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March 1, 2011 Becoming the Mad Scientists of Geocoding…

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Presentation on theme: "March 1, 2011 Becoming the Mad Scientists of Geocoding…"— Presentation transcript:

1 March 1, 2011 Becoming the Mad Scientists of Geocoding…

2 Hi! I’m Brooke Gajownik

3 Hi! I’m Mike Morris

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

5 The Science of Geocoding ● 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 is it? ● 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

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14 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.

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

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17 What ESRI says about locators

18 Diabolical use of address locators

19 Diabolical use of composite locators

20 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

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22 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)

23 Geocoding apartments

24 Always question authority Q & A time….

25 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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