Data Collectionand Quality Assurance

Ron Howard Jr., EIEnvironmental

Coordinator

Russell Koenig, PS, EISurveyor

DLZ Ohio, Inc.2008 Ohio GIS

ConferenceSeptember 10-12, 2008

Crowne Plaza North Hotel

Columbus, Ohio

QUALITY ASSURANCE

Refers to planned and systematic processes that

provide confidence of a product’s or service’s

effectiveness.

Original Hand

WrittenDocument

. Drawbacks • Difficult to

read• Not structured• Must be

retyped• Open to

interpretation

Palm Database Document

Benefits• Standardized

responses.• Easy sorting

and manipulation of data.

• Provide client with a document designed around their changing needs.

Palm Database Document

Benefits cont.• Check

boxes and drop down menus save time.

• Once entered document is complete.

• Greater quality final product.

Palm Database Document

Drawbacks• Special

Training.• Greater

learning curve for users.

• Field crew’s level of detail is visibly displayed whether good or bad.

Hours / Job Palm Hand Written Position Hourly RateField Work 267 481 Field Tech 21.00$ Retyping hand written forms 240 Administrative assistant 16.00$ Inserting forms into books 40 Intern 12.00$ Database development 40 Programmer 35.00$

Palm Hand Written SavingsTotal Hours 307 761 60%Total Cost 7,007$ 14,419$ 51%

Comparison and Savings between Electronic and Hand Written Data

Collection.Parcels / Day Palm Hand WrittenField Work 45 25Retyping hand written forms 0 50Inserting forms into books 0 300

Total Parcels

1502

Related Benefits1. Less people handling information relates to a higher quality product.2. Realistic deliverable 1 cd -vs- 13 3-inch binders3. Ability to sort specific information due to standardized inputs.4. Ability to generate reports relative to each client's particular need.5. Ability to attach a photo with pertinent data.6. Improved ability to check work for accuracy.7. Database development was more extensive in this case because it was our 1st project.8. Newer databases need approx 50% less work.

Note: Now that the client has increased ability to work with the data they will ask for extra database items. Therefore, don't reduce programmer time.

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.

Case Study: I-70/71

Existing Utility Location– Subsurface Utility Engineering (SUE)– Sewerage/Drainage

Project Approach

Combine SurveyData with GIS DataCollection methodsto produce a finalproduct withmaximum quality inminimal time.

707802.19, 1873544.62

987.12

70-71 MANHOLE INVENTORY

NAVD881000 STORM MH

1

2

24” RCP

1000 STORM MH

8.10 1001

09-11-08

707802.19, 1873544.62 RH/RK

CONC

987.12

STEEL

GOOD

70-71 MANHOLE INVENTORY

NOTRASH & SILT

24” RCP 8.42

NAVD88N

24” NE RCP

1000 STORM MH

8.10 1001

DIR

09-11-08

707802.19, 1873544.62 RH/RK

CONC

987.12

STEEL

GOOD

70-71 MANHOLE INVENTORY

NOTRASH & SILT

24” S RCP 8.42

NAVD881

2

N

GIS Data Collection Advantages

• Upload coordinates for navigation• Customized drop-down menus• No lost, damaged, or illegible forms• Downloadable information

GIS-Grade GPS

• Fast and effective– Navigation– Inventory

• Low accuracy– 30 feet un-processed– 1-3 feet post-processed

(using CORS)

Survey-Grade GPS

• Static (~0.03’)– Must Post-Process

Survey-Grade GPS

• Static (~0.03’)– Must Post-Process

• RTK (~0.10’)– Base Station

& Radio Waves– No Post-Processing

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

Step 1: Survey• Search for approximately 1900 structures

– 770 located previously during SUE work• Obtain accurate coordinates

Step 2: Report• Structure details & condition• Pipe information

– Direction, size, material, depth, connection• GIS-Grade GPS coordinate

• Sewer Database spreadsheet (Excel)– Survey coordinates and GIS report data

• Compare GIS and survey coordinates• Calculate pipe invert elevations

Step 3: Assemble

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

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

Structure Location

Structure Information

Pipe Information

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

Pipe Point FilePOINT NORTHING EASTING ELEV

CODE30000 711769.45 1827261.58 696.27

BL*P130001 711778.66 1827277.52 696.27

EL*P130002 711769.45 1827261.58 696.24

BL*P230003 711778.29 1827093.73 695.56

EL*P230004 711798.41 1827232.98 710.24

BL*P330005 711792.29 1827244.84 709.55

EL*P330006 711792.94 1827113.96 0.00

BL*P430007 711792.29 1827244.84 708.36

EL*P430008 711792.94 1827113.96 704.57

BL*P530009 711787.09 1827114.39 704.45

EL*P530010 711787.09 1827114.39 702.07

BL*P630011 711786.62 1827092.33 701.14

EL*P630012 711787.09 1827114.39 704.29

BL*P730013 711424.05 1827187.41 703.43

EL*P7

Highlights

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

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

THANKS!Ron Howard Jr., EI

Environmental Coordinator

Russell Koenig, PS, EISurveyor

DLZ Ohio, Inc.6121 huntley RoadColumbus, Ohio 43229614-888-0040