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 workflows for 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 workflows high speed point cloud generation Processing ActivityRemarks Processing Time per Flight 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 IPAS GNSS/IMU Processing - DGNSS Proc. using GrafNav Formatting data from base station and airborne IPAS GNSS into GrafNav format IPAS GNSS/IMU Processing - GNSS/IMU Proc. (IPAS Pro) Integration of processed DGNSS position data and IMU data IPAS GNSS/IMU Processing - Data Review Checking position plots and forward/reverse difference plots for proper processing and accuracy Subtotal - GNSS/IMU Processing Point Cloud Generation Assumes 150 kHz laser pulse rate for one hour "on-line" time and 7.8% multiple returns (i.e., average 162 kHz return rate) Subtotal - Expected average processing time for 1 flight hour (raw data to point cloud) Note: based on processing using workstation equipped with Intel Xeon 2.66 GHz, 3 GB RAM

4 Sample LIDAR-derived DEM data products safety Disaster prevention / disaster monitoring Forest fire fuels assessment

5 Sample LIDAR-derived DEM data products security 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 products environment 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 products fused 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 workflows market requirements, paths for 3 rd -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 new additional 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 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

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