The document discusses advancements in visualizing remotely sensed 3D data. It describes historical methods for managing large volumes of 3D point data, such as LiDAR and photogrammetry data, which included rasterizing, loading entirely into memory, decimation, and streaming from disk. A new advanced spatial indexing solution is introduced that allows for real-time rendering of massive 3D point clouds with unlimited size, compressed data, and low computer resource usage while preserving the full resolution and detail of the original data.

2. Matt Bethel
Advancements In Visualization Of
Remotely Sensed 3D Data

3. Agenda
• Review of 3D point data sources
• Historical methods of managing this data
• Introduction to a revolutionary and disruptive
technology for accessing and rendering unlimited
amounts of 3D data

4. 3D Point Data Sources
• ATE
• SAR / IFSAR
• LiDAR / LADAR
– Airborne
– Mobile
– Terrestrial
– Underwater
– Autonomously collected
• Newer processes
– SFM (computer vision)
– SGM (photogrammetry)

5. 3D Point Data Sources
• ATE
• SAR / IFSAR
• LiDAR / LADAR
– Airborne
– Mobile
– Terrestrial
– Underwater
– Autonomously collected
• Newer processes
– SFM (computer vision)
– SGM (photogrammetry)

6. 3D Point Data Sources
• ATE
• SAR / IFSAR
• LiDAR / LADAR
– Airborne
– Mobile
– Terrestrial
– Underwater
– Autonomously collected
• Newer processes
– SFM (computer vision)
– SGM (photogrammetry)

7. 3D Point Data Sources
• ATE
• SAR / IFSAR
• LiDAR / LADAR
– Airborne
– Mobile
– Terrestrial
– Underwater
– Autonomously collected
• Newer processes
– SFM (computer vision)
– SGM (photogrammetry)

8. Historical Point Data Handling Methods
• Rasterizing elevation data
– Works well in open land
cover
– Cannot represent
multiple height features
– Does not work with
FOPEN data
• Loading points into
memory (RAM)
• Point decimation
• Streaming from disc
• Vectorizing features

9. Historical Point Data Handling Methods
• Rasterizing elevation data
– Works well in open land
cover
– Cannot represent
multiple height features
– Does not work with
FOPEN data
• Loading points into
memory (RAM)
• Point decimation
• Streaming from disc
• Vectorizing features

10. Advanced Spatial Indexing Solution
• Real time 3D data rendering at full resolution and detail
• Massive data (density, extent, or both) is now accessible
and usable
• Compressed data size
• Data loads in 1 second no matter the size
• Unlimited amount of data to manage, load, display, etc.
• Low computer resource requirements
• Preserves true 3D data, not derivative products
• Capable of streaming 3D data across secured network or
internet
• Cost savings - make use of data that already exists
• Centralized data storage
• Version control
• Opportunity for 3D imagery and 3D models

11. Advanced Spatial Indexing Solution
• Real time 3D data rendering at full resolution and detail
• Massive data (density, extent, or both) is now accessible
and usable
• Compressed data size
• Data loads in 1 second no matter the size
• Unlimited amount of data to manage, load, display, etc.
• Low computer resource requirements
• Preserves true 3D data, not derivative products
• Capable of streaming 3D data across secured network or
internet
• Cost savings - make use of data that already exists
• Centralized data storage
• Version control
• Opportunity for 3D imagery and 3D models

12. Advanced Spatial Indexing Solution
• Real time 3D data rendering at full resolution and detail
• Massive data (density, extent, or both) is now accessible
and usable
• Compressed data size
• Data loads in 1 second no matter the size
• Unlimited amount of data to manage, load, display, etc.
• Low computer resource requirements
• Preserves true 3D data, not derivative products
• Capable of streaming 3D data across secured network or
internet
• Cost savings - make use of data that already exists
• Centralized data storage
• Version control
• Opportunity for 3D imagery and 3D models

13. Thank you
Matt Bethel
Director of Technology
Merrick & Company
matt.bethel@merrick.com
303-353-3662
http://www.merrick.com/Geospatial