2013 ASPRS Track, Modeling Asset Condition Using LIDAR and GIS Data by Colin Hobson
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This presentation details a methodology for assessing the condition of infrastructure in Albany using LIDAR and GIS data as part of an Asset Management Information Plan. It outlines the criteria and data sources used to prioritize maintenance and improvement, including factors like age, material, and structural integrity. The approach utilizes advanced visualization and mapping techniques to ensure a comprehensive evaluation of the city's collection system infrastructure.
2013 ASPRS Track, Modeling Asset Condition Using LIDAR and GIS Data by Colin Hobson
- 1. Modeling Asset Condition Using LIDAR and GIS Data Colin Hobson Director, North America Open Spatial Corporation
- 2. Overview and purpose This presentation outlines the data and techniques used to provide a prioritized rating value and map of the condition and improvement priority of the collection system infrastructure as part of the development of an Asset Management Information Plan (AMIP) for the City of Albany
- 3. Conceptual model and data sources OBSERVED CONDITION Structural condition Ops and maint. condition CONSEQUENCE Pipe Diameter Environmental proximity Construction Critical crossings Risk Cond. Conseq. PROBABILITY (OF FAILURE) Age Material CONDITION SCORE RISK SCORE Prob . TOTAL SCORE COND_CATEGORY A - 10 or more years B - 5-10 years C - 1 - 5 years
- 4. Build Asset Intelligence Management WO’s, Planning Modeling, Online maps, mobile apps Seamless, connected, attributed network CAD drawings Paper maps As builts & projects
- 5. Data sources • Structural • Condition from CCTV • Ops and Maint • Derived from CMMS Score based on maintenance and repairs required • Age • Material • Diameter • Derived from as-builts, field notes and stored in GIS database
- 6. How was the data gathered and checked • Build attributed asset inventory in Munsys using – – – – Existing CAD/DWG maps Paper as-builts Field check and updates In the office • Checking • Imagery • Google • Autodesk Civil 3D and Munsys for LIDAR surface and flow analysis • Autodesk InfraWorks
- 7. Reference and locate as-built documents
- 8. Reference and locate as-built documents
- 9. Update directly from as-builts
- 10. Track and find referenced as-built documents Show and list all referenced as-builts for the project area (solid red area)
- 11. Search, find and hyperlink in a browser
- 12. Search, find and hyperlink in a browser Selected objects Summary list of objects Individual details and hyperlink
- 13. Search, find and hyperlink in a browser As-built document opened from Hyperlink
- 14. Fully attributed asset inventory in Munsys
- 16. Error checking using 3D visualization
- 17. From asset inventory to 3D visualization
- 18. Example factors
- 19. LIDAR data used for flow checking between sewer and storm systems: Surface loaded in Autodesk Civil 3D with Sewer and Storm data
- 20. LIDAR data used for flow checking between sewer and storm systems: Water surface flows displayed
- 21. LIDAR data used for flow checking between sewer and storm systems: Flow from Sewer to Storm recorded – distance, ID and type of asset
- 23. Using the model – data manipulation Linked GIS Source data Calculated values and derived categories
- 24. Using the model – calibration categories Set category ranges and factors – view changes dynamically
- 25. Using the model – scores from matrices
- 26. Using the model – data listing of score, priority and repair and replace costs for each pipe segment
- 27. Output on the Map – Repair categories
- 28. Tangible value – repair priorities
- 29. Conceptual model and data sources OBSERVED CONDITION Structural condition Ops and maint. condition CONSEQUENCE Pipe Diameter Environmental proximity Construction Critical crossings Risk Cond. Conseq. PROBABILITY (OF FAILURE) Age Material CONDITION SCORE RISK SCORE Prob . TOTAL SCORE COND_CATEGORY A - 10 or more years B - 5-10 years C - 1 - 5 years