topic Choropleth Map - Fire Department Response Data in Public Safety Questions

Choropleth Map - Fire Department Response Data

BrentVan_Scoy__Fire_ — Mon, 23 Mar 2015 01:58:52 GMT

Hello,

I am in the 4th week of the "Going Places with spatial analysis" and I have a follow up questions pertaining to fire department response data. As we learned in the class, to create a choropleth map it is best to normalize the data for an accurate comparison between areas. They mention with crime data, you would count the number of calls and then divide by the area. I am not sure what that means.

Any suggestion on how to properly normalize my fire response data in order to use in a choropleth map?

Thanks,

Brent

Re: Choropleth Map - Fire Department Response Data

RobinPatton2 — Thu, 26 Mar 2015 20:18:50 GMT

Hi Brent

I am an analyst for a Fire Department and most of the time we normalize our incident data by population in a specified area. We determine the population in a particular response zone and then divide the number of incidents for the same zone by the population - most people call this "per capita" information. AGOL enrichment tools can help with the population determination and take you even further by letting you explore additional data like housing type and median age or income.

Re: Choropleth Map - Fire Department Response Data

BrentVan_Scoy__Fire_ — Thu, 26 Mar 2015 23:30:17 GMT

Hi Robin,

I will give that a try. I just normalized it by square miles, but I like the idea of the population also.

Thank you for the reply.

Brent

Omaha Fire Department

Re: Choropleth Map - Fire Department Response Data

hhet — Fri, 27 Mar 2015 19:05:46 GMT

dividing a total "count" by an areal extent will give you a relative measure of your variable.

the final units are aka density.Density is a relationship.

in arcGIS 10.1 , you use Layer Properties to draw quantities using symbol size to show relative value by chooosing the appropriate fields for both Value and Normaliztion.

Larger areas may or may not influence the numerical values you want to classify. What you are doing in this calcaulation is deriving spatially intensive data from spatially extensive data. dividing one sum (as in, summary statistic) by another sum will yield you a spatially independent (of size) unit. Note that areas and perimenters are also considered summary statistics.

if you split the areal unit and recalulate (but first you make the basic assumption that the counts are uniformly distributed across the area), the density value will remain the same as before but the counts and the area will not say the same. Proportions, though calulated differently than density, are also spatially extensive.

spatially extensive data should not be used to symbolize a chorolpleth map although this mistake is made over and over again by the uninitiated

Re: Choropleth Map - Fire Department Response Data

BrentVan_Scoy__Fire_ — Sat, 28 Mar 2015 18:49:11 GMT

Yes is a fantastic response. I recall reading the intensive data verus extensive data in an article this week.

Understanding Statistical Data for Mapping Purposes

I will have to go back and compare what you are describing as it pertains to fire departement response data.

Thank you for the comments.

Brent