<Insert Picture Here> Data Management Innovations for Massive Point Cloud, DEM, and 3D Vector Databases

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1 <Insert Picture Here> Data Management Innovations for Massive Point Cloud, DEM, and 3D Vector Databases Xavier Lopez, Director, Product Management

2 3D Data Management Technology Drivers: Challenges & Benefits Use Cases for 3D Data Management Overview of Spatial Databases Oracle 11g 3D Features Wrap-up <Insert Picture Here>

3 Technology Drivers <Insert Picture Here>

4 Technology & Business Trends Massive new sensor hardware capabilities Automated Data Capture / Model Creation (sensors) Increase productivity in 3D data management workflow Improve performance and scalability of existing workflows Bridging gap between point cloud surveys, GIS, CAD, BIM Propel 3D to Mainstream Mass Market: Consumer-focused systems Benefit from IT scalability, security, and reliability Files to Databases Merge Point Cloud content with other geospatial types Integrate attribute data with point cloud features

5 Challenges: Managing Point Cloud Data Robust Data Management Challenges: High Density LIDAR: Sub-meter point spacing (billions of points) Combine with multi-spectral gridded data (terabytes of data) Versioning, Archiving (terabytes, petabytes) Back-up/recovery Data Transformation LIDAR point filtering, visualization, analysis Surfaces and 3D vector models Attribute Data Integration Leverage Grid computing, clustered servers Visualization & Analytics Integrate 3D models into business workflows Associate 3D objects/features to attributes Spatial query across point cloud features Managing updates

6 What do Spatial Databases Bring? Scalability: Large seamless 3D scenes: Terabytes of objects Fast Retrieval: Geospatial (r-tree) Indexes on 3D point clouds Partitioning: Manage large seamless scenes Grid computing: Massive Data processing Interoperability: Fusion of aerial imagery, close-range airborne and ground video/lidar with traditional 2D vector models Spatial analysis: conduct traditional GIS queries on 3D scenes Transactional Updates Enterprise Integration: Integrate 3D models with business information. Versioning and Long Transaction Support: Data security, access control, encryption, authentication Open: Support by third party 3D viz and analysis tools

7 Creating Value Added Data Products CAD/BIM server TIN server Point Cloud Repository 3D Model server Image server

8 Spatial DBMS in a Production Workflow: Data Collection Production Dissemination & Exploitation LIDAR Surveys Model/Scene Generation 3D Mapping Photogrammetry Image Texture Wrapping Fly Through Aerial Photos Versioning 3D analysis LIDAR CAD Ortho- Photos Satellite Imagery COTS Scenes CAD Designs Editing/Updates Quality Control Volumetric Analysis Engineering Design Predictive Analysis Navigation Systems Spatial RDBMS

9 3D Information Management Challenges Scalability - large data volume Availability tens of thousands of users Security protect sensitive location data Performance timely query response Accessibility to enterprise applications Manageability leverage IT resources Open Supports standard interfaces and formats = Database Strengths

10 Use Cases <Insert Picture Here>

11 GIS Analytical Modeling & Simulation Flood Plain Analysis Petroleum Exploration

12 CAD Infrastructure Design (Super Models) Courtesy Parsons Brinckerhoff

13 Google Earth 3D Mash-ups

14 Simulation, Gaming, and VR

15 Oracle Spatial Overview <Insert Picture Here>

16 Customer Requirements Enterprise-class RDBMS to manage ALL geospatial types 2D, 3D, Rasters, Networks, Topology, Attributes Native type support, indexing, and analysis First commercial vendor to full 3D coordinate systems support Standards based: SQL, Java,.NET Addresses large volumes of 3D point data Building City models (Collada, CityGML) Laser scanning (LIDAR, sonar) Geo-engineering (CAD) Surfaces (TINS, DEMS) Addresses range of 3D application domains GIS, CAD/CAM City Modeling, environmental analysis Real Estate, asset management Personal navigation VR, gaming, simulation

17 Spatial Database Capabilities Spatial Analysis Spatial Data Types Spatial Indexing All Location/Spatial Data Stored in the Database Spatial Access Through SQL Fast Access to Spatial Data

18 Spatial Databases: Managing all Geodata Types 3D Models (Buildings) Networks (Highway network) Parcels (polygons) Imagery (Satellite) Data Structured Networks/Boundaries (persistent topology) Lidar (Point Clouds)

19 Advanced Spatial Data Management Capabilities SQL Spatial Type R-tree index Spatial Operators Spatial Reference System EPSG Support Geodetic (lat/long) Support Linear Referencing Spatial Aggregates Versioning Long Transactions Fusion Middleware MapViewer GeoRaster Type Network Data Model Linear Referencing Topology Data Model Geocoding Engine Routing Engine Spatial Data Mining Text Annotation/Orientation 3D Models and LIDAR Types Web Feature Server (WFS T)

20 Spatial Databases Addressing GIS Interoperability Problem Leica Bentley Spatial Data Warehouse Mapinfo MapXtreme

21 <Insert Picture Here> Oracle 11g Spatial 3D Capabilities

22 3D Functionality in Oracle Spatial 11g 3D COORDINATE SYSTEMS Types SDO_GEOMETRY (3D) SDO_TIN SDO_POINT_CLOUD Building Models,.. Surface Modeling Scene, Efficient Storage Query Analysis Object Modeling

23 3D Spatial Data Types Simple and composite Solids Solids are composed of closed surfaces It has to have one outer surface and one or more interior surfaces Cube is an example of a simple solid A pyramid is another example of a simple solid Composite solids: formed by multiple solids Always define a single contiguous volume

24 Point Clouds: LIDAR Large volumes of point data acquired by sensors LIDAR (Light Detection and Ranging) Seismic sensors Millions of points used to model a scene New data type introduced to efficiently manage this type of point data TIN to create triangulation of such points

25 TINs: Triangulated Irregular Networks Vector-based topological data model represents terrain/surface Contain a network of irregularly spaced triangles 3D surface derived from irregularly spaced points Each sample point has an x, y, z or surface value Node No X Y Z

26 Query, Analysis of 3D Data Given a 3D Geometry as Query, Identify data geometries that Intersect the Query (SDO_ANYINTERACT) Within specified distance from Query (SDO_WITHIN_DISTANCE) Nearest to Query (SDO_NN) Analysis Functions Relationship: Geometry-Geometry Intersection Length, Area, Volume Analysis Validation of 3D Geometry: Is Solid closed? Extrusion of 2-D Footprint to a 3-D Solid by specifying heights Association of Textures with LabelStrings of Geometry Elements Extraction of Elements using LabelString of Geometry Conversion Functions to/from GML, to KML/Collada, from CityGML

27 3D Coordinate System Functions Same use as 2D Coordinate Systems: A reference system for spatial operations Associate a coordinate system with 3D data SDO_GEOMETRY Support transformations from one to another coordinate system Compute distances, and other spatial relationships between two objects within the same coordinate system

28 3D Coordinate Systems Oracle Spatial 11g supports the following EPSG types Vertical Coordinate Systems: Essentially 1-d coordinate system (w.r.t sea-level etc.) Geocentric: 3-d Cartesian Geographic-2d, Projected-2d: 2-d Ellipsoidal Geographic-3d: 3-d Ellipsoidal Compound Coordinate System Combines A Vertical Coordinate System with Either A Geographic-2D or A Projected-2D Coordinate System Oracle Spatial 11g supports transformations between different 3D Coordinate Systems

29 Summary Support for large seamless 3D scenes: Terabytes of objects Provides bridge to fuse 3D, 2D, CAD, raster data Fusion of aerial imagery, close-range airborne and ground video/lidar with traditional 2D vector models Integrated support for Web delivery Spatial analysis: conduct traditional GIS queries on 3D scenes Transactional Updates Enterprise Integration: Integrate 3D models with business information. Data security, access control, encryption, authentication Open: Support by third party 3D viz and analysis tools

30 To find out more... Or me..