Point Cloud Technologies for Geomorphologists: From Data Acquisition to Processing

145 Pages·2022·6.889 MB·English

by  Christopher Gomez

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Christopher Gomez
Point Cloud Technologies
for Geomorphologists
From Data Acquisition to Processing
123
Christopher Gomez
Kobe University
Kobe,Hyogo,Japan
ISSN 2510-1307 ISSN 2510-1315 (electronic)
SpringerTextbooks inEarth Sciences, GeographyandEnvironment
ISBN978-3-031-10974-4 ISBN978-3-031-10975-1 (eBook)
https://doi.org/10.1007/978-3-031-10975-1
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To my wife, Junko, for her continuous support,
and to my parents and brothers who have been the silent victims of my
scientific tribulations that seldom brings me back to the country road.
Preface
GeomorphologyisthedisciplinethatinvestigatesthesurfaceoftheEarth,byexaminingboth
the landforms (literally the land–forms) and the processes that shape those landforms. The
landforms are associated with processes that can be endogenous (such as earthquakes and
volcanicactivity) andexogenous (such as rainfall erosion andwind deflation),as well as any
combinationofthetwo(e.g.landslides,debrisflowsandothermassmovementsthatareoften
atthecrossroadbetweenslopesgeneratedbytectonicupliftforinstanceandtheroleofwater
mixed with sediments under the action of gravity, etc.). Other processes notably include
human influences and zoogeomorphology, for instance, etc.
To measure these processes and landforms, geomorphologists use a wide variety of tools,
among which we can now count pointcloud technologies, which have become a household
name in most laboratories. In this book, which is also designed as a manual, I have tried to
give a presentation of the different methods to collect field data and then process them for
geomorphologicalpurposes.Thefirstgroupofchapters(moretechnical) isthencompletedby
a set of chapters divided between geomorphological environments and processes. The diffi-
cultythere,wastogiveanintroductiontosomeconceptsthatwereofimportance,butwithout
it becoming yet another introductory geomorphology book. Choices were thus made and
for instance, in the chapter on landslide, I give some elements of slope stability and soil
mechanics,becauseincombinationwithpoint-cloudtechnologies,theycan—Ibelieve—bring
to the discussion table the importance of some of the topographic details that were estimated
or just overlooked.
As I started my geomorphologist career at Paris 1 Sorbonne University in France, before
movingtoParis7University(nowParisUniversity),digitalelevationmodelsandgriddeddata
were just emerging in the field and the geospatial education in GIS and other applied tech-
niques was still in its infancy, and it certainly took some extra work to get up to speed and
remainingrelevantthroughmycareer,whichisabitmorethanadecadeaftermyPh.D.whenI
amwriting those lines.AndIhavecertainlyfeltthethrillofthese newtechniquesandseeing
growing in the field of geomorphology all the new options that were offered to us, but at the
sametime,Ididnottakemuchtimetoreflectontherealnatureofthechanges,metamorphosis
and modifications that new technologies were operating on the scientific field. Of course, I
wouldratherliketoseethetoolsservingtheidea,butIamforcedtoadmitthatinthepresent
case the tool has provided deep changes to the very approach and the vision that we have of
geomorphology.ThisiswhyIamkeepingChap.7todiscusssomeofthosepoints,althoughI
already provide some quick hints in the introduction.
WhenIwrotethisbook,Ihadthestudentsofgeomorphologyinmind,andalthoughIknow
thattheycanfindseveralexcellentmonographsonlandformsandtheEarthsurfaceprocesses,
I have failed to identify a complete manuscript on pointcloud technologies that have recently
emergedinthefieldofgeomorphology.Ofcourse,thereareseveralbooksinremotesensing,
incivilandotherengineeringfields,butIdidnotfindanythingthatwaseasilyaccessibletoall
geomorphologists regardless of their physics and mathematics background. I have therefore
triedtobridgethatgap.Furthermore,Icertainlyhadmyownstudentsinmind,thinkingthatit
wouldbenicetohaveashort-handbookthattheycouldgotowhentheyneedtoeithercollect
or process pointclouds in a given geomorphological environment and at a given scale.
vii
viii Preface
As any monograph, it is a work in progress and even after publication, we will all find
different ways to improve the manuscript further, and in advance, I thank the readers for any
constructive comments they will provide me with.
Kobe, Japan Christopher Gomez
2021
Contents
1 Pointcloud and Geomorphology—Introduction . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Adjustments Needed in the Working Paradigms of Geomorphologists. . . . . . 3
1.1.1 From Single Measurement to Pointcloud . . . . . . . . . . . . . . . . . . . . . 3
1.1.2 From Error Measurement to Error Estimation . . . . . . . . . . . . . . . . . . 4
1.1.3 The Need for a Paradigm Shift: Shaping the Question. . . . . . . . . . . . 4
1.2 Logic and Content of this Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
References and Suggested Readings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 Pointcloud Generation in Geomorphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 LiDAR Point-Cloud in Geomorphology . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.1 The Introduction of Laser Technologies in Geomorphology. . . . . . . . 8
2.1.2 LiDAR—How Does It Work? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.3 The Different Types of LiDAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.1.4 Hybrid Solutions Combining Total Station and Laser Scanning . . . . . 17
2.1.5 From Fieldwork to Point-Cloud . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2 SfM-MVS:StructurefromMotion―Multiple-ViewStereophotogrammetry. . . 19
2.3 Emergence and Timeliness of SfM-MVS in Geosciences . . . . . . . . . . . . . . . 22
2.3.1 Protocol Proposed for SfM-MVS Photogrammetry
in Geomorphology (After James et al. [16]) . . . . . . . . . . . . . . . . . . . 22
2.3.2 ExampleofaStep-By-StepWorkflowwithAgisoftMetashapePro . . . 24
2.4 From Quantitative to Qualitative: SfM-MVS “Photogrammology” . . . . . . . . 26
References and Further Readings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3 Point-Cloud Processing and Derivatives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.1 Point-Cloud Format, Visualization, Classification and Division. . . . . . . . . . . 32
3.1.1 Point-Cloud Formats and Extensions . . . . . . . . . . . . . . . . . . . . . . . . 32
3.1.2 Pointcloud Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.1.3 Classification of Points/Selecting Points for Computing. . . . . . . . . . . 33
3.1.4 Forward Outlooks for Filtering and Classification . . . . . . . . . . . . . . . 36
3.1.5 Comparison of Two Pointclouds . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.2 Data Conversion: From Pointclouds to Other Formats . . . . . . . . . . . . . . . . . 40
3.2.1 Triangulated Irregular Network (TIN) Data. . . . . . . . . . . . . . . . . . . . 40
3.2.2 Gridded Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.2.3 Making Measurements from a Structured Point-Cloud. . . . . . . . . . . . 41
3.2.4 The Three Most Common Derivatives for Regularly Spaced
Pointclouds and Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.2.5 Manual Control of Object Elevation from Dense Point-Cloud
with RGB Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.3 Example to Extract Data on a Grid from a Pointcloud with R and LidR . . . . 44
3.4 Quality and Error Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.4.1 The Different Types of Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
ix
x Contents
3.4.2 Measuring and Communicating the Error of a Pointcloud . . . . . . . . . 48
3.4.3 Error Propagation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
References Used in the Chapter and Further Reading. . . . . . . . . . . . . . . . . . . . . . 51
4 Point-Cloud Technology for Coastal and Floodplain Geomorphology . . . . . . . 53
4.1 Introductory Few Words on Coastal and Floodplain Geomorphology . . . . . . 54
4.1.1 Floodplain and Channel Geomorphology . . . . . . . . . . . . . . . . . . . . . 54
4.1.2 Coastal Processesandlandforms—ARapidGlance attheProcesses
that Make and Change the Coast . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.2 Point-Cloud Technology and the Floodplain . . . . . . . . . . . . . . . . . . . . . . . . 57
4.2.1 SfM-MVS and LiDAR for Floodplain Geomorphology . . . . . . . . . . . 57
4.2.2 Examples at Different Scales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.2.3 Toolboxes for LiDAR Data Processing in Fluvial Geomorphology. . . 63
4.3 Selected Coastal Landforms and Adapted Point-Cloud Technologies. . . . . . . 63
4.3.1 Point-Cloud Technologies for Coastal Geomorphology . . . . . . . . . . . 63
4.3.2 Cliffs and Point-Cloud Technologies . . . . . . . . . . . . . . . . . . . . . . . . 64
4.3.3 Coastal Dunes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.3.4 Beaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.3.5 Spits and Coastal Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.3.6 Submerged and Semi-submerged Landforms: Shore Platforms,
Estuaries, Deltas, Coastal Marsh and Wetlands . . . . . . . . . . . . . . . . . 69
4.3.7 A Few Words on Managed and Degraded Landforms . . . . . . . . . . . . 69
4.4 Worked Example with R: A Meander on the Alabama River . . . . . . . . . . . . 71
4.5 Worked Coastal Example with R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.5.1 Extracting Cross Sections in R with the LidR Package . . . . . . . . . . . 75
4.5.2 Extracting Coastal Data on a Grid in R with the LidR Package . . . . . 76
References and Suggested Readings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5 Pointcloud and Hillslope Geomorphology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5.1 A Rapid Overview of Hillslope Geomorphology and a Selection
of the Processes That Make Them . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.1.1 Focus on Some Remarkable Hillslope Processes. . . . . . . . . . . . . . . . 85
5.1.2 The Role of the Relief and Gravity in Driving Denudation
Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.1.3 Hard-Rock Hillslopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.1.4 Hillslopes in Sediment Formation and Sedimentary “Soft-Rocks” . . . 86
5.1.5 Applied Hillslope Geomorphology and Civil Engineering . . . . . . . . . 87
5.2 Hillslope Geomorphology and Point-Cloud Technology . . . . . . . . . . . . . . . . 88
5.2.1 Landforms Associated with Hillslope Drainages . . . . . . . . . . . . . . . . 88
5.2.2 Landforms Associated with Hillslope Interfluves. . . . . . . . . . . . . . . . 90
5.2.3 Tectonic Deformations and Ruptures . . . . . . . . . . . . . . . . . . . . . . . . 91
5.2.4 Mass Movements, Slope Collapses and Fans . . . . . . . . . . . . . . . . . . 91
5.3 Worked Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.3.1 Road-Side Slope Monitoring Using Low-Cost SLAM-LiDAR
Sensor and SfM-MVS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.3.2 Aligning a Debris-Flow Fan Lidar-Based DEM and a SfM-MVS
Point-Cloud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.3.3 Detrending the Topography to Extract Small-Scale Features
and Trees in R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.3.4 Using the Trees as a Proxy of Slope and Other Geomorphological
Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94