Workshop bogota tls

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Workshop bogota tls

  1. 1. Terrestrial Laser Scanning in River Environments Dr David Hetherington Ove Arup and Partners, Newcastle upon Tyne, UK. Tuesday the 1st June 2010 Universidad Javeriana, Bogota, Colombia Laser Scanner Laser Scanner Photograph – River Wharfe Laser Scan Model – River Wharfe
  2. 2. 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
  3. 3. What is good quality spatial data?...
  4. 4. 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
  5. 5. Interpolation – various methods (From Keckler 2001)
  6. 6. Survey Methods: Thedolite/GPS Aerial Photo 2 people x 3 days = 4000 data points
  7. 7. Survey inaccuracy: Form Interpolation
  8. 8. 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)
  9. 9. Example complex (yet high quality) input spatial data – Terrestrial lidar
  10. 10. 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
  11. 11. 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
  12. 12. Laser measurement theory - REFLECTIVITY • 3 types of light reflection: Diffuse Mirror-like Retro (most surfaces) (Glass, mirrors flat (roadsigns, bike water surfaces) reflectors, strips on high-vis jackets)
  13. 13. 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.
  14. 14. 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
  15. 15. 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.
  16. 16. 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).
  17. 17. Riegl LMSZ420 laser scanner
  18. 18. Spatial & Temporal Change 1000km Rates River scale slope adjustment Reach scale Increasing Spatial Scale slope adjustment 1km Planform change Barform change 1m Cross-section adjustment Fine sediment movement 1mm 1 day 1 month 1 year 1000 years 10000 years Increasing Time Scale
  19. 19. Spatial & Temporal Survey 1000km Limits Aerial Photo's Airborne Increasing Spatial Scale LIDAR GPS 1km Theodolite 1m Photogrametry 1mm 1 day 1 month 1 year 1000 years 10000 years Increasing Time Scale
  20. 20. Spatial & Temporal Survey 1000km Limits Aerial Photo's Airborne Increasing Spatial Scale LIDAR GPS 1km Theodolite 1m Photogrametry NO DATA 1mm 1 day 1 month 1 year 1000 years 10000 years Increasing Time Scale
  21. 21. 1000km Lidar limits Aerial Photo's Airborne Increasing Spatial Scale LIDAR GPS 1km Theodolite 1m Terrestrial LIDAR Photogrametry NO DATA 1mm 1 day 1 month 1 year 1000 years 10000 years Increasing Time Scale
  22. 22. Multiple scans and overlap Multiple scans from various perspectives reduce “shadow”
  23. 23. 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.
  24. 24. Example laser scan model – River Wharfe • 25 High-Resolution Scans • Scans Merged to within <5mm • 21 million Data points • 1 point per cm2
  25. 25. Error Measurement On The Wharfe 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 b 15 10 Rock Gaps 5 0 -1 -0.5 0 0.5 1 c 20 15 10 5 Grass 0 -1 -0.5 0 0.5 1
  26. 26. Gravel-scale Measurement 8x8m grid in centre of bar was the area of focus
  27. 27. 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.
  28. 28. Example results – Gravel scale measurement Scan height = 1.5m Scan amount = 1 Mismeasurement errors Scan locations = n/a All Highs Lows Scan distance = 10m Processing = none Min = 0.000001 0.000001 0.00007 Scan resolution = max Max = 0.121 0.121 0.114 Repeat scans = no Merging = reflectors only Mean = 0.0243 0.0146 0.0339
  29. 29. Example results – Gravel scale Measurement Mismeasurement errors Scan height = 1.9m Scan amount = 2 All Highs Lows Scan locations = opposite Min = 0.00002 0.00002 0.00016 Scan distance = 20m Processing = default OCTREE Max = 0.1266 0.1266 0.1124 Scan resolution = max Mean = 0.0270 0.0205 0.03359 Repeat scans = no Merging = reflectors only
  30. 30. 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.
  31. 31. Arolla/Ferpecle Glacial Outwash Plain, Valais, Switzerland. Arolla 300m x 300m plain Ferpecle
  32. 32. Terrestrial lidar point cloud model Three Modelled Scans (out of twelve available)
  33. 33. Small-Scale Morphological change • Sub-bar level change • bank collapse and deposition
  34. 34. Outwash Plain Reach-Scale Morphology
  35. 35. Total sediment budget and model error Deposition Erosion 180 Peak discharge 0.9 Sediment volume (m 3) 160 0.8 Discharge (m3s- 1) 140 0.7 120 0.6 100 0.5 80 0.4 60 0.3 40 0.2 20 0.1 0 0.0 2nd-3rd 3rd-4th 4th-5th 5th-7th 7th-9th 9th-10th Date (June 04) 30 25 20 frequency 15 10 5 0 0 -0 -0 -0.1 -0.1 -0.1 0.02 0.04 0.06 0.08 0.1 m
  36. 36. Dartford Creek – morphological monitoring
  37. 37. The Dartford Creek - Location Site
  38. 38. The Dartford Creek - Kent
  39. 39. The Dartford Creek - Kent Sheet Piling Rig and Plant The Dartford Barrier Brushwood Barge
  40. 40. The Dartford Creek - Kent
  41. 41. The Dartford Creek - Kent
  42. 42. The Dartford Creek - Kent
  43. 43. The Dartford Creek - Kent
  44. 44. Scope of work • To describe, assess and understand the geomorphological system • To monitor the site and habitat geomorphology during and post construction 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
  45. 45. 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..?
  46. 46. 4) Dartford Creek
  47. 47. Dartford Creek Raw point cloud model
  48. 48. Dartford Creek Raw point cloud model Survey subtraction
  49. 49. Dartford Creek Compound slope- elevation Survey subtraction
  50. 50. Dartford Creek Compound slope- elevation Survey subtraction
  51. 51. Dartford Creek – 3D model, planform view Single Scan
  52. 52. Dartford Creek – Model detail
  53. 53. TLS data in GIS Compound slope/elevation map Regionalised slope map
  54. 54. First survey near to rig
  55. 55. Dartford Creek – Second Survey
  56. 56. Dartford Creek – Second Survey Area of Slumping Area of moderate erosion
  57. 57. Dartford Creek – DTM subtraction Area of erosion XSection9 5.00 Area of deposition 4.00 3.00 Elevation (m) 2.00 Aug06 Nov-06 1.00 0.00 -1.00 -2.00 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)
  58. 58. Digital Terrain Model Subtraction Elevation Change Sediment Budget
  59. 59. Nenthead Unstable Valley
  60. 60. 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
  61. 61. Reflector tie points Used for second survey modelling 7 reflectors used
  62. 62. Natural tie points Used for first survey modelling Easily Identifiable points
  63. 63. Slope Model
  64. 64. Slope Movement Erosion and Deposition Upstream stability and vegetation growth: Complicating Factor
  65. 65. Slope Erosion
  66. 66. Immediate Channel Change
  67. 67. Immediate channel deposition
  68. 68. Volumetric change Slope Change Volume Channel Change Volume (m3) (m3) Positive Volume 11.63 Positive Volume 29.10 [Deposition]: [Deposition]: Negative Volume 77.57 Negative Volume 33.32 [Erosion]: [Erosion]: Net Volume [Cut- - 75.94 Net Volume [Cut- - 4.22 Fill]: Fill]: • 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
  69. 69. 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
  70. 70. Engineering works model flood hydraulics 700 600 500 400 74 cross- 300 200 sections 100 0 0 100 200 300 400 500 600 700 800 900 1000 Flood shear Fine sed threshold Coarse sed threshold 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
  71. 71. Deposition downstream Exceedence percentage 120 100 80 60 40 20 0 0.1 1 10 100 1000 Clast size (mm) POOL 1 POOL 2 POOL 3 Coarse material in pool 1 Fining in downstream pools
  72. 72. Deposition downstream Conventional EDM survey 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 Roughly matches the 2 x 80m3 removed from mine slopes
  73. 73. TLS - bridges
  74. 74. 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
  75. 75. Valley Tidal Doors – Asset Measurement • Used to produce digital document of a historical asset and a wider DEM and bare-earth DTM.
  76. 76. Valley tidal Doors
  77. 77. Practical Considerations: Weather and Nature Curious Animals Single Scan Truecolour (high resolution) Fog
  78. 78. Practical Considerations: Water Scan direction Diffuse reflection from valley side Water surface (mirror-like) reflection. NO DATA RETURN!
  79. 79. Practical Considerations: Water Return to scanner Diffuse reflection from valley side Scan direction Water surface (mirror-like) reflection 3D Model: 3 scans (high resolution)
  80. 80. Practical Considerations: Water Scan direction Incorrectly located coordinate points 3D Model: 3 scans (high resolution)
  81. 81. 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 •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.
  82. 82. Study Rivers River South Tyne River Skirfare River Wharfe
  83. 83. 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
  84. 84. 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
  85. 85. 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
  86. 86. 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.
  87. 87. 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.
  88. 88. Results: Spatial consistency •Min stdev Max stdev 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 •Clear from the data that the local roughness variability shows considerable overlap between biotope units suggesting that the present classifications are overly complex
  89. 89. Results: Spatial consistency •Units may be usefully amalgamated to •Five roughness sub-divisions are form a broader set of flow types. proposed, amalgamating: Pools and deadwater zones Accelerating flow areas Riffles runs chutes and glides Rapids cascades Boils and Waterfalls
  90. 90. Results: Typology validation frequency biotope successfully Unit descriptor 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
  91. 91. 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.
  92. 92. Where next…………? • Sediment size measurement 160 140 a 120 2 R = 0.9653 b 100 c 80 2 Linear (a) R = 0.9202 60 Linear (c) 40 20 y = 1.0876x - 3.5613 Linear (b) R2 = 0.9711 0 0 10 20 30 40 50 1000 Sediment size (mm) wolman 100 laser all 10 0 20 40 60 80 100 % excedence
  93. 93. 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
  94. 94. 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)
  95. 95. 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.
  96. 96. 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 …..
  97. 97. Thank you !! Questions?

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