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Scarc 2013 jack_beers_lynnewest_laurenscnty
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Scarc 2013 jack_beers_lynnewest_laurenscnty

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  • LYNNBefore GIS…We had large paper mapsThere were no digital sources of dataThere was very little detailHard to imagine…but many voters cannot always tell you where they live!!! Especially by pinpointing on an old wall map.…this made it very hard to find Registered Voter Locations
  • LYNNMany addresses on maps were in the wrong locationThis led to voters being placed in the wrong location and wrong district…..Even WorseWe faced the Census and Mandatory Re-Districting of Most Voting DistrictsHouse of Representatives Collapsed a DistrictCounty Council Districts changed as wellIt took TIME to correct the voter locations in the State databaseWe had limited time to move all 35,000 + voters to the current and LEGAL voting districts…Led to many Disgruntled Voters
  • LYNNWith the Local Government Template already in place in Laurens CountyWe began with updating our district layers and overlaying them onto the old districtsWe could now easily see which streets were involved in the changesWe could now easily see what address ranges needed to be correctedWe Realized that MANY, MANY more voters were, in fact, assigned to the wrong voting district than originally thoughtWith Limited time before the 2012 Elections….WE WERE IN TROUBLEWe needed a solution… {{{{{TRANSITION TO JACK}}}}}}
  • JACKWe needed to devise a plan of attack that would allow Lynn to visually identify the problem votersLIST PROBLEMSWe came up with a simple workflow that allow us to link the state database to GIS address points and the correct locations:We knew we had to geocode the votersThis allowed Lynn to view all voters not assigned correctly due to spelling errors and street names that didn’t match between the state database and Laurens County DataNext we had to compare the geocoded voters to the voting districtsThis allowed Lynn to visually see voters not assigned to the correct voting district/precinct and why they were not assigned correctly.The end result would need to be simple enough to an end user with limited GIS experienceCreated Point Feature Classes that showed unmatched geocoded voters and unmatched voters compared to each district/precinctCreated Printable reports using ArcGIS’s Report Wizard that allowed Lynn to distribute the QA/QC workload throughout the organization
  • JACKTo Geocode the voters from the State’s Voter Mass Query Export:We had to import into GIS as a Database TableThen combined the address number and street name into one fieldThis allowed us to geocode the field using Laurens County’s Composite Geocoder which also use a combined address number and street name field.It was important that Laurens already had a composite geocoder in place because in order for this to work, we needed accuracy of both addresses and street ranges
  • JACKThe Results helped us identify many of the addressing issues and why many voters were not registered to the correct districtMost unmatched voters were do to address spelling in State Database compared to spelling in County DatabaseTrinity Church Rd would be Trinity Ch in County database so it could fit onto a road sign, and because the misspelling was greater than allowed in the geocoder, it didn’t match at all.Lower Percentage partial matches had to do with Address number miss-matchesHigher Scoring partial matches were generally misspelling with correct address number
  • JACKThe Next step was to compare the geocoded voters to the voting district polygonsIn order to compare, we deployed a few spatial joins that allowed us select and export voters that didn’t match the state databaseThe output was a point with name, address, state assigned district and the GIS geocoded districtLynn could now compare the wrong state assigned district to the actual geocoded district location for which the voter should be voting
  • JACKLynn needed to identify all roads and address ranges that needed to be updated in the state database.She wouldn’t be able to identify them all herself, so we deployed ArcGIS Desktop’s Reporting wizardLynn could now distribute the reports to multiple personnel to make a list of all address ranges and streets that needed to be updated in the state databaseThese reports showed…
  • JACKLynn could also visually inspect data spatially within GIS to find errors such as address ranges or street miss-spellingsOr could be just that the registered voters were voting in the wrong district due to never being moved after re-districting
  • LYNNThe results were simple but effective, we could now easily identify address errors, zip code errors and simple typosAnd the Elections office received some really nice publicity….Having ZERO issues on Election Day, we were celebrated in the local newspaper
  • LYNNConfidenceCleaning up City of Clinton errorsCleaning up school district errorsNew ballot stylesFuture precinct splits
  • LYNNThe public can also view updates on the County GIS Website using the Voter Registration Widget…………Any Questions……..

Scarc 2013 jack_beers_lynnewest_laurenscnty Presentation Transcript

  • 1. The Ins and Outs of Redistricting: ModelingErrors for QA/QCLynn WestLaurens CountyVoter Registration and ElectionsJack BeersURS
  • 2. Before GIS…Hard to Find Registered Voter LocationVeryLittleDetailNoDigitalMapsLargePaperMaps
  • 3. Before GIS…DisgruntledVotersTIMERegisteredto WrongDistrict
  • 4. Then there was…GIS Access to County Data Addresses Roads Geocoders Digital Voting Districts/Precincts ESRI’s Local Government Template
  • 5. QA/QCProblem• Identify voters not assigned to the correct district• Identify voters not assigned to any of the given districts• Limited amount of time due to the ensuing 2012 electionsWorkflow• Geocode addresses from state database• Compare the geocoded voters to voting districtsResult• Point Feature Classes with:• Unmatched geocoded voters• Unmatched geocoded voters per each district• Printable reports listing each error
  • 6. Workflow: Geocode Voters
  • 7. Geocoded Voters Results Out of 35,737 Registered Voters 713: Unmatched 473: Partial Matches 34,551: 100% Matches
  • 8. Workflow:Compare Voters
  • 9. ReportsGeocoded VotersError ReportVoting PrecinctError Report
  • 10. Visual Inspection
  • 11. Results We can now easily identify: Addressing errors Zip code errors Simple typos ZERO district issues on General Election Day 2012 Unheard of Elections Office was celebrated in the local Newspaper
  • 12. Moving Forward… Confidence to discuss concerns with voters on wherethey are voting and who they are voting for Cleaning up City of Clinton errors from re-districtingof cleared DOJ council seat lines Cleaning up school district errors that were neverimplemented after the last piece of legislation New Ballot Styles Future Precinct Splits
  • 13. QUESTIONS?www.laurenscountygis.org