Structure from Motion in the Geosciences

Jonathan Carrivick is a Senior Lecturer in Geomorphology in the School of Geography, University of Leeds, UK. His primary research interests lie within polar, arctic and alpine ice-marginal systems, and especially focus on glacier outburst floods and proglacial lakes. He specialises in digital topographic surveying, especially for construction of terrain models for input to morphodynamic computer simulations, and for detecting rapid geomorphological changes and geomorphological coupling in glaciers, alpine hillslopes, moraines and gravel bed and bedrock rivers.Dr Mark Smith is a Lecturer in Water Research in the School of Geography, University of Leeds, UK. His research focuses on the interactions of rough surfaces with air and water flows and methods of quantifying that roughness, with particular application to fluvial hydraulics, sediment transport and surface energy balances. He is a specialist in high resolution survey methods having worked with Terrestrial Laser Scanners for over a decade and more recently using Structure-from-Motion datasets in a range of environments, from gravel bed rivers, to eroding badlands to melting glacier ice.Dr Duncan Quincey is an Associate Professor in Geomorphology in the School of Geography, University of Leeds, UK. His research focuses on the evolution of glacial and alpine environments, with particular interests in the processes controlling lake development and outburst flooding. He is a remote sensing specialist with skills in developing optical- and SAR-based methods for retrieving surface velocity data from satellite imagery and in employing novel remote sensing methods, such as Structure-from-Motion, to data model geophysical processes.

• AbbreviationsAbout the companion websiteChapter 1: Introduction to Structure from Motion for the geosciences1.1. The geosciences and related disciplines1.2. Aim and scope of this book1.3. The time and the place1.4. What is Structure from Motion?1.5. Structure of this bookReferencesChapter 2: The place of Structure from Motion: a new paradigm in topographic surveying?2.1. Introduction2.2. Direct topographic surveying2.3. Remote digital surveying2.4. Chapter summaryReferencesFurther Reading/ResourcesChapter 3: Background to Structure from Motion3.1. Introduction3.2. Feature Detection3.3. Keypoint Correspondence3.4. Identifying Geometrically Consistent Matches3.5. Structure from Motion3.6. Scale and Georeferencing3.7. Optimization of Image Alignment3.8. Clustering for Multi View Stereo3.9. Multi View Stereo Image Matching Algorithms3.10. SummaryReferencesFurther Reading/ResourcesChapter 4: Structure from Motion in practice4.1. Introduction4.2. Platforms4.3. Sensors4.4. Acquiring images and control data4.5. Software4.6. Point cloud viewers4.7. Filtering4.8. Generating digital elevation models (DEMs) from point clouds4.9. Key issues4.10. Chapter summaryReferencesFurther readingChapter 5: Quality assessment: quantifying error in Structure from Motion-derived topographic data5.1. Introduction5.2. Validation Data Sets5.3. Validation Methods5.4. Survey Platform5.5. Error Metrics5.6. Distribution of Ground Control Points5.7. Terrain5.8. Software5.9. Camera5.10. SummaryReferencesFurther Reading/ResourcesChapter 6: Current applications of Structure from Motion in the geosciences6.1. Introduction6.2. Use of SfM-MVS-derived orthophotograph mosaics6.3. Use of SfM-MVS for 3D point clouds6.4. Use of SfM-MVS for gridded topography6.5. Combined orthophotograph and point cloud analysis6.6. Crossing temporal scales: Examples of change detection to suggest process dynamics6.7. Practitioner-based SfM-MVS6.8. Chapter summaryReferencesFurther Reading/ResourcesChapter 7: Developing Structure from Motion for the geosciences: future directions7.1. Introduction7.2. Developments in hardware7.3. Progressive automation of acquisition7.4. Efficient management and manipulation of photographs7.5. Point cloud generation and decimation7.6. Real-time SfM-MVS and instant maps: Simultaneous Localization And Mapping (SLAM)7.7. Augmented reality7.8. Detection of object or surface motion: non-rigid SfM (NRSfM)7.9. Chapter summaryReferencesFurther Reading/ResourcesChapter 8: Concluding recommendations8.1. Key Recommendation 1: get ‘under the bonnet’ of SfM-MVS to become more critical end-users8.2. Key Recommendation 2: get coordinated to understand the sources and magnitudes of error8.3. Key Recommendation 3: focus on the research question8.4. Key Recommendation 4: focus your efforts on data processing8.5. Key Recommendation 5: learn from other disciplines8.6. Key Recommendation 6: harness the democratising power of SfM-MVSIndex

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