GIS Data Management for Large Infrastructure Projects

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GIS Data Management for Large Infrastructure Projects

  1. 1. GIS Data Management forLarge Infrastructure ProjectsRoland MartinSenior GIS Consultant, Arup 19 April 2012
  2. 2. Introduction1. Who am I?2. What is a large engineering project?3. How does GIS help?4. Managing GIS data5. GIS analysis
  3. 3. We are a global, integrated, multidisciplinary firm ofprofessionals working together to tackle complex planning,infrastructure and building design challenges10,000 engineers, designers, planners, managementconsultants and economists90 networked offices in 37 countriesFull service from concept through completionDedicated to delivering value through expertise, globalresources and local delivery
  4. 4. Large infrastructure projects Forth Road Crossing, Scotland Antwerp Scheldt Crossing, Belgium California High Speed Train Project Transbay Terminal, San Francisco
  5. 5. Typical GIS tasks Gather Manage information information GIS Analyze Share information information
  6. 6. Data gathering Civils Geotechnics GIS Utilities Base Data General Information
  7. 7. Project data flows On an example Primary data flows rail project... Secondary data flows GIS AirNoise Quality Utility Environmental Engineering teams Ecology Rail Engineering Highway Geotechnical Engineering Engineering Bridge Engineering
  8. 8. Project data flows Rail Aerial Land Existing Alignment Imagery Parcels Infrastructure ALG TIFF MDB MixedSource Modelled using InRoads Purchased files Personal Geodatabase SHP, MDB and DWG DGN DGN Labelled with AIN, owner name, Generated in InRoads DGN etc Assessed for accuracy fGDBRequired Classified by construction JPEG fGDB output method With files as small as possible Classified by land use fGDB MDB Various KMZ Database of ownership For quick visualisation information, right of way
  9. 9. Processing alignment into GIS
  10. 10. Land use analysis Urban areas can be extremely complex Lots of constraints  Parks  Churches  Prison  Healthcare facilities
  11. 11. Route analysis Terrain data Faults Land use data Engineering constraints:  Minimum curve radii  Maximum gradient Keep costs down!
  12. 12. Property counts Output from acoustic model  Noise impact (Ln) from road Level Properties People Affected 50-55 dB 420 917 55-60 dB 265 606 60-65 dB 317 715 65-70 dB 232 569 >= 70 dB 114 222 Output from air quality model • Areas with NO2 levels above threshold Level Properties People Affected < 40 PPM 823 1782 >= 40 PPM 525 1247
  13. 13. Environmental modeling Noise mapping Air quality modeling Ecology assessments Odormodeling
  14. 14. Environmental modeling with FME Extracting data from OracleNoise modeling Air quality modeling
  15. 15. Thank You! Questions? For more information:  roland.martin@arup.com  www.arup.com

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