Point Clouds: Big Data, Simple Solutions Mike Lane
Light Detection and Ranging
Point Cloud is the Third Type of Data Vector Point Measurements and Contours Sparse, highly irregularly spaced X,Y,Z values Raster Pixel represents elevation value for X,Y location Dense, regularly spaced Z values Point Cloud Collection of points with attributes. Dense, semi-regularly spaced X,Y,Z, Attribute values. 3
What is a Point Cloud? Two different types of point clouds: Photogrammetric point clouds Derived from stereo imagery LiDAR point clouds Captured by LiDAR equipment 9/15/2013 2012 Intergraph Corporation 4
Point Cloud from Photogrammetry
Terrestrial LiDAR from sensor 9/15/2013 2012 Intergraph Corporation 6
Let s get straight to the point
Vegetation Mapping USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Hydrology Erosion Studies
Hydrology Flood plain mapping and simulation
Urban modeling Photorealistic rendering for visualization
Transportation Highway corridor mapping
Mining and Construction Accurate volumetric calculations Volume removed from mine Measure tailings
Solutions for: Emergency Response Local Government Utilities
Emergency response Problem: Mitigate the effects of disaster like floods or earthquakes. Solution: Accurate surface model to help find areas which will be inundated by flood water, or where buildings have collapsed. Benefit: Safer working conditions for 1 st responders. Better Planning before disaster strikes
Disaster Recovery 16
Disaster response www.news.com.au www.news.com.au www.earthquake-report.com www.theatlantic.com
Disaster response
Local Government Problem: Managing and understanding the jurisdiction. Solution: Identify dangerous intersections and where to place cameras. Discover taxable home additions. Benefit: Safer cities More tax revenue
Non classified point cloud
Point Cloud Classification for Rooftop Extraction
Convert to Vector Point Cloud Encode Classify Filter Vector
Image + Point Cloud: Object Based Feature Extraction 24
Point Cloud-assisted rooftop extraction 25
Change Detection
Locate increase or decrease in structures
Change Detection Results: Increase
Utilities Problem: Vegetation encroachment on power lines Solution: Find, measure and tag possible encroachments. Benefit: Saves costly time in the field. Fulfills as-built requirements Provide valuable data about line capacity.
Corridor Mapping and Vegetation Encroachment 30
Point Clouds perspectives 2D View Profile Views 3D View Side View Front View 9/15/2013 2012 Intergraph Corporation 31
Point Clouds in Utilities Profile Views 9/15/2013 2012 Intergraph Corporation 32
Point Cloud Data Management 9/15/2013 2012 Intergraph Corporation 33
Clip Zip Ship Native Point Clouds from Apollo to Desktop Applications Clip, Zip and Ship subsets of LAS-formatted point cloud data Select clip area Output options: Select classifications Filter by return value Output to LAS Automatic mosaic of results Clipped output LAS Region to subset 2012 Intergraph Corporation 34
Georgia Power and ERDAS APOLLO Background 2 nd largest land owner in the state of Georgia Owns TBs of historical imagery and survey data Moving forward, must comply with NERC will be collecting repeated LIDAR surveys Problem Georgia Power Land Department supervisors need to catalog and retrieve imagery, GIS and LIDAR data. TBs of data not being managed effectively New LIDAR data coming in TB s of historical Imagery and survey data Need to support almost 250 concurrent users
THE SITUATION Land Management Distribution www. www.slashbuster.com www.tutorvista.com Customer Care & Support Power Management www.voltswagon-commercial.com.au www.siemens.com.au
Data in Silos Data in silos inhibits communication and sharing of geospatial data and functionality
Think outside the box Blog.kace.com
Why use LiDAR in Utilities? BLACKOUT - August 2003 in US and Canada 50 million people affected; cost = $10 billion+ Reason Energy co. "failed to adequately manage tree growth in its transmission rights-of-way". North American Electric Reliability Corporation (NERC) Adopts management standards aimed at reducing outages caused by vegetation Failure to comply results in penalty (i.e. fines $$) RESULT for Power Companies Survey hundreds of thousands of miles of electric transmission lines; repeat surveys required Use LIDAR and imagery to understand: Vegetation clearance and encroachments Growth patterns Terrain features Span lengths Sag distances Facilities information (i.e. location and size of towers, lines, buildings, roads, right-of-way)
Georgia Power Benefits from using ERDAS APOLLO Geospatial analysts spend less time managing data each day and more time on solving GIS problems. Long term: Greater use of expensive data collections because of easier access and dissemination.
Big Data, Simple Solutions
Questions?