1 / 36

Data Collection and Quality Assurance

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

callie
Télécharger la présentation

Data Collection and Quality Assurance

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

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

  3. Original Hand Written Document. • Drawbacks • Difficult to read • Not structured • Must be retyped • Open to interpretation

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

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

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

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

  8. 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.

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

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

  11. 70-71 MANHOLE INVENTORY 707802.19, 1873544.62 1000 STORM MH 987.12 NAVD88

  12. 09-11-08 70-71 MANHOLE INVENTORY RH/RK 707802.19, 1873544.62 1000 STORM MH 1 987.12 NAVD88 N CONC GOOD STEEL NO TRASH & SILT 2 24” RCP 8.10 1001 24” RCP 8.42

  13. 09-11-08 70-71 MANHOLE INVENTORY RH/RK 707802.19, 1873544.62 1000 STORM MH 1 987.12 NAVD88 N CONC GOOD STEEL NO TRASH & SILT 2 DIR 24” NE RCP 8.10 1001 24” S RCP 8.42

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

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

  16. Survey-Grade GPS • Static (~0.03’) • Must Post-Process

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

  18. 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

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

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

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

  22. 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

  23. 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

  24. Structure Location

  25. Structure Information

  26. Pipe Information

  27. 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

  28. Pipe Point File POINTNORTHINGEASTINGELEVCODE 30000 711769.45 1827261.58 696.27 BL*P1 30001 711778.66 1827277.52 696.27 EL*P1 30002 711769.45 1827261.58 696.24 BL*P2 30003 711778.29 1827093.73 695.56 EL*P2 30004 711798.41 1827232.98 710.24 BL*P3 30005 711792.29 1827244.84 709.55 EL*P3 30006 711792.94 1827113.96 0.00 BL*P4 30007 711792.29 1827244.84 708.36 EL*P4 30008 711792.94 1827113.96 704.57 BL*P5 30009 711787.09 1827114.39 704.45 EL*P5 30010 711787.09 1827114.39 702.07 BL*P6 30011 711786.62 1827092.33 701.14 EL*P6 30012 711787.09 1827114.39 704.29 BL*P7 30013 711424.05 1827187.41 703.43 EL*P7

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

  30. 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

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

More Related