AndrewFalker_Imagery Derived Surface Modeling

Imagery Derived Surface Modeling For Orthophoto Production

Andrew Falker, PT (ASPRS)Keystone Aerial Surveys, Inc. Philadelphia, PA

Imagery Derived DSM of Camden, NJ using Microsoft Ultra Map 3.0

Imagery Derived Surface Modeling For Orthophoto ProductionPresentation Overview:

• Introduction of Presenter• DSM / DTM Generation Review• Current Methods and Technologies

• Manual Interpolation• USGS National Elevation Datasets• Satellite Derived DEMs• LiDAR

• Advancement of Software/Hardware Technologies• Digital Aerial Mapping Cameras• ABGPS/IMU Processing• CPU/GPU Imagery Processing

• Sample Projects• Questions, Comments, Concerns?

GIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

Imagery Derived Surface Modeling For Orthophoto Production

Andrew Falker, PTGeospatial Analyst, Keystone Aerial Surveys, Inc.


• ASPRS Certified Photogrammetric Technologist• 7 Years of Geospatial Industry Experience • Qualified Airborne Sensor Operator, (Film,

Digital, LiDAR). Hundreds of Survey Missions with over 2500 flight hours.

• In Field Project Manager/Sensor Operator for the Microsoft BING Maps Global Ortho Project

• Orthophoto Production Manager; completed projects from the following industries; Environmental, Energy, Transportation, & Government)

• Keystone’s GIS Projects Manager

Digital Surface Model (DSM) VS. Digital Terrain Model (DTM)


DSM – are point clouds combined with an interpolation scheme defining the visible surface (fig 1a)

DTM – are point clouds defining the bare ground (fig 1b)(Miller and Laflamme, 1958, Doyle, 1978, )

Current Methods and Technologies


• Manual Interpolation “Softcopy Photogrammetry” • Photogrammetrist collect ground points off of

stereo imagery sing “Digital Soft Copy Instruments”

• Time Consuming• Man Power intensive

Current Methods and Technologies


• USGS National Elevation Models (NED) Available in a Varity of Resolutions• 1 arc-second (approximately 30 meters) for the conterminous

United States

• 1/3 and 1/9 arc-seconds (approximately 10 and 3 meters respectively) for parts of the United States . (USGS)

• Though free and widely available, they often have errors and discrepancies (especially between tiles)

• Not “current” enough in certain areas.

USGS National Map


Current Methods and Technologies• Satellite Derived Digital Elevations Models

- Types• ASTER – Advanced Space born Thermal Emission and

Reflection Radiometer

• SRTM – Shuttle Radar Topography Mission

• Commercial Providers (Digital Globe, GeoEye, Astrium, Third Party Vendors)


Current Methods and Technologies• LiDAR – Active Sensor

• Great for multiple applications• Power line mapping• Transportation corridor mapping• Still evolving and maturing

• Different products being produce Expensive

• Requires a great deal of flying • Requires highly skilled technicians for

processing and editing of the data

Advancement of Software/Hardware Technologies


Next Generation of Digital Aerial Mapping Cameras(UltraCam Eagle, UltraCam Osprey, UltraCam )

• Better Geometric Accuracy• Better Reliability • Larger Footprints• More Efficient • All Digital Workflow• Multiple products derived from a single

flight

RGB, RGBNIR Stereo Imagery DSM/DTM’sDSM Point CloudsHi-Res Ortho Imagery (2cm achievable from Fixed wing)

Microsoft UltraCam Eagle


Advancement of Software/Hardware TechnologiesABGPS/IMU Processing

• Refined IMU/INS (Inertia Measurement Units)• Higher sensitive instruments

• GNSS ABGPS

• Proliferation of CORS Network.• Less demand for Base Stations • Better solution for the ABGPS


Advancement of Software/Hardware TechnologiesCPU/GPU Imagery Processing

• Multi-Core image processing has vastly improved the speed and efficiency of processing large imagery data sets (as well as LiDAR)

• GPU processing takes it step further taking advantage of powerful image processors traditionally used by the gamming industry

Software Used at Keystone Aerial Surveys

Sample Project


Rutgers University Camden Campus• 15cm Pixel, Two Flight Lines• 80% Forward Lap, 60% Side lap


UltraMap Generated DSM15CM GSD Pixel

Sharp Detail Even @ 15cm GSD


Individual vehicles can be easily identified

Change Detection?

Structures Well Defined


3D City Modeling GIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

Bridge DetailGIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

Completed 15cm GSD MosaicGIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

Other Samples of DSM’s… GIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

City of Camarillo, CA

Imagery Derived DSM• Microsoft UltraCam X• SimActive Correlator 3D

Colorized .LAS Point Cloud• Inpho 5.5 (NEW)

Point Cloud Global Mapper DemoGIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

Some Issues With Automatic Imagery Derived DSM’s

GIS Pro 2013: Presentation Luncheon; Tuesday, September 17th, 2013

• NOT a Silver Bullet • There is still a need for heavy editing• Break lines are STILL necessary (albeit

fewer)• Vegetation penetration is difficult • Shadows, glass and water surfaces

introduce erroneous errors and noise


• Questions • Comments• Concerns

THANK YOU!

References GIS Pro 2013: Presentation Luncheon, Tuesday September 17th, 2013

Passini, Jacobsen, Day, Qillen 2013http://www.ipi.uni-hannover.de/uploads/tx_tkpublikationen/asprs_Baltimore_2013.pdf

http://www.ipi.uni-annover.de/uploads/tx_tkpublikationen/asprs_Baltimore_2013.pdf




http://www.ipi.uni-hannover.de/uploads/tx_tkpublikationen/asprs_Baltimore_2013.pdf

http://www.ipi.uni-hannover.de/uploads/tx_tkpublikationen/asprs_Baltimore_2013.pdf

AndrewFalker_Imagery Derived Surface Modeling

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