hawaii pacific gis conference 2012: lidar for intrastructure and terrian mapping - lidar data...
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LiDAR Data Management and Exploitation Joe Bob Penor
Staff Scientist
GIS Product Specialist: Geospatial Operations
Overview
How is LiDAR data useful in Disaster Management
Acquiring Point Data – Traditional Airborne Capture
– Points from Pixel correlation
– Pro’s and Con’s of each collection
Managing and Deliver your LiDAR Data
LiDAR Data Exploitation
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Disaster Happens
3
How is LiDAR useful
Prevention and mitigation
Search and Rescue
Insurance assessment
Restoration
At Risk Analysis (3D Visualization)
5 3/14/2012 GeoMedia 3D
Potential Slide Areas Historical Flood Zones
Potential Water Extents
Capture
What if Pre-date LiDAR does not exist?
Pixel correlation
The result….
…a very dense color encoded point cloud.
Aerial vs. Pixel Correlation
Aerial LiDAR Pixel Correlation
Typical high point density
(points/m2)
25
400
Typical point accuracy
(sigma x, y in m)
0.15
0.025
Typical point accuracy
(sigma z in m)
0.050
0.075
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There is a little problem…
Distributed Processing
One Step further…Processing as a Service
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Turnkey Software-as-a-Service (SaaS) enablement tools that turns almost any
application into an instantly deployable software + infrastructure package that is
hosted, managed, and billed directly from their Cloud.
http://www.skygoneinc.com/
Other Considerations
• What point density is required?
• What accuracy is required?
• What types of surfaces are more important (e.g., vertical versus horizontal)?
• How quickly must the data be collected (e.g., hours versus days)?
• When can the data be collected (e.g., which season)?
• Is data collection at night an advantage (e.g., lower security risk, or avoiding air traffic near
major airports, less ‘clutter’)?
• What details are required (e.g., courtyards, roofs, tops of bridges, under bridges)?
• What type of vegetation cover exists and do you need to penetrate the vegetation?
• For Comparison, historical imagery may exist but LiDAR may not
Manage LiDAR in ERDAS APOLLO
Discover
Catalog
Edit Metadata
Visualize
Execute WPS models
CZS - Clip-zip-Ship
Export
Manage LiDAR in ERDAS APOLLO
ERDAS IMAGINE and LPS LiDAR Capabilities
Terrain Analysis and visualization (slope, Aspect, shading, viewshed, intervisibility)
Import / export, Merge, Split, Thin
Generate contours
Use in Ortho generation
Create LAS in eATE
Edit in Terrain Editor
3D visualization
Classification cue in ERDAS IMAGINE Objective
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Terrain Analysis and
visualization (slope, aspect,
shading, viewshed, etc.)
Import / export
Generate true vector
contours
Statistical Analysis
Advanced Interpolation,
including Kriging
Downhill flow and flow
concentration analysis
Classification
GeoMedia LiDAR Capabilities
Identifying change in Lidar Data
Point Cloud Tools
Conclusions
Point Clouds can be a useful tool in disaster management
– Prevention and mitigation
– Search and Rescue
– Insurance assessment
– Restoration
There are alternative methods to collect LiDAR data with pro’s and con’s
– Traditional airborne survey
– Pixel correlation from stereo imagery
Once you have LiDAR you need effective management and exploitation tools
LiDAR and Dam Analysis
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Thank you
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