Geospatial Data Production NSF Workshop on GeoSpatial and GeoTemporal Informatics Jan 8-9, 2009 J....
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Transcript of Geospatial Data Production NSF Workshop on GeoSpatial and GeoTemporal Informatics Jan 8-9, 2009 J....
Geospatial Data Production
NSF Workshop on GeoSpatial and GeoTemporal Informatics
Jan 8-9, 2009
J. Chris McGlone
SAIC, Inc
14668 Lee Rd
Chantilly, VA 20151
703-676-9228
Energy | Environment | National Security | Health | Critical Infrastructure
What is solved (90%)?
• Photogrammetry: determination of image<->world relationship – Bundle adjustment, direct georeferencing, camera self-calibration
• Synthesis of photogrammetry, computer vision, computer graphics– Geometric and metric properties– Stochastic characteristics– Feature extraction
• Photogrammetry for the non-technical user: photogrammetry (e.g., Photosynth)
• Semi-automated construction of 3d urban models
Energy | Environment | National Security | Health | Critical Infrastructure
Texture-mapped lidar building models, w/ road centerlines
Energy | Environment | National Security | Health | Critical Infrastructure
Visual simulation database examples
Energy | Environment | National Security | Health | Critical Infrastructure
What is almost solved?
• Lidar exploitation (40%)
• Data fusion (based on geometry) (70%)
• Image sequence registration (50%)
• Semi-automatic feature extraction (40%)
• Building interior generation from plans or scans (50%)
• Interaction with 3D worlds (30%)– Navigation– Query– 3D – Immersive worlds (e.g, Second Life)
Energy | Environment | National Security | Health | Critical Infrastructure
What has failed (so far)?
• Automatic cartographic feature extraction– Still scene/image specific – Low productivity due to training, parameter fiddling, or editing requirements
Energy | Environment | National Security | Health | Critical Infrastructure
What is missing?
• Database maintenance models – Updates: scheduled, need based – Reasoning on status
• Integration of crowd sourcing into standard production flows– Verification – Characterization: accuracy, completeness, timeliness
• Simultaneous interaction with multiple datasources, SDIs – Understanding differences (timeliness, accuracy, coverage, design goals,
etc) – Automatically select best source for current purpose
• Non-geometric feature attribution (e.g., function, materials, description)
• Data fusion based on semantics
• Consumer understanding of data quality issues
• New business models for data acquisition, processing, distribution
Energy | Environment | National Security | Health | Critical Infrastructure
What is next?
• Improved realism and interactions for 3D models s
• Crowd-sourced photogrammetry (distributed acquisition)
• 3D modeling as consumer video camera application
• Video game boxes as photogrammetry/modeling/geospatial data platforms
• Mapping from image sequences
• Continuous mapping instead of discrete updates
• Better sensors, new sensing modalities (e.g., lidar + video)