43
3.2 An overview of radiative transfer in shallow stream channels, 45
3.2.1 Quantifying the light field, 45
3.2.2 Radiative transfer processes along the image chain, 49
3.3 Optical characteristics of river channels, 54
3.3.1 Reflectance from the water surface, 55
3.3.2 Optically significant constituents of the water column, 55
3.3.3 Reflectance properties of the streambed and banks, 58
3.4 Inferring river channel attributes from remotely sensed data, 60
3.4.1 Spectrally-based bathymetric mapping via band ratios, 60
3.4.2 Relative magnitudes of the components of the at-sensor radiance signal, 61
3.4.3 The role of sensor characteristics, 62
3.5 Conclusion, 66
3.6 Notation, 67
References, 68
4 Hyperspectral Imagery in Fluvial Environments, 71
Mark J. Fonstad
4.1 Introduction, 71
4.2 The nature of hyperspectral data, 72
4.3 Advantages of hyperspectral imagery, 74
4.4 Logistical and optical limitations of hyperspectral imagery, 75
4.5 Image processing techniques, 78
4.6 Conclusions, 82
Acknowledgments, 82
References, 82
5 Thermal Infrared Remote Sensing of Water Temperature in Riverine Landscapes, 85
Rebecca N. Handcock, Christian E. Torgersen, Keith A. Cherkauer, Alan R. Gillespie, Klement Tockner, Russel N. Faux and Jing Tan
5.1 Introduction, 85
5.2 State of the art: TIR remote sensing of streams and rivers, 88
5.3 Technical background to the TIR remote sensing of water, 91
5.3.1 Remote sensing in the TIR spectrum, 91
5.3.2 The relationship between emissivity and kinetic and radiant temperature, 92
5.3.3 Using Planck’s Law to determine temperature from TIR observations, 93
5.3.4 Processing of TIR image data, 94
5.3.5 Atmospheric correction, 94
5.3.6 Key points, 95
5.4 Extracting useful information from TIR images, 96
5.4.1 Calculating a representative water temperature, 96
5.4.2 Accuracy, uncertainty, and scale, 96
5.4.3 The near-bank environment, 97
5.4.4 Key points, 98
5.5 TIR imaging sensors and data sources, 98
5.5.1 Ground imaging, 98
5.5.2 Airborne imaging, 98
5.5.3 Satellite imaging, 101
5.5.4 Key points, 101
5.6 Validating TIR measurements of rivers, 102
5.6.1 Timeliness of data, 102
5.6.2 Sampling site selection, 103
5.6.3 Thermal stratification and mixing, 104
5.6.4 Measuring representative temperature, 104
5.6.5 Key points, 105
5.7 Example 1: Illustrating the necessity of matching the spatial resolution of the TIR imaging device to river width using multi-scale observations of water temperature in the Pacific Northwest (USA), 106
5.8 Example 2: Thermal heterogeneity in river floodplains used to assess habitat diversity, 108
5.9 Summary, 108
Acknowledgements, 109
5.10 Table of abbreviations, 110
References, 110
6 The Use of Radar Imagery in Riverine Flood Inundation Studies, 115
Guy J-P. Schumann, Paul. D. Bates, Giuliano Di Baldassarre and David C. Mason
6.1 Introduction, 115
6.2 Microwave imaging of water and flooded land surfaces, 116
6.2.1 Passive radiometry, 117
6.2.2 Synthetic Aperture Radar, 117
6.2.3 SAR interferometry, 119
6.3 The use of SAR imagery to map and monitor river flooding, 120
6.3.1 Mapping river flood inundation from space, 120
6.3.2 Sources of flood and water detection errors, 124
6.3.3 Integration with flood inundation modelling, 129
6.4 Case study examples, 129
6.4.1 Fuzziness in SAR flood detection to increase confidence in flood model simulations, 129
6.4.2 Near real-time flood detection in urban and rural areas using high resolution space-borne SAR images, 131
6.4.3 Multi-temporal SAR images to inform about floodplain dynamics, 133
6.5 Summary and outlook, 135
References, 137
7 Airborne LiDAR Methods Applied to Riverine Environments, 141
Jean-St´ephane Bailly, Paul J. Kinzel, Tristan Allouis, Denis Feurer and Yann Le Coarer
7.1 Introduction: LiDAR definition and history, 141
7.2 Ranging airborne LiDAR physics, 142
7.2.1 LiDAR for emergent terrestrial surfaces, 142
7.2.2 LiDAR for aquatic surfaces, 144
7.3 System parameters and capabilities: examples, 146
7.3.1 Large footprint system: HawkEye II, 146
7.3.2 Narrow footprint system: EAARL, 147
7.3.3 Airborne LiDAR capacities for fluvial monitoring: a synthesis, 148
7.4 LiDAR survey design for rivers, 148
7.4.1 Flight planning and optimising system design, 148
7.4.2 Geodetic positioning, 150
7.5 River characterisation from LiDAR signals, 150
7.5.1 Altimetry and topography, 150
7.5.2 Prospective estimations, 152
7.6 LiDAR experiments on rivers: accuracies, limitations, 153
7.6.1 LiDAR for river morphology description: the Gardon River case study, 153
7.6.2 LiDAR and hydraulics: the Platte River experiment, 154
7.7 Conclusion and perspectives: the future for airborne LiDAR on rivers, 158
References, 158
8 Hyperspatial Imagery in Riverine Environments, 163
Patrice E. Carbonneau, Herv ´e Pi´egay, J ´ er ˆome Lejot, Robert Dunford and Kristell Michel
8.1 Introduction: The Hyperspatial Perspective, 163
8.2 Hyperspatial image acquisition, 166
8.2.1 Platform considerations, 166
8.2.2 Ground-tethered devices, 166
8.2.3 Camera considerations, 170
8.2.4 Logistics and costs, 172
8.3 Issues, potential problems and plausible solutions, 172
8.3.1 Georeferencing, 173
8.3.2 Radiometric normalisation, 176
8.3.3 Shadow correction, 176
8.3.4 Image classification, 179
8.3.5 Data mining and processing, 180
8.4 From data acquisition to fluvial form and process understanding, 182
8.4.1 Feature detection with hyperspatial imagery, 182
8.4.2 Repeated surveys through time, 183
8.5 Conclusion, 188
Acknowledgements, 189
References, 189
9 Geosalar: Innovative Remote Sensing Methods for Spatially Continuous Mapping of Fluvial Habitat at Riverscape Scale, 193
Normand Bergeron and Patrice E. Carbonneau
9.1 Introduction, 193
9.2 Study area and data collection, 194
9.3 Grain size mapping, 194
9.3.1 Superficial sand detection, 196
9.3.2 Airborne grain size measurements, 198
9.3.3 Riverscape scale grain size profile and fish distribution, 200
9.3.4 Limitations of airborne grain size mapping, 200
9.3.5 Example of application of grain size maps and long profiles to salmon habitat modelling, 201
9.4 Bathymetry mapping, 203
9.5 Further developments in the wake of the Geosalar project, 205
9.5.1 Integrating fluvial remote sensing methods, 205
9.5.2 Habitat data visualisation, 207
9.5.3 Development of in-house airborne imaging capabilities, 208
9.6 Flow velocity: mapping or modelling?, 209
9.7 Future work: Integrating fish exploitation of the riverscape, 211
9.8 Conclusion, 211
Acknowledgements, 212
References, 212
10 Image Utilisation for the Study and Management of Riparian Vegetation: Overview and Applications, 215
Simon Dufour, Etienne Muller, Menno Straatsma and S. Corgne
10.1 Introduction, 215
10.2 Image analysis in riparian vegetation studies: what can we know?, 217
10.2.1 Mapping vegetation types and land cover, 217
10.2.2 Mapping species and individuals, 220
10.2.3 Mapping changes and historical trajectories, 220
10.2.4 Mapping other floodplain characteristics, 220
10.3 Season and scale constraints in riparian vegetation studies, 221
10.3.1 Choosing an appropriate time window for detecting vegetation types, 221
10.3.2 Minimum detectable object size in the riparian zone, 221
10.3.3 Spatial/spectral equivalence for detecting changes, 221
10.4 From scientists’ tools to managers’ choices: what do we want to know? And how do we get it?, 223
10.4.1 Which managers? Which objectives? Which approach?, 224
10.4.2 Limitations of image-based approaches, 224
10.5 Examples of imagery applications and potentials for riparian vegetation study, 226
10.5.1 A low-cost strategy for monitoring changes in a floodplain forest: aerial photographs, 226
10.5.2 Flow resistance and vegetation roughness parametrisation: LiDAR and multispectral imagery, 228
10.5.3 Potential radar data uses for riparian vegetation characterisation, 230
10.6 Perspectives: from images to indicators, automatised and standardised processes, 233
Acknowledgements, 234
References, 234
11 Biophysical Characterisation of Fluvial Corridors at Reach to Network Scales, 241
Herv´e Pi´egay, Adrien Alber, J. Wesley Lauer, Anne-Julia Rollet and Elise Wiederkehr
11.1 Introduction, 241
11.2 What are the raw data available for a biophysical characterisation of fluvial corridors?, 242
11.3 How can we treat the information?, 243
11.3.1 What can we see?, 243
11.3.2 Strategy for exploring spatial information for understanding river form and processes, 245
11.3.3 Example of longitudinal generic parameters treatment using unorthorectified photos, 248
11.3.4 The aggregation/disaggregation procedure applied at a regional network scale, 250
11.4 Detailed examples to illustrate management issues, 253
11.4.1 Retrospective approach on the Ain River: understanding channel changes and providing a sediment budget, 254
11.4.2 The Droˆme network: example of up- and downscaling approach using homogeneous geomorphic reaches, 256
11.4.3 Inter-reach comparisons at a network scale, 259
11.5 Limitations and constraints when enlarging scales of interest, 261
11.6 Conclusions, 265
Acknowledgements, 265
References, 266
12 The Role of Remotely Sensed Data in Future Scenario Analyses at a Regional Scale, 271
Stan Gregory, Dave Hulse, M´ elanie Bertrand and Doug Oetter
12.1 Introduction, 271
12.1.1 The purposes of scenario-based alternative future analyses, 272
12.1.2 Processes of depicting alternative future scenarios, 272
12.1.3 Methods of employing remotely sensed information in alternative futures, 278
12.1.4 Alternative future scenarios for the Willamette River, Oregon as a case study, 278
12.2 Methods, 279
12.2.1 Ground truthing, 281
12.2.2 Use of remotely sensed data in the larger alternative futures project, 282
12.3 Land use/land cover changes since 1850, 282
12.4 Plan trend 2050 scenario, 283
12.5 Development 2050 scenario, 287
12.6 Conservation 2050 scenario, 287
12.7 Informing decision makers at subbasin extents, 289
12.8 Discussion, 291
Acknowledgements, 294
References, 294
13 The Use of Imagery in Laboratory Experiments, 299
Michal Tal, Philippe Frey, Wonsuck Kim, Eric Lajeunesse, Angela Limare and Franc¸ois M´etivier
13.1 Introduction, 299
13.2 Bedload transport, 300
13.2.1 Image-based technique to measure grainsize distribution and sediment discharge, 302
13.2.2 Particle trajectories and velocities using PTV, 304
13.3 Channel morphology and flow dynamics, 306
13.3.1 Experimental deltas, 308
13.3.2 Experimental river channels with riparian vegetation, 309
13.4 Bed topography and flow depth, 312
13.5 Conclusions, 317
Acknowledgements, 318
References, 318
14 Ground based LiDAR and its Application to the Characterisation of Fluvial Forms, 323
Andy Large and George Heritage
14.1 Introduction, 323
14.1.1 Terrestrial laser scanning in practice, 324
14.2 Scales of application in studies of river systems, 325
14.2.1 The sub-grain scale, 325
14.2.2 The grain scale, 325
14.2.3 The sub-bar unit scale, 327
14.2.4 In-channel hydraulic unit scale, 329
14.2.5 Micro-topographic roughness units, 330
14.2.6 The bar unit scale, 330
14.2.7 Reach-scale morphological analyses, 332
14.2.8 Terrestrial laser scanning at the landscape scale, 334
14.2.9 Towards a protocol for TLS surveying of fluvial systems, 336
References, 338
15 Applications of Close-range Imagery in River Research, 341
Walter Bertoldi, Herv´e Pi´egay, Thomas Buffin-B´ elanger, David Graham and Stephen Rice
15.1 Introduction, 341
15.2 Technologies and practices, 342
15.2.1 Technology, 342
15.2.2 Overview of possible applications, 344
15.3 Post-processing, 347
15.3.1 Analysis of vertical images for particle size, 347
15.3.2 Analysis of vertical images for particle shape, 349
15.3.3 Analysis of oblique ground images, 349
15.4 Application of vertical and oblique close-range imagery to monitor bed features and fluvial processes at different spatial and temporal scales, 350
15.4.1 Vertical ground imagery for characterising grain size, clast morphometry and petrography of particles, 350
15.4.2 Monitoring fluvial processes, 352
15.4.3 Survey of subaerial bank processes, 353
15.4.4 Inundation dynamics of braided rivers, 355
15.4.5 River ice dynamics, 356
15.4.6 Riparian structure and dead wood distributions along river corridors, 359
15.5 Summary of benefits and limitations, 361
15.6 Forthcoming issues for river management, 362
Acknowledgements, 363
References, 363
16 River Monitoring with Ground-based Videography, 367
Bruce J. MacVicar, Alexandre Hauet, Normand Bergeron, Laure Tougne and Imtiaz Ali
16.1 Introduction, 367
16.2 General considerations, 368
16.2.1 Flow visualisation and illumination, 368
16.2.2 Recording, 368
16.2.3 Image ortho-rectification, 369
16.3 Case 1 – Stream gauging, 369
16.3.1 Introduction, 369
16.3.2 Field site and apparatus, 370
16.3.3 Image processing, 370
16.3.4 Stream gauging, 371
16.3.5 Results, 371
16.4 Case 2 – Filtering bed and flare effects from LSPIV measurements, 372
16.4.1 Introduction, 372
16.4.2 Field site and apparatus, 373
16.4.3 Data filtering, 373
16.4.4 Results, 373
16.5 Case 3 – At-a-point survey of wood transport, 376
16.5.1 Introduction, 376
16.5.2 Field site and apparatus, 376
16.5.3 Manual detection and measurement, 376
16.5.4 Image segmentation and analysis, 377
16.5.5 Results, 379
16.6 Discussion and conclusion, 380
References, 381
17 Imagery at the Organismic Level: From Body Shape Descriptions to Micro-scale Analyses, 385
Pierre Sagnes
17.1 Introduction, 385
17.2 Morphological and anatomical description, 386
17.2.1 Identification, 386
17.2.2 Characterisation of life-history traits and ontogenetic stages, 390
17.2.3 Ecomorphological studies, 393
17.3 Abundance and biomass, 394
17.4 Detection of stress and diseases, 396
17.4.1 Direct visualisation of stress (or its effects), 396
17.4.2 Activity of organisms as stress indicator, 398
17.4.3 Fluctuating asymmetry as stress indicator, 398
17.5 Conclusion, 399
References, 399
18 Ground Imagery and Environmental Perception: Using Photo-questionnaires to Evaluate River Management Strategies, 405
Yves-Francois Le Lay, Marylise Cottet, Herv´e Pi´egay and Anne Rivi `ere-Honegger
18.1 Introduction, 405
18.2 Conceptual framework, 406
18.3 The design of photo-questionnaires, 409
18.3.1 The questionnaire and selection of photographs, 409
18.3.2 The attitude scales, 410
18.3.3 The selection of participant groups, 412
18.4 Applications with photo-questionnaires, 412
18.4.1 From judgment assessment to judgment prediction, 412
18.4.2 Comparing reactions between scenes and between observers, 415
18.4.3 Linking judgments to environmental factors, 417
18.4.4 Modelling and predicting water landscape judgments, 420
18.4.5 Photographs and landscape perception, a long history of knowledge production, 420
18.5 Conclusions and perspectives, 425
Acknowledgements, 426
References, 426
19 Future Prospects and Challenges for River Scientists and Managers, 431
Patrice E. Carbonneau and Herv´e Pi´egay
References, 433
Index, 435
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