1. Data Collection and Quality Assurance Ron Howard Jr., EI Environmental Coordinator Russell Koenig, PS, EI Surveyor DLZ Ohio, Inc. 2008 Ohio GIS Conference September 10-12, 2008 Crowne Plaza North Hotel Columbus, Ohio

2. QUALITY ASSURANCE Refers to planned and systematic processes that provide confidence of a product’s or service’s effectiveness.

3. Original Hand Written Hand WrittenDocument. Drawbacks Difficult to readDifficult to read Not structuredNot structured Must be retypedMust be retyped Open to interpretationOpen to interpretation

4. Palm Database Document Benefits Standardized responses.Standardized responses. Easy sorting and manipulation of data.Easy sorting and manipulation of data. Provide client with a document designed around their changing needs.Provide client with a document designed around their changing needs.

5. Palm Database Document Benefits cont. Check boxes and drop down menus save time.Check boxes and drop down menus save time. Once entered document is complete.Once entered document is complete. Greater quality final product.Greater quality final product.

6. Palm Database Document Drawbacks Special Training.Special Training. Greater learning curve for users.Greater learning curve for users. Field crew’s level of detail is visibly displayed whether good or bad.Field crew’s level of detail is visibly displayed whether good or bad.

9. Comparison and Savings between Electronic and Hand Written Data Collection.

11. Brain power has to rise in proportion to the reduction in time, operational effort, and muscle power. Joseph V.R. Paiva, PH.D., P.S.

12. Case Study: I-70/71 Existing Utility Location –Subsurface Utility Engineering (SUE) –Sewerage/Drainage

13. Project Approach Combine Survey Data with GIS Data Collection methods to produce a final product with maximum quality in minimal time.

18. GIS Data Collection Advantages Upload coordinates for navigation Customized drop-down menus No lost, damaged, or illegible forms Downloadable information

19. GIS-Grade GPS Fast and effective –Navigation –Inventory Low accuracy –30 feet un-processed –1-3 feet post-processed (using CORS)

20. Survey-Grade GPS Static (~0.03’) –Must Post-Process

21. Survey-Grade GPS Static (~0.03’) –Must Post-Process RTK (~0.10’) –Base Station & Radio Waves –No Post-Processing

22. Survey-Grade GPS Static (~0.03’) –Must Post-Process RTK (~0.10’) –Base Station & Radio Waves –No Post-Processing VRS (~0.10’) –CORS Network –“On the fly” results

23. Step 1: Survey Search for approximately 1900 structures –770 located previously during SUE work Obtain accurate coordinates

24. Step 2: Report Structure details & condition Pipe information –Direction, size, material, depth, connection GIS-Grade GPS coordinate

25. Sewer Database spreadsheet (Excel) –Survey coordinates and GIS report data Compare GIS and survey coordinates Calculate pipe invert elevations Step 3: Assemble

26. Step 4: QC Database analysis –Identify missing or conflicting information Existing records –City of Columbus Sewer Atlas –Original construction and as-built drawings Additional field work –Stakeout, locate, and report missing structures

27. Step 5: Deliver The final report included –1458 located structures –3177 reported inverts Bound book –Database was easy to format Organized into 3 sections –Structure Location –Structure Information –Pipe Information

28. Structure Location

29. Structure Information

30. Pipe Information

31. Additional Request – Pipe Drawing Create invert coordinates Place all start & stop points in order Add point number & survey linework codes –BL*P = Begin Line “Pipe” –EL*P = End Line “Pipe” Run through drafting software –Lines were automatic and at true elevation

32. Pipe Point File POINTNORTHINGEASTINGELEVCODE 30000711769.451827261.58696.27BL*P1 30001711778.661827277.52696.27EL*P1 30002711769.451827261.58696.24BL*P2 30003711778.291827093.73695.56EL*P2 30004711798.411827232.98710.24BL*P3 30005711792.291827244.84709.55EL*P3 30006711792.941827113.960.00BL*P4 30007711792.291827244.84708.36EL*P4 30008711792.941827113.96704.57BL*P5 30009711787.091827114.39704.45EL*P5 30010711787.091827114.39702.07BL*P6 30011711786.621827092.33701.14EL*P6 30012711787.091827114.39704.29BL*P7 30013711424.051827187.41703.43EL*P7

34. Highlights Minimal field time Structure & report verification Automated calculations No transposing errors Easily formatted report

35. The Future Innovative process and experience –More jobs of this type at very low cost Enhanced Sewer Database spreadsheet –Automated calculations and error messages –Faster and better

36. THANKS! Ron Howard Jr., EI Environmental Coordinator Russell Koenig, PS, EI Surveyor DLZ Ohio, Inc. 6121 huntley Road Columbus, Ohio 43229 614-888-0040