advancements in visualization of remotely sensed 3d data

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2013* GEOINT Lightning Talk presentation given by Matt Bethel, Director of Technology for Merrick & Company's Geospatial Solutions team. Presentation given on Monday, April 14, 2014 at the Tampa Marriott Waterside Hotel in Tampa, Florida.

TRANSCRIPT

Page 1: Advancements In Visualization Of Remotely Sensed 3D Data
Page 2: Advancements In Visualization Of Remotely Sensed 3D Data

Matt Bethel Advancements In Visualization Of

Remotely Sensed 3D Data

Page 3: Advancements In Visualization Of Remotely Sensed 3D Data

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

Page 4: Advancements In Visualization Of Remotely Sensed 3D Data

3D Point Data Sources

• ATE

• SAR / IFSAR

• LiDAR / LADAR

– Airborne

– Mobile

– Terrestrial

– Underwater

– Autonomously collected

• Newer processes

– SFM (computer vision)

– SGM (photogrammetry)

Page 5: Advancements In Visualization Of Remotely Sensed 3D Data

3D Point Data Sources

• ATE

• SAR / IFSAR

• LiDAR / LADAR

– Airborne

– Mobile

– Terrestrial

– Underwater

– Autonomously collected

• Newer processes

– SFM (computer vision)

– SGM (photogrammetry)

Page 6: Advancements In Visualization Of Remotely Sensed 3D Data

3D Point Data Sources

• ATE

• SAR / IFSAR

• LiDAR / LADAR

– Airborne

– Mobile

– Terrestrial

– Underwater

– Autonomously collected

• Newer processes

– SFM (computer vision)

– SGM (photogrammetry)

Page 7: Advancements In Visualization Of Remotely Sensed 3D Data

3D Point Data Sources

• ATE

• SAR / IFSAR

• LiDAR / LADAR

– Airborne

– Mobile

– Terrestrial

– Underwater

– Autonomously collected

• Newer processes

– SFM (computer vision)

– SGM (photogrammetry)

Page 8: Advancements In Visualization Of Remotely Sensed 3D Data

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

Page 9: Advancements In Visualization Of Remotely Sensed 3D Data

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

Page 10: Advancements In Visualization Of Remotely Sensed 3D Data

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

Page 11: Advancements In Visualization Of Remotely Sensed 3D Data

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

Page 12: Advancements In Visualization Of Remotely Sensed 3D Data

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

Page 13: Advancements In Visualization Of Remotely Sensed 3D Data

Thank you

Matt Bethel

Director of Technology

Merrick & Company

[email protected]

303-353-3662

http://www.merrick.com/Geospatial