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Becoming the Mad Scientists of Geocoding…

Becoming the Mad Scientists of Geocoding…. Hi! I’m Brooke Gajownik. Hi! I’m Mike Morris. Outline. The science of geocoding Using your powers for good examples Cleaning up eccentric data Diabolical use of address locators Steps for taking over the world with geocoding

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Becoming the Mad Scientists of Geocoding…

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  1. Becoming the Mad Scientists of Geocoding…

  2. Hi! I’m Brooke Gajownik

  3. Hi! I’m Mike Morris

  4. Outline • The science of geocoding • Using your powers for good examples • Cleaning up eccentric data • Diabolical use of address locators • Steps for taking over the world with geocoding • Questioning authority

  5. The Science of Geocoding • What is it? • a GIS operation for converting street addresses into spatial data as features on a map, usually by referencing address information from a street segment data layer. (source: ESRI knowledge base GIS dictionary) • What do you need? • A table of addresses and a reason!

  6. Using your powers for good examples • Sewer Billing • Map all customers • Track the areas that don’t have customers • Find homes that are not paying • Increase revenue • Public Safety • Useful to track past & future changes for investigations (burglaries, prowlers, thefts, etc.) • Sex offender work and home locations • Community corrections monitoring

  7. Cleaning up eccentric data • Clean up unknowns, bad data, suffix’s. etc first • Think about State Roads that use alternate names and using apartment numbers (or not) • For nationwide data (not local) use address locator style – US Streets with City State Zip. • Populate unassigned zip codes • Performance tip: best when address table resides on client machine.

  8. Unusual suffix decisions When in doubt or for additional help, consult www.nena.org

  9. What ESRI says about locators

  10. Diabolical use of address locators

  11. Diabolical use of composite locators

  12. Steps for taking over the world with geocoding • How to get the highest address match rates? • Use a composite locator • Rematch interactively • Set minimum match score higher • Do exactly what we say! Watch and learn

  13. Refining your selections A- Automatically matched or rematched M- Manually matched or unmatched by using buttons PP- Picked by Point (match to clicked point) PA – Picked by Address (match to closest address)

  14. Geocoding apartments

  15. Always question authority Q & A time….

  16. For additional information: Brooke Gajownik, GISP 317-776-2461 Brooke.Gajownik@hamiltoncounty.in.gov Or Mike Morris, GISP 317-770-5134 Mmorris@noblesville.in.us

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