Airborne LIDAR Mapping Technology

CRSS/ASPRS 2007 Specialty Conference

October 31, 2007

Flight Planning

Flight Control

Position and Attitude System

Sensor Mount

ALS50

ALS CM

ADS SH52

RCD105

ADS SH51

2

LIDAR workflowsfor DEM data production

Leica focus

Sensor performance and data acquisition productivity

GNSS/IMU workflow

GrafNav

IPAS Pro

Point cloud generation

ALS Post Processor

Third party developer focus

Editing and project management productivity

Filtering/editing/QA:

TerraScan/TerraModeler/TerraMatch

VLS LIDAR Analyst

QCoherent LP360

Merrick MARS

Tiltan TLiD

Applied Imagery Quick Time Modeler / Quick Time Reader

LIDAR project management

GeoCUE

3

LIDAR workflowshigh speed point cloud generation

Processing Activity Remarks

Processing Time per Flight Hour @

150 kHz PRF

Time (sec) Ratio

IPAS GNSS/IMU Processing - Extraction

Extraction of files from mission drive; 1 hour 20 minutes IPAS "ON" time consisting of 1 hour airborne plus 10 minutes static occupation at beginning and end of flight

12 0.003

IPAS GNSS/IMU Processing - DGNSS Proc. using GrafNav

Formatting data from base station and airborne IPAS GNSS into GrafNav format

180 0.050

IPAS GNSS/IMU Processing - GNSS/IMU Proc. (IPAS Pro)

Integration of processed DGNSS position data and IMU data

68 0.019

IPAS GNSS/IMU Processing - Data Review

Checking position plots and forward/reverse difference plots for proper processing and accuracy

300 0.083

Subtotal - GNSS/IMU Processing 560 0.156

Point Cloud GenerationAssumes 150 kHz laser pulse rate for one hour "on-line" time and 7.8% multiple returns (i.e., average 162 kHz return rate)

4204 1.168

Subtotal - Expected average processing time for 1 flight hour (raw data to point cloud) 4764 1.323

Note: based on processing using workstation equipped with Intel Xeon 5150 @ 2.66 GHz, 3 GB RAM

4

Sample LIDAR-derived DEM data productssafety

Disaster prevention / disaster monitoring

Forest fire fuels assessment

5

Sample LIDAR-derived DEM data productssecurity

Defense

Supply route monitoring

Spot reconnaissance

Base mapping

Homeland security

Border monitoring

Urban event risk assessment

Law enforcement

Covert activity detection

6

Sample LIDAR-derived DEM data productsenvironment

Coastal survey

Watershed management

Flood zones

Erosion

Forest management

Tree health

Biometric data

Forest inventory

Development impact / change detection

Image courtesy of Watershed Sciences

7

Sample LIDAR-derived DEM data productsfused data for multiple applications

Typical sensors co-collecting with ALS DEM data

Medium-format RGB

Medium-format CIR

Thermal imagery

Hyperspectral imagery

Auxiliary sensors collect:

Additional spectral regions

High definition planimetric data

8

Future development in LIDAR-derived DEM workflowsmarket requirements, paths for 3rd-party developers

Speed – but can be overcome with more CPUs

Black box – minimizing human interaction, especially during the filtering and editing stages; possible impact of Full Waveform Digitizing (FWD) LIDAR data on accuracy and ability to filter data

Multi-sensor automation - easier fusion from dissimilar sensors – airborne LIDAR + terrestrial LIDAR, LIDAR + airborne (Vis or NIR) imager, LIDAR + thermal imagery

Auto QC – automating the quantitative measurement of output data quality

9

What’s newadditional milestones since ASPRS annual meeting

Huge projects being undertaken w/ MPiA systems (Example – NWG has collected 315,000 km², 835 aircraft hours, 1 point / m², 0 sensor problems to date on 750,000 km² collection)

Number of new system deliveries/demos for high altitude use @ 4500 m – 6000 m AGL

Hexagon acquires NovAtel

Participation in large-scale defense exercises

Customer support staff increased to 30 staff

4500 m AGL, MPiA, 66º FOV, 1.5 m avg. post spcng

Image courtesy of North West Geomatics

Thank you!visit us in our booth

Doug Flint

doug.flint@leicaus.com

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