Terrestrial Laser Scanning in
River Environments
Laser Scanner
Dr David Hetherington
Ove Arup and Partners, Newcastle upon Tyne, UK.
Tuesday the 1st June 2010
Universidad Javeriana, Bogota, Colombia
Photograph – River Wharfe Laser Scan Model – River Wharfe
Laser Scanner
Presentation Structure
•Spatial Data Theory
•Terrestrial Laser Scanning principles and
operation• Reflectivity, Time-of-flight measurement, Scanner operation
• Potential uses and example projects• Example projects, Potential applications, where next?
• Benefits and Limitations• Fit-for-purpose?
•Questions
What is good quality spatial data?...
Processing spatial data into elevation models
• Manual filtering – to remove anomalies
• Ground filtering – to remove lowest or highest
points
• Regularisation / gridding – to allow for surfacing
• Averaging – between surveys
• Lumping – all data together
• Extrapolation – estimating beyond surveys
• Interpolation – predicting lines and data between
points
• ALL OF THESE IMPACT ON DATA QUALITY
Interpolation – various methods
(From Keckler 2001)
Survey Methods: Thedolite/GPS
2 people x 3 days =
4000 data points
Aerial Photo
Survey inaccuracy: Form
Interpolation
Survey method and interpolation error
Potential volumetric estimation error for various survey techniques,
and interpolation methods in a river system (from Milan et al,
2007)
Example complex (yet high quality)
input spatial data – Terrestrial lidar
Terrestrial Laser Scanning (TLS) - types
• Various types exist• Ultra-short range (hand held static) used in manufacturing,
medicine, archaeology
• Short range (mobile static) used in heritage, archaeology, small
buildings
• Medium range (mobile static) used in buildings, street scenes,
infrastructure.
• Long Range (mobile static) used for large buildings,
townscapes, topographical surveys, mining, forestry.
• Vehicle Based (mobile dynamic) automated survey and data
registration. Used to easily map towns, long roads, motorways
etc.
• All have their relative benefits and weaknesses.
• Choosing the correct method is key
Measurement using Laser Scanning –
Basic Principles
•Lidar:• “Light Detection And Ranging” using a pulsed laser beam.
• Numerous automated measurements = Scanning
• 3 platforms for lidar scanning• Satellites (extremely long range)
• Airborne (long to moderate range)
• Terrestrial (very short to moderate range)
• All based on time-of-flight principles of laser pulses
• All are reflectorless and non-contact.
• Measurements are based on reflections from physical
surfaces
Laser measurement theory - REFLECTIVITY
• 3 types of light reflection:
Diffuse Mirror-like Retro
(most surfaces) (Glass, mirrors flat
water surfaces)
(roadsigns, bike
reflectors, strips on
high-vis jackets)
Time-of-flight measurement
• A laser pulse generator sends out infrared light pulses.
• Reflected echo signals generate a receiver signal.
• Time interval counted by a quartz-stabilised clock frequency.
• The calculated range value is then processed and saved.
A simplified lidar scanner
1. Range finder electronics
2. Laser beam
3. Rotating mirror
4. Rotating optical head
5. Connection to Laptop
6. Laptop
7. Software
Terrestrial laser scan data
• Range of up to 1500m (for highly reflective surfaces)
• Sub-cm accuracy
• A single scan can contain over 7-million data points
• A single model is made of multiple scans from various
locations to avoid data shadow
• Each coordinate point is associated with colour (as
measured by an integrated camera) and intensity
(reflectivity) information.
• Data and scans are automatically georeferenced using
an integrated GPS system.
• Can be easily linked to thermal imagery cameras.
Riegl LMSZ420 laser scanner
• Arup own this model of medium-long range
scanner.
• Time of Flight-based scanner
• Range of around 1km
• Point accuracy of around 10mm (can be reduced to
around 5mm with repeat scanning)
• Allowing for very high resolution point clouds.
• Integrated camera captures colour data
• Captures intensity of return data and attached to
each coordinate (along with colour).
Riegl LMSZ420 laser scanner
Fine sedimentmovement
Cross-sectionadjustment
Planform change
Reach scaleslope adjustment
River scale slope adjustment
Barform change
1mm
1m
1km
1000km
1 day 1 year 1000 years 10000 years1 month
Inc
rea
sin
gS
pa
tia
lS
ca
le
Increasing Time Scale
Spatial & Temporal Change
Rates
1mm
1m
1km
1000km
1 day 1 year 1000 years 10000 years1 month
Inc
rea
sin
g S
pa
tia
l S
cale
Increasing Time Scale
Photogrametry
GPS
Theodolite
Aerial Photo's
AirborneLIDAR
Spatial & Temporal Survey
Limits
1mm
1m
1km
1000km
1 day 1 year 1000 years 10000 years1 month
Inc
rea
sin
g S
pa
tia
l S
cale
Increasing Time Scale
Photogrametry
GPS
Theodolite
Aerial Photo's
AirborneLIDAR
Spatial & Temporal Survey
Limits
NO DATA
1mm
1m
1km
1000km
1 day 1 year 1000 years 10000 years1 month
Inc
rea
sin
gS
pa
tial
Sc
ale
Increasing Time Scale
Photogrametry
GPS
Theodolite
Aerial Photo's
AirborneLIDAR
Lidar limits
NO DATATerrestrial LIDAR
Multiple scans and overlap
Multiple scans
from various
perspectives
reduce “shadow”
Point Cloud Model Creation (merging scans)
• All individual scan need to be registered into one
common coordinate system.
• Various ways to do this..
• Quickest and most reliable way is via “pattern
matching” / “surface matching”.
• I-Site software is a good option.
• Allows for surfaces to be created, cross sections to
be cut, volumes calculated, change/deformation to
be observed.
• Output possible in numebrous formats including
CAD.
Example laser scan model – River Wharfe
• 25 High-Resolution Scans
• Scans Merged to within <5mm
• 21 million Data points
• 1 point per cm2
Error Measurement On The Wharfe
0
5
10
15
-1 -0.5 0 0.5 1
b
0
5
10
15
20
-1 -0.5 0 0.5 1
c
Rock Gaps
Grass
x y z
Mean -0.0176 0.00011 0.001078
Standard Error 0.002014 0.004054 0.001856
Median -0.013 0 0.001
Standard Deviation 0.015983 0.032429 0.014846
Sample Variance 0.000255 0.001052 0.00022
Gravel-scale Measurement
8x8m grid in centre of bar was the area of focus
Controlled Experiment Description
• Scans taken at various known distances, heights,
locations, sequences and amounts on and around the
bar.
• Models were merged and processed in various ways
in RiScan Pro, Polyworks and Surfer.
• Models were then tested against a EDM Theodolite
data-based model (appx 3mm accuracy) including 3200
coordinate points within the 8x8 grid.
• EDM data taken systematically across the 8x8 grid in
order to leave surface undisturbed.
• EDM data catagorised as exposed rock tops and
topographic lows.
Example results – Gravel scale measurement
Scan height = 1.5mScan amount = 1Scan locations = n/aScan distance = 10mProcessing = noneScan resolution = maxRepeat scans = noMerging = reflectors only
Mismeasurement errors
All Highs Lows
Min = 0.000001 0.000001 0.00007
Max = 0.121 0.121 0.114
Mean = 0.0243 0.0146 0.0339
Example results – Gravel scale Measurement
Scan height = 1.9mScan amount = 2Scan locations = oppositeScan distance = 20mProcessing = default OCTREEScan resolution = maxRepeat scans = noMerging = reflectors only
Mismeasurement errors
All Highs Lows
Min = 0.00002 0.00002 0.00016
Max = 0.1266 0.1266 0.1124
Mean = 0.0270 0.0205 0.03359
Arolla Outwash Plain Study - Description
• To measure geomorphological change on a daily
basis over a 2-week period.
• Net Change and change at a local level.
• 12 scans were taken between 5AM and 11AM at zero-
low flow after overnight re-freezing of glacier water.
• AIMS
• To test the appropriateness of TLS for such a project.
• To better understand geomorphological change at small
temporal intervals over a number of spatial scales.
• To monitor the gravel resource on the plain
• To better manage extraction for building purposes and
downstream sedimentation.
Arolla/Ferpecle Glacial Outwash Plain, Valais, Switzerland.
Arolla
Ferpecle
300m x 300m
plain
Terrestrial lidar point cloud model
Three Modelled
Scans (out of
twelve available)
Small-Scale Morphological change
• Sub-bar level change
• bank collapse and
deposition
Outwash Plain Reach-Scale Morphology
Total sediment budget and model error
0
20
40
60
80
100
120
140
160
180
2nd-3rd 3rd-4th 4th-5th 5th-7th 7th-9th 9th-10th
Date (June 04)
Sed
imen
t vo
lum
e (
m3)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Dis
ch
arg
e (
m3s-1
)
Deposition
Erosion
Peak discharge
0
5
10
15
20
25
30
-0.1
-0.1
-0.1 -0 -0 0
0.02
0.04
0.06
0.08 0.1
m
freq
uen
cy
Dartford Creek – morphological monitoring
Site
The Dartford Creek - Location
The Dartford Creek - Kent
The Dartford Creek - Kent
The Dartford
BarrierBrushwood
Rig and Plant
Barge
Sheet Piling
The Dartford Creek - Kent
The Dartford Creek - Kent
The Dartford Creek - Kent
The Dartford Creek - Kent
Challenges for measurement and understanding
• Complex morphology (a result of tidal, fluvial and geotechnical
processes)
• Tides
• Operational plant and machinery
• Structurally complex over many scales
• Potential for widespread and subtle change
• Difficult to measure due to ground conditions and available
perspective
Scope of work
• To describe, assess and understand the
geomorphological system
• To monitor the site and habitat geomorphology
during and post construction
Geomorphological
Assessment
• Desk Study
• Walk over survey using
customised pro-forma
• Separated the channel
into process units on
each bank based on key
characteristics and
process evidence
• Noted features within
each process unit
(gullies, shear faces, cut
banks, failures)
• Quantify Morphology..?
4) Dartford Creek
Dartford Creek
Raw point cloud
model
Dartford CreekDartford Creek
Raw point cloud
model
Survey
subtraction
Dartford CreekDartford Creek Compound slope-
elevation
Survey
subtraction
Dartford Creek Compound slope-
elevation
Survey
subtraction
Dartford Creek – 3D model, planform view
Single Scan
Dartford Creek – Model detail
TLS data in GIS
Regionalised
slope map
Compound
slope/elevation map
First survey near to rig
Dartford Creek – Second Survey
Dartford Creek – Second Survey
Area of Slumping
Area of moderate erosion
Dartford Creek – DTM subtraction
XSection9
-2.00
-1.00
0.00
1.00
2.00
3.00
4.00
5.00
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 54.49
Distance (m)
Ele
va
tio
n (
m)
Aug06
Nov-06
Area of deposition
Area of erosion
Digital Terrain Model Subtraction
Sediment BudgetElevation Change
Nenthead Unstable Valley
Survey Description - Nenthead
• Scan surveys completed on 07/10/03 and
16/08/04 (approx 10 months)
• One season of high Discharges
• Concentrated on main unstable slope
(approximately 80% of sediment source area)
• 1st survey no reflectors – 2nd survey with
reflectors
• 5 scan positions (only 2 used)
• Surveys linked using common points between
models in RiScan
Reflector tie points
Used for second
survey modelling
7 reflectors
used
Natural tie points
Used for first
survey modelling
Easily
Identifiable
points
Slope Model
Slope Movement
Erosion and
Deposition
Upstream
stability and
vegetation
growth:
Complicating
Factor
Slope Erosion
Immediate Channel Change
Immediate channel deposition
Volumetric change
Channel Change Volume
(m3)
Positive Volume
[Deposition]:
29.10
Negative Volume
[Erosion]:
33.32
Net Volume [Cut-
Fill]:
- 4.22
Slope Change Volume
(m3)
Positive Volume
[Deposition]:
11.63
Negative Volume
[Erosion]:
77.57
Net Volume [Cut-
Fill]:
- 75.94
• Approximately 80 m3 of sediment removed from the local system
over a 9 month period.
• One high flow season
• Efficient channel – steep and high energy
Downstream engineering works
R. Nent engineered to stabilize mine spoil through
Village of Nenthead.
Series of pools and blockstone rapids created
Pools act as sediment traps
Engineering works model flood hydraulics
20cumec flood simulated using HEC RAS model
Distinct pool-rapid hydraulic shear stress fluctuation
Sub 2mm material just movable in pools
Coarser material likely to be trapped in pools
0
100
200
300
400
500
600
700
0 100 200 300 400 500 600 700 800 900 1000
Flood shear Fine sed threshold Coarse sed threshold
74 cross-
sections
Deposition downstream
0
20
40
60
80
100
120
0.1 1 10 100 1000
Clast size (mm)
Ex
ce
ed
en
ce
pe
rce
nta
ge
POOL 1 POOL 2 POOL 3
Coarse material in pool 1
Fining in downstream pools
Deposition downstream
Deposition measured in
upstream 3 pools up to 2002
Deposition reduced in upper
pool but continuing in pools 2
and 3 up to 2004
190m3
sediment deposited in
the pools
Conventional EDM
survey
Roughly matches the 2 x 80m3 removed from
mine slopes
TLS - bridges
Ulley Dam – Emergency monitoring
• Used to remotely monitor the dam face during a
failure event (movement above 2mm would be
detected)
• Also used to measure water surface area for draw-
down calculations
Valley Tidal Doors – Asset Measurement
• Used to produce digital document of a historical asset and a wider
DEM and bare-earth DTM.
Valley tidal Doors
Practical Considerations:
Weather and Nature
Single Scan Truecolour (high resolution)
Fog
Curious Animals
Practical Considerations: Water
Scan direction
Water surface
(mirror-like)
reflection. NO
DATA
RETURN!
Diffuse reflection from valley side
Practical Considerations: Water
3D Model: 3 scans (high resolution)
Scan direction
Water surface
(mirror-like)
reflection
Diffuse reflection from valley side
Return to scanner
Practical Considerations: Water
3D Model: 3 scans (high resolution)
Scan direction
Incorrectly located
coordinate points
•This study utilises terrestrial LiDAR data to map water surface
character based on the local standard deviation of the laser returns.
•A revised biotope unit classification is proposed and tested using
similar data from an upland river in the UK.
Measuring Water Surface variations
Study Aims and Objectives
LMSZ210 – Older Model Scanner
360deg horizontal
90deg vertical
5mm accuracy
0.0025deg angular resolution
8000-12000 points are acquired/second
350m radial range
Non destructive
Rapid
Study Rivers
River Wharfe
River Skirfare
River South Tyne
Data Collection 1
•Biotope units were visually identified by the survey team and mapped
using theodolite survey
•Retro reflectors mapped using theodolite survey
•Sites scanned using TLS
Data Collection 2
•Automatic retro-reflector recognition and scan registration in RiScan Pro™
•Data captured inside the wetted perimeter of the channel were extracted
manually
•Data exported as ASCII files for input and analysis using the SURFER™
surface mapping software
Data Analysis
•The local standard deviation of the data were computed using a 0.2 m radius
moving window
•Data were gridded at 0.04 m so as to capture the smallest biotope unit seen
at the study sites
•Local standard deviation values at each of the measured biotope locations
were then extracted from the grids using the residual function in SURFER™
•Local standard deviation values interrogated at each known biotope location
•Statistical properties of each biotope determined
Results: Temporal variation
•Temporal data from the River Skirfair at Arncliffe reveal that the median
surface roughness values for the recorded biotopes are generally
consistent between scans.
•Suggests that local surface standard deviation is a robust measure
recording consistent values at the same biotope locations
•The surface expression of each biotope is subject to minimal temporal
variation and should therefore be definable.
Results: Spatial consistency
•Between river roughness values show good consistency particularly
around the median values recorded for each river.
•These data allow physical surface roughness limits to be defined for
each biotope that can then be used to map the biotope distribution along
scanned river reaches.
Results: Spatial consistency
•Clear from the data that the local roughness variability
shows considerable overlap between biotope units
suggesting that the present classifications are overly
complex
Pool 0 0.005
Accelerating flow 0.012 0.016
Glide 0.016 0.02
Deadwater 0.018 0.02
Chute 0.019 0.023
Eddy 0.023 0.025
Run 0.023 0.025
Riffle 0.025 0.03
Cascade 0.035 0.046
Boil 0.036 0.039
Unbroken standing wave 0.046 0.05
Broken standing wave 0.05 0.09
•Min stdev Max stdev
Results: Spatial consistency
•Units may be usefully amalgamated to
form a broader set of flow types.
Pools and deadwater zones
Accelerating flow areas
Riffles runs chutes and glides
Rapids cascades
Boils and Waterfalls
•Five roughness sub-divisions are
proposed, amalgamating:
Results: Typology validation
Unit descriptor
frequency biotope successfully
classified frequency amalgamated biotope successfully classified
Run 0.00 0.90
Glide 0.14 0.75
Chute 0.20 0.59
Rapid 0.38 1.00
Riffle 0.25 0.55
Deadwater 0.71 0.71
Pool 1.00 1.00
Experiment - Conclusions
Despite issues of signal loss due to absorption and transmission
through the water the reflected signal generates an extremely detailed
and accurate objective map of the water surface roughness which may
be compared to known biotope locations as defined by visual
identification in the field.
Biotope surface roughness delineation has proved problematic using
the current set of biotopes found in the literature due to large within
biotope surface variation. This suggests an overly complex set of
biotope classifications.
The results also suggest that present biotope classifications are overly
complex and could reasonably be reduced to three or four
amalgamated units.
Where next…………?
• Sediment size measurement
R2 = 0.9653
y = 1.0876x - 3.5613
R2 = 0.9711
R2 = 0.9202
0
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0 10 20 30 40 50
a
b
c
Linear (a)
Linear (c)
Linear (b)
10
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1000
0 20 40 60 80 100
% excedence
Sed
imen
t siz
e (
mm
)
wolman
laser all
Problems with TLS and Fitness-for-purpose
• An inappropriate measurement technique
when:
• mm or sub-mm accuracy is required on key
points.
• Only one distance measurement is needed
• No appropriate vantage is available
• The measurement area exceeds a practical
limit (around 10km2)
• Water is present (not always a problem)
• Point interpolation error is accepted
Key considerations
• TLS is not the answer to all measurement problems
• When it is the appropriate it is extremely useful• Try to consider different types of TLS
• Cost reduction and “added value” in Arup?
• It can reduce risk and thus benefit H&S
• The technology is improving
• Could one survey provide many different types of
information? (dimensions, change, hydraulics, habitat, roughness,
colour, reflectivity, sediment size, vegetation characteristics)
Key Considerations
• An ideal technique when:
• Good accuracy and point resolution is required
over medium to large areas
• (<+/-1cm error over 10m2 up to 10s of km2)
• There is no access but good vantage (non-contact
tool)
• The data are required for multiple purposes
• Measurement and monitoring, GIS, Virtual
Reality
• The scene of measurement is complex and
includes features such as vegetation, overhangs,
wells and bridges.
TLS – Warnings and Benefits
• What are the implications / uses of a survey?
• Control?
• State expected data character, nature and utility early.
• Sometimes overboard and can be over sold.
• It can be “the ultimate” data set.
• Allows errors to be tracked and understood.
• Can measure more than just topography.
• Great in Emergencies.
• Its getting better …..
Questions?
Thank you !!
