Mastering the Challenges of 3D Data Management
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Transcript of Mastering the Challenges of 3D Data Management
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Mastering the Challenges of3D Data Management
Hans ViehmannProduct Manager EMEA
ORACLEPRODUCT
LOGO
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Specific challenges for 3D data
• large amounts of data (acquisition & storage)
• expertise and specific tooling required for data processing
• data models and standards
• adequate visualization tools
• data dissemination
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How do we fit in?
• Data Storage
• Data Lifecycle Management
• Data Analysis
• for all variations of spatial data
• Vector, Raster, Point Clouds, TINs, Networks, Topologies, ...
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Why use a database?!
• Moving Spatial data into IT infrastructure allows to– Lower data management cost– Simplify application development– Integrate with other enterprise data
• Enable development teams to focus on business context, not infrastructure services
– Database and Application Server manage deployment infrastructure• Security • Scalability • Standards Compliance• Load Balancing • Failover • HW/SW Dependencies
– Support multiple application models with common data model• Java • GML • Future …• .Net • Web Services/SOA
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Data acquisition in 3D
• large volumes of point data acquired by sensors– LIDAR (Light Detection and Ranging)– Seismic sensors
• millions of points to model a scene
• data type to efficiently manage this data– SDO_PC: can handle billions of points
• Triangulated Irregular Network: create surfaces from point data sets– SDO_TIN: scalable storage
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General 3D processing flow
LiDAR Files
LiDAR loader
SDO_PC tables
Query and Clip
Convert to Geometries
Flat files
Load point cloud
Point Tables
TIN tablesGenerate TIN
Query and Clip
Convert to Geometries
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Data loading using libLAS
• available from http://liblas.org/
• for Windows, download and install pre-build binaries in the OSGeo4W package http://trac.osgeo.org/osgeo4w/– A packaging of a number of open source tools: libraries, desktop GIS (Quantum,
Grass, …), servers (UMN Mapserver, …)
• main tools (see http://liblas.org/docs.html for details)– lasinfo = returns information about a LAS file– las2oci = loads a LAS file into Oracle– las2las = copy and transform a LAS file– las2txt = converts a LAS file to a text format– txt2las = the reverse
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Management of 3D data
• correct, integral usage of height information („z“)– 3D indexing and query– coordinate system support
• ability to model 3D objects– points, lines, polygons with „z“– solids, surfaces– point clouds
• need for higher-level data models– eg. support for CityGML data model
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Constructing 3D objects
• Simple Surfaces– Face = 3D Polygon
• Composite Surface– Multiple connected faces
• Simple Solid– Closed composite
surface
• Composite Solid– Multiple connected
simple solids
• Extrusion– Generating solids from
2D polygons
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Data models for City Modelling
• Structures at multiple levels of detail
• Textures and facades
• Orthophotos
• Versioning
3DCityDB (open source data model) is widely used
LOD1 Building LOD2 Building LOD3 Building LOD4 Building
Images courtesy of: Research Center Karlsruhe
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City of Berlin – 3D City Model
• 550000 buildings, reconstructed from 2D cadastre and LIDAR data
• Textures extracted from oblique aerial photography
• Stored in 3DCityDB
• 2012 Oracle Spatial Excellence Award
Implemented by TU Berlin
Images courtesy of: TU Berlin, Institute for Geodesy and Geoinformation
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Engineering & Construction - Crossrail
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Publish KML in the XDB Repository
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View in Google Earth
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Summary
• integrated storage and management of all relevant data types
• scalability to huge amounts of data and large numbers of users
• comprehensive tooling and partner solution portfolio
• leveraging key features of Oracle Database
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Upcoming Events
• Oracle Spatial and Graph Users Conference 2013• Washington, DC, May 22• in conjunction with Location Intelligence 2013, May 21
• new: attend by Webcast, „live“ or „on-demand“• see http://www.locationintelligence.net/dc/registration/
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