workshop bogota tls

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,

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

• 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

1000km

1 day 1 year 1000 years 10000 years1 month

Increasing Time Scale

Spatial & Temporal Change

1000km

Photogrametry

Theodolite

Aerial Photo's

AirborneLIDAR

Spatial & Temporal Survey

Limits

1000km

Photogrametry

Theodolite

Aerial Photo's

AirborneLIDAR

Spatial & Temporal Survey

Limits

NO DATA

1000km

Photogrametry

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

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

-1 -0.5 0 0.5 1

Rock Gaps

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

• 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

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

2nd-3rd 3rd-4th 4th-5th 5th-7th 7th-9th 9th-10th

Date (June 04)

Deposition

Erosion

Peak discharge

-0.1 -0 -0 0

0.08 0.1

Dartford Creek – morphological monitoring

The Dartford Creek - Location

The Dartford Creek - Kent

The Dartford

BarrierBrushwood

Rig and Plant

Sheet Piling

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

Dartford CreekDartford Creek

Raw point cloud

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

Area of Slumping

Area of moderate erosion

Dartford Creek – DTM subtraction

XSection9

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)

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

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

Positive Volume

[Deposition]:

Negative Volume

[Erosion]:

Net Volume [Cut-

Fill]:

- 4.22

Slope Change Volume

Positive Volume

[Deposition]:

Negative Volume

[Erosion]:

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

0 100 200 300 400 500 600 700 800 900 1000

Flood shear Fine sed threshold Coarse sed threshold

74 cross-

sections

Deposition downstream

0.1 1 10 100 1000

Clast size (mm)

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

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)

Curious Animals

Practical Considerations: Water

Scan direction

Water surface

(mirror-like)

reflection. NO

RETURN!

Diffuse reflection from valley side

3D Model: 3 scans (high resolution)

Scan direction

Water surface

(mirror-like)

reflection

Diffuse reflection from valley side

Return to scanner

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

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.

•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

•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 10 20 30 40 50

Linear (a)

Linear (c)

Linear (b)

0 20 40 60 80 100

% excedence

wolman

laser all

Problems with TLS and Fitness-for-purpose

• An inappropriate measurement technique

• 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

• 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 !!

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