HYDROFEST 2005 CAPABILITIES OF A MODERN BATHYMETRIC LIDAR SYSTEM - THE SHOALS 1000T SYSTEM. Bill Gilmour Fugro Pelagos Inc, San Diego, CA, USA

HYDROFEST 2005 CAPABILITIES OF A MODERN BATHYMETRIC LIDAR SYSTEM - THE SHOALS 1000T SYSTEM Bill Gilmour Fugro Pelagos Inc, San Diego, CA, USA

ACKNOWLEDGEMENTS FUGRO PELAGOS INC. David Millar Carol Lockhart Dushan Arumugam OPTECH INTERNATIONAL INC. Grady Tuell JALBTCX Jeff Lillycrop NOAA

OUTLINE BACKGROUND INFORMATION SYSTEM SPECIFICATIONS DATA ACQUISITION DATA PROCESSING SYSTEM CALIBRATION SYSTEM ACCEPTANCE TESTING SAT s for Optech NOAA Seattle Tests IHO specifications Target Detection SYSTEM APPLICATIONS Hydrography River Surveys Coastal Zone Mapping LATEST DEVELOPMENTS LIDAR Pseudoreflectance Hyperspectral Data Fusion

BACKGROUND INFORMATION FUGRO PELAGOS INC. San Diego, California Anchorage, Alaska Kiln, Mississippi Honolulu, Hawaii

Providing Hydrographic Surveys in Alaska for NOAA Charting Since 1998

Collected Over Eight Billion Soundings in Five Years

Delivering Datasets In Support of Ecosystem-based Management

Current NOAA Charting Contract Awarded in 2005 at $50 Million over Five Years

Providing Airborne LIDAR Bathymetry Operational Support to USACE and NAVO Since 1994

Fugro ALB History Support of GFE USACE Contracts Fugro SHOALS-200 Operations 1992 1994 Commercial Services FPI SHOALS-400 Operations SHOALS-400 Retired CHARTS Operations FCI 1998 2001 2002 Feb-2003 Jul-2003 Aug-2003 Jul-2004 Subcontract LADS in AK Subcontract SHOALS in AK Team with Optech SHOALS-1000T Services SHOALS-1000T Ordered ALB Activities Consolidated FPI Jan-2005 Apr-2005 ALB Activities Consolidated SHOALS-1000T Delivery

SYSTEM SPECIFICATIONS SHOALS 1000T

Airborne LIDAR Bathymetry Offers Greater Production Rates than Multibeam Echosounder

ALB Technology The Basics 140 120 photoelectrons 100 80 60 40 20 0 1 21 41 61 81 101 121 141 161 181 time (ns) D Laser light source projects 2 beams onto spinning mirror Mirror rotates at a very fast rate and directs two beams per pulse to water surface Creates a swath of points within field of view Green beam penetrates water and detects seabed Infrared beam penetrates little: detects land and sea surface Red energy from Raman backscatter can also detect surface

Scan Patterns for Hydrographic Mode Altitude (m) Swath (m) Lateral Spot Spacing (m) Forward Spot Spacing (m) Flight Speed (knots) Scanner Cycle Rate (Hz) Area Coverage (nm 2 /hr) 400 60 2 2 124 16.0 4.0 300 60 2 2 124 15.9 4.0 400 130 3 3 127 10.9 8.9 300 125 3 3 128 11.0 8.7 400 215 4 4 126 8.1 14.7 300 165 4 4 162 10.5 14.5 400 230 5 5 180 9.2 22.4 200 150 100 50 0 1 IR Surface 51 101 151 70 60 50 40 30 20 10 0 Raman 1 26 51 76 160 140 120 100 80 60 40 20 0 APD Green 140 120 100 80 60 40 20 0 PMT Green 451 401 351 301 251 201 151 101 51 1 151 101 51 1

Evolution of Airborne LIDAR Bathymeters Evolution of the SHOALS Product Line from Optec Comparison Criteria SHOALS-200 SHOALS-400 SHOALS-1000T Scanning Frequency 200Hz 400Hz 1000Hz + 10kHz topo Power Requirements 150A @ 28VDC 120A @ 28VDC 60A @ 28VDC Weight 450kg 450kg 205kg Volume 1.5m³ 1.5m³ 0.5m³ Function Bathy Bathy Bathy / Topo / Imagery

SHOALS-1000T Has Multi-Sensor Capability 1kHz bathy mode and 10kHz topo mode Integrated digital camera

SHOALS-1000T Key Bathy Specifications Speed over ground Altitude above ground Sounding density Swath width 125-180 knots 300-400 m 2x2, 3x3, 4x4, 5x5 m 60-230 m Minimum depth 0.2m Maximum depth 50 m Depth accuracy IHO Order 1 (0.25m, 1σ) Horizontal accuracy IHO Order 1 (2.5 m, 1σ) Laser classification Class IV laser product (FDA CFR 21) Eyesafe altitude Power requirements 150m 60 A @ 28VDC

DATA ACQUISITION

SHOALS-1000T is the Smallest, Lightest Sensor Available

Offering a Completely Portable Solution Capable of mobilization on fixed or rotary wing aircraft Bell 206L King Air A90 Anywhere in the world

Water Clarity / Other Environmental Constraints Data collection and data quality impacted by the following: Weather Low clouds Rain Fog Water clarity Turbidity Surf zone Red Tide Algae bloom Aquatic vegetation

Ground Control System Software Modules MAPS Management And Planning Software Generate flight lines for a project Establish data collection attributes for these lines Allocate flight lines to a mission Search for holidays Unload x,y,z + meta-data DAViS Downloading, Automated processing and 3D Visualization Software Download data from airborne removable hard drives Auto process airborne collected data View, clean, and edit data in 3D via Fledermaus

MAPS Flight Line Planning

Operator Interface Display

GPS and Survey Support Complement Airborne Operations

Enhancing Data Collection and Processing with PPK GPS

DATA PROCESSING

DAViS Autoprocessing Display

Data Editing

Lake Ontario 07Jan03 0-35 m depth Visualizing Today s Data

SHOALS- 400 Attributes in CARIS

SHOALS Attributes in CARIS Link between HDCS Time Stamp and SHOALS Time Stamp Shows both Primary and Secondary Depth Shows Confidence value calculated in SHOALS system Soundings maintain their Kill, Keep or Swap attribute from the SHOALS system. These can be modified in CARIS. Wave form is viewable for every Sounding

Deliver Cleaned and Edited XYZ Point Data

Deliver Integrated Bathy and Topo DEMs

Deliver Contour and Cross Section Data

Deliver Color Coded and Sun-Illuminated Bathymetric Data

Deliver Digital Imagery

SHOALS-1000T Deliverables Orthophoto Mosaic Drape over DTM

Deliver Fly-Through Animations

SYSTEM CALIBRATION

Calibrations Laboratory Calibration System timing for bathy and topo systems Scanner scale and offset factors Downlook camera lens and radial distortion Hydro subsystem Angular calibration residual angular offsets resolved over several flightlines Residual vertical error - determine correct elevation by runway check Horizontal accuracy evaluated over a landmark feature Underwater vertical accuracy comparison against groundtruth data Topo subsystem Angular calibration - residual angular offsets resolved over several flightlines Vertical accuracy - comparison against groundtruth data Horizontal accuracy evaluated over a landmark feature Downlook Camera Boresight calibration points compared over reciprocal flightlines Data processing Calibration values saved in GCS parameter file

SYSTEM ACCEPTANCE TESTING SAT s for Optech NOAA Seattle Tests IHO specifications Target Detection ± ( b d) 2 2 a + IHO Order a b 1 0.5 0.013 2 1.0 0.023

How Did We Get Here? Teaming Agreement Signed 2 nd Group of Projects 1 st Group of Projects 3 rd System Tests Conducted 1 st System Tests Conducted 3 rd Group of Projects Corporate Approval 2 nd System Tests Conducted Letter of Intent Issued

System Acceptance Tests - Objectives Purpose: To confirm that the SHOALS-1000T (System 2) is functioning as designed and required to meet hydrographic charting requirements. Objectives: Verify proper functionality of hardware Verify proper functionality of software Verify proper functionality of data processing work flow Verify validity of topographic data collected Verify validity of bathymetric data collected Verify portability of the system Verify reliability of the system

1 st System Acceptance Tests Lake Ontario KGPS positioned LIDAR surface KGPS positione d MBES surface

1 st System Acceptance Test Results Day 1

1 st System Acceptance Test Results Day 2

Power Timing Test System Timing Error Discovered

Single Peaks Timing is Stable

Double Peaks Faulty Digitizer Board 1.9 ns Timing Error ~20 cm Depth Error

Timing Error was Intermittent Error distribution for a single cross check line

Distribution returns to normal Timing Error Corrected

2 nd System Acceptance Test Results Day 1

2 nd System Acceptance Test Results Day 2

3 rd System Acceptance Tests San Diego

3 rd System Acceptance Test Results - Ellipsoid

3 rd System Acceptance Test Results - Tides

NOAA Seattle Tests IHO Compliance SHILSHOLE TEST AREA NOAA surveyed with Reson SeaBat 8101 (2001) Surveyed previously by FPI using: LADS MkII (2001) SHOALS- 400 (2002)

DATA ACQUISITION Multiple Flights / Multiple Days Multiple Laser Spot Spacings Each Spot Spacing flown more than twice 200% Coverage Two Cross Lines at 2x2m and 4x4m Laser Spot Spacing (m) Altitude (m) Speed (knots) Swath 2 x 2 300 124 60 3 x 3 300 128 125 4 x 4 300 162 165 5.0 x 3.8 300 180 174

SURVEY AREA

PROCESSING Processing followed 2 methods: 1. Real-time DGPS Position & NOS Preliminary Observed Tides from Seattle (9447130) 2. Post Processed KGPS in NAD83. Geoid03 transform to NAVD88 elevations. Offset 0.715m to MLLW NAD83 Geoid03 Height NAVD88 MLLW 0.715m at NOS Gauge 9447130

IHO TESTS - OVERVIEW Three separate comparisons conducted: 1. LIDAR X-Line : DTM of LIDAR Survey Lines X Line over MBES Reference Surface X Line run up Channel 2. LIDAR X-Line : DTM of MBES Reference Surface 3. All LIDAR Soundings : DTM of MBES Reference Surface

LIDAR X Line : DTM of LIDAR Survey Lines X-Line Over MBES Surface Positioning Survey Spot Spacing (m) DTM Grid Size (m) Cross Line Spot Spacing (m) No. of Samples Mean Diff (m) QC Results St Dev of Diff % Pass IHO Order 1 KGPS 2x2 2 2x2 15007-0.006 0.128 100% KGPS 3x3 3 2x2 12297 0.080 0.119 100% KGPS 4x4 4 4x4 9487 0.017 0.125 99% KGPS 5x3.8 5 4x4 8794-0.011 0.126 99% DGPS & Tides 2x2 2 2x2 13104-0.031 0.112 100% DGPS & Tides 3x3 3 2x2 10805 0.019 0.115 99% DGPS & Tides 4x4 4 4x4 6541-0.032 0.117 99% DGPS & Tides 5x3.8 5 4x4 6360-0.085 0.120 99%

LIDAR X Line : DTM of LIDAR Survey Lines X-Line Over Channel QC Results Positioning Survey Spot Spacing (m) DTM Grid Size (m) Cross Line Spot Spacing (m) No. of Samples Mean Diff (m) St Dev of Diff % Pass IHO Order 1 KGPS 2x2 2 2x2 30922-0.099 0.193 97% KGPS 3x3 3 2x2 27895-0.083 0.227 95% KGPS 4x4 4 4x4 20484-0.043 0.449 83% KGPS 5x3.8 5 4x4 17334-0.057 0.547 78% DGPS & Tides 2x2 2 2x2 31617-0.014 0.179 98% DGPS & Tides 3x3 3 2x2 29991-0.077 0.232 95% DGPS & Tides 4x4 4 4x4 23188-0.030 0.373 86% DGPS & Tides 5x3.8 5 4x4 18140-0.044 0.499 79%

LIDAR X Line : DTM of LIDAR Survey Lines Grid of Differences between Survey Lines and Cross Lines over Channel Red = Fail at IHO 1 Blue = Pass IHO1

LIDAR X Line : DTM of LIDAR Survey Lines 1. LIDAR Data Internally Consistent for both KGPS and DGPS/Tide Methods 2. Need to be careful where comparison is done

LIDAR X-Line : DTM of MBES Surface MBES Reference Surface N 300 m B O C G F 12 to 30m WD 3.1 Slope J K D E H A L M N 3.1 o I 270 m DTM = 1m Weighting Diameter = 1

LIDAR X-Line : DTM of MBES Surface No significant variations between Spot Spacings No significant difference between KGPS & DGPS Overall Results No. of Samples Mean Difference (m) St Dev of Difference % Pass IHO Order 1 KGPS with Wreck 4125 0.663 2.063 88% KGPS without Wreck 3624 0.036 0.193 98% DGPS/Tides with Wreck 3712 0.658 2.228 89% DGPS/Tides without Wreck 3302 0.004 0.339 98%

All LIDAR Soundings : DTM of MBES Surface No significant variations between Spot Spacings No significant difference between KGPS & DGPS Overall Results No. of Samples Mean Difference (m) St Dev of Difference % Pass IHO Order 1 KGPS with Wreck 24169 0.362 1.431 93% KGPS without Wreck 22635 0.078 0.202 98% DGPS/Tides with Wreck 28000 0.352 1.486 94% DGPS/Tides without Wreck 26459 0.070 0.189 98%

All LIDAR Soundings : DTM of MBES Surface LIDAR Data Passes IHO Order 1 Depth Accuracy

Target Detection Only shallower targets seen due to water clarity 300 m B O Inspected using KGPS dataset C J K G D F E A M N 4x4 m 2x2m 3.1 o H I L 270 m Compared by measuring height above surrounding seafloor remove any bias in data from analysis

Target Detection Multibeam LIDAR - 4x4 ALL LIDAR - 2x2 ALL Size (m) Surrounding Water Depth (m) Height Above Seafloor (m) Height Above Seafloor (m) Height Above Seafloor (m) A 56 x 4 17.9 8.9 9.7 9.6 D 7.6 20 3.2 Too Deep Too Deep H 4.2 17.6 0.8 0.6 0.9 I 2.2 15.7 1 1 0.7 L 2.8 15.3 0.3 0.5 0.5 M 10.2 15.3 0.7 0.8 0.8 N 6.6 14.7 0.7 0.7 0.8

Conclusions Achieve IHO Order 1 depth accuracy above 95% confidence SHOALS-1000T capable of detecting targets within the abilities of LIDAR but not guaranteed with a 4x4m spot spacing LIDAR technology does not have the same accuracy as MBES when finding least depths on sharp targets, due to footprint size Fugro Pelagos & SHOALS-1000T is able to reach required standards for hydrographic surveys

SYSTEM APPLICATIONS Hydrography River Surveys Coastal Zone Mapping

Airborne LIDAR Bathymetry combined with Multibeam Bathymetry for Hydrographic Charting

Smooth Sheet

Sitka Air Photo Ortho Mosaic

Belknap

Drape Over DEM

Elimination of Shallow Water Boat Work Reduces Time, Cost and Safety Risk

Shoreline Correlator

ALB Markets Ports & Harbor Surveys

ALB Markets Shoreline Mapping

ALB Markets Rivers, Lakes, Canals and Inland Waterways

Grand Canyon

Trinity River

Yakima River Kittitas Reach

COASTAL ZONE MAPPING - SANDAG Project IMAGERY LIDAR Bathymetry Multibeam Echosounder Acoustics Digital Multispectral Photography Multibeam Backscatter Acoustics WATER DEPTH

Integrated LIDAR Bathymetry and Multibeam Echosounder Data Acoustic Multibeam LIDAR Bathymetry

Integrated Digital MultiSpectral Photography and Multibeam Echosounder Backscatter Images

ArcGIS example - Interpretation

GIS Data from the SANDAG Project Now Available Online http://sccoos.ucsd.edu/nearshore/

LATEST DEVELOPMENTS LIDAR Pseudoreflectance Hyperspectral Data Fusion

SHOALS-1000T Waveforms Permit Seabed Imaging 140 120 100 80 60 40 20 0 bottom peak signal 151 101 51 1

LIDAR Pseudoreflectance Seabed Imagery

SHOALS-1000T Offers Sensor Fusion Developments Images courtesy of Optech International K 53 4 ρ W 534 ρ B 53 4 CASI ρ B 534

Seafloor reflectance for each channel of the passive hyperspectral data Images courtesy of Optech International