Eric Wing, GISP GIS Systems Analyst, City of Boise September 16, 2010

1. Leveraging Linear Referencing to Map Sewer Events from CCTV Logs Eric Wing, GISP GIS Systems Analyst, City of Boise September 16, 2010 Penn State Advisor: Dr. Todd Bacastow

2. Overview • Background • Objectives • Methodology • Challenges • Results • Questions

3. Boise and Sewer • 650 miles of sewer lines • 51,760 customers • 30 million dollars annual revenue • 150 users in Public Works Background Objectives Methodology Challenges Results

4. Sewer in the Field • GIS data • Manholes • Mainlines • Service laterals Background Objectives Methodology Challenges Results

5. GPS vs CCTV • GPS • Since 1995 • 22,431 records • Better representation • CCTV • Pre 1995 • 60,454 records Background Objectives Methodology Challenges Results

6. CCTV • Service laterals • Roots • Material changes • Cracks • Grease Background Objectives Methodology Challenges Results

7. Previous Process Background Objectives Methodology Challenges Results

8. Issues • 12 year old UNIX server • ARC/INFO 7 AML and coverages • Many manual steps • Automated processes take 62 hours • Known limitations Background Objectives Methodology Challenges Results

9. Objectives • Streamline the process • Reduce manual steps • Automate where possible • Use ESRI ArcGIS 9.3 technology • No new extensions • No additional software • Correct for limitations where possible • Evaluate expansion opportunities Background Objectives Methodology Challenges Results

10. Linear Referencing Background Objectives Methodology Challenges Results

11. Development Strategy • ModelBuilder / Python • City not ready for ArcGIS 10 • Rapidly changing environment • Hansen 8 upgrade pending • New CCTV software • Looking to automate Background Objectives Methodology Challenges Results

12. General Process • Extract Hansen data • Mainline assets • Inspection logs • Event records Background Objectives Methodology Challenges Results

13. General Process • Create and calibrate routes • Calibrate against Hansen length Background Objectives Methodology Challenges Results

14. General Process • Massage Hansen data • Joins, filters, and calculations Background Objectives Methodology Challenges Results

15. General Process • Generate features Background Objectives Methodology Challenges Results

16. Challenges • Hansen issues • Hansen 8 upgrade behind schedule • Data inconsistencies • Sewer mainlines with 0 length • Event located at footage longer than the pipe • Synchronization between GIS and Hansen Background Objectives Methodology Challenges Results

17. Challenges • 12:00 and 6:00 observations Background Objectives Methodology Challenges Results

18. Challenges • Service connections to manholes Background Objectives Methodology Challenges Results

19. Challenges • Problem: duration • Takes 54 hours to create 64,000 features • Solution: update only new/changed data • Typically on a few hundred new/altered records in a month Background Objectives Methodology Challenges Results

20. Results • Solution streamlined • Eliminated manual steps • Process is automated • Using ArcGIS 9.3 software • Can surplus UNIX server • No more ties to ARC/INFO 7 • Limitations corrected • Some resolved, some remain Background Objectives Methodology Challenges Results

21. Current Process Background Objectives Methodology Challenges Results

22. Expanded Data Results Background Objectives Methodology Challenges Results

23. Next Steps • Expanded data • Hansen 8 upgrade • ArcGIS 10 upgrade • Move entirely to Python Background Objectives Methodology Challenges Results

24. Acknowledgements • City of Boise • Barbara Edney, GIS Analyst • Jim Pardy, Assistant City Engineer • Melissa Rushton, Public Works Project Coordinator / Hansen Specialist • Penn State • Dr. Todd Bacastow, Advisor

25. References • Cadkin, J., & Brennan, P. (2002). Dynamic Segmentation in ArcGIS. ArcUser, July-Sept. Retrieved from http://www.srnr.arizona.edu/rnr/rnr420/dynseg.pdf • Clancy, D., Gustafson, J., & Higgins, L. (2002). Economical Sewer Main Rehabilitation Utilizing ArcGIS and Dynamic Segmentation. Retrieved from http://proceedings.esri.com/library/userconf/proc02/pap1181/p1181.htm • Curtin, K., Nicoara, G. & Arifin, R.R, (2007). A Comprehensive Process for Linear Referencing. Journal of the Urban and Regional Information Systems Association, 19 (2): 41-50. Retrieved from http://www.urisa.org/curtin • ESRI. (2001). Linear Referencing and Dynamic Segmentation in ArcGIS 8.1. Retrieved from http://www.esri.com/library/whitepapers/pdfs/lrds_arcgis.pdf • ESRI. (2003) Linear Referencing in ArcGIS: Practical Considerations for the Development of an Enterprisewide GIS. Retrieved from http://downloads2.esri.com/support/whitepapers/ao_/Linear_Referencing_in_ArcGIS.pdf • ESRI. (2006) GIS for Utilities [PowerPoint slides]. Retrieved from http://www.iowagic.org/resources/user-groups/eastern-iowa-user-group/past-events/january-25-2006/arcgis-tools-for-water-and-wastewater.pdf • Ferreira, A., & Duarte, A. (2005) A GIS-Based Integrated Infrastructure Management System. Retrieved from http://www.fig.net/pub/cairo/papers/ts_37/ts37_09_ferreira_duarte.pdf • Goodman, J.E. (2001). Maps in the Fast Lane – Linear Referencing and Dynamic Segmentation. Retrieved from http://www.directionsmag.com/article.php?article_id=126 • Meehl, J. (2004). Pipeline Integrity Management Using Linear Referencing With ArcObjects. Retrieved from http://proceedings.esri.com/library/userconf/proc04/docs/pap1976.pdf • Pierre, J., Mosher, J., Hargis, A. (2006). Linear Referencing in Boulder County, CO: Getting Started [PowerPoint slides]. Retrieved from http://proceedings.esri.com/library/userconf/proc06/papers/papers/pap_2071.pdf

26. Questions Eric Wing, GISP GIS Systems Analyst, City of Boise 150 N Capitol Blvd Boise, ID 83702 208.384.3936 ewing@cityofboise.org