mastering 3d challenges - hansviehman

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Mastering the Challenges of 3D Data Management

GIS Ireland 2013

Hans Viehmann

Product Manager EMEA


Driving Forces for 3D/4D Projects

• Risk management

– flooding

– land slides

• Renewable Energy

– solar potential

– wind energy

• Urban Planning

– traffic management

Public Services, selected use cases

• Public Safety

– disaster management

– event management

• Tourism

• numerous initiatives

underway

– 3D Pilot NL, AdV Germany, ...


Driving Forces for 3D/4D Projects

• Utilities

– asset maintenance

• Engineering & Construction

– railway construction

– road construction

– BIM

• Telecoms

– mobile phone network planning

Commercial, selected use cases

• Railway operations

– track monitoring

– noise emission

simulation

• Retail

– indoor navigation

– Location-based

marketing


Specific challenges for 3D data

• expertise and specific tooling required

for data processing

• adequate visualization tools

• new or extended data models

• new standards

• rethink data dissemination

• ... and large amounts of data (acquisition & storage)

Bad news: There‘s more complexity ...


Let‘s not forget the lessons learnt

• Reduce complexity, use standard IT components

– Integration of geospatial and enterprise data

• Take advantage of cost saving technologies

– Move towards cloud computing, information lifecycle management, ...

• Avoid moving data around

– „in-situ“ processing

• Capture, maintain and deliver metadata

– consider semantic interoperability

• Use open standards for technical interoperability

Experience from the last decades


Crossrail, UK

• 21km twin tunnel under City of London,

90km of new railway line

• Database as „single source of truth“

– „live“ data in a single location

– 500 layers of information, large data sets

– Serving Bentley Map, Geo Web Publisher,

Esri ArcGIS

– integrated security

• collaboration and cooperation across

different disciplines and companies

Geospatial Data Warehouse


Engineering & Construction - Crossrail


Simplify IT by moving to Cloud Computing

Private Cloud

• Self-service

• Auto-scaling

• Metering & chargeback

• Capacity planning

Public Cloud

• Specialized

• Shared

• Standardized

Hybrid Cloud

• Federation across public & private clouds

• Interoperability

• Cloudbursting

Traditional Silos Consolidated

• Physical

• Dedicated

• Static

• Heterogeneous

• Disparate Spatial Data

• Virtual

• Shared platform

• Dynamic

• Standardizedplatform & infrastructure

• Integrated Spatial Data

Start with consolidation • Extend to private cloud • Use public cloud where appropriate


Consolidation of data and Services

Database functionality such as

• Spatial queries

• Semantic queries

• Versioning/Long Transactions

SOA Plattform

• Application Server

• Service Bus/Orchestration

Required platform capabilities

PaaS

WebGIS

Srv. App

f1

f2n1

n2

e1

e2e3

e40D (points) 1D (lines) 2D (areas) Geo-Raster Network Topology 3D, LIDAR

WFS

CSW WCS

WMS

OpenLS


Data models, eg. based on CityGML

• Decomposing urban space into meaningful

objects

• Structures at multiple levels of detail

• Textures and facades

• Orthophotos

3DCityDB (open source data model) is widely used

LOD1 Building LOD2 Building LOD3 Building LOD4 Building

Images courtesy of: Research Center Karlsruhe

http://opportunity.bv.tu-berlin.de/software/projects/3dcitydb


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


ÖBB-Infrastruktur AG, R&DOracle Spatial and Graph: Railway Network Management

Objectives

Optimize railway planning, construction and

maintenance

Enable efficient routing of railway lines

Solution

Stores and processes more than 8 billion

points of objects along railway tracks

Enables LiDAR data to be viewed with

existing infrastructure vector data

Provides comprehensive metadata about

railway tracks through CSW

Delivers data through open WebServices

“[This technology…] is indispensable to process

geospatial data with high efficiency at low cost,”Dr. Michaela Haberler-WeberÖBB-Infrastruktur AG, R & D

Image courtesy of: IQsoft, Austria


Point-Cloud to Contour


Publish KML in the XDB Repository


View in Google Earth


Summary

• Reduce complexity, use standard IT components

– Integration of geospatial and enterprise data

• Take advantage of cost saving technologies

– Move towards cloud computing, information lifecycle management, ...

• Avoid moving data around

– „in-situ“ processing

• Capture, maintain and deliver metadata

– consider semantic interoperability

• Use open standards for technical interoperability

Managing the Challenges of 3D Data


Role of Authoritative Geospatial Information

Providers

• Continue to collect, aggregate, and validate national

geospatial and statistical data, increasingly in 3D/4D

• Produce Authoritative reports and sources of information

• Be the information source in the Cloud

• Establish / adopt standards to enable sharing of this

information

• Opportunity to produce added value analysis and

analytic services

mastering 3d challenges - hansviehman

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