crime concentration index

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PALM MELROSE FOREST PARK OLIVE LAFAYETTE STAUNTON MARYLAND CRESCENT HANOVER 25TH HANOVER 31ST ORANGE 30TH 29TH 24TH 23RD SALEM SALEM ESSEX 30TH KEATS GLENGARY MILTON NAHO SHENANDOAH DELTA CENTRE 24TH 24TH CENTRE LOUDON 22ND ± BAKER BAKER 27TH JOHNSON 25TH 0 0.05 0.1 0.2 Miles BAKER
The Alternative • Using a 755-foot buffer, the same 22 robberies are captured • The area of the buffer calculated • A new CCI is computed based on the <strong>concentration</strong> per unit of area in the buffer • CCI=(22/0.198845)/(907/42.89)=5.23 • This suggests that there are a little more than 4 times as many robberies in this area
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Using Crime Concentration Indices i
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The map is not the territory. -Alfr
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Our Fair City
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± 0 1 2 4 Miles
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Crime Count Example LAX Inglewood-L
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Display as Graduated Colors ± Homi
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Selection: 184 Tracts Area in Sq Mi
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Illustration Dark & Bram, 2007
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Crime rates standardize crime count
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Crime rate Crime Rates Count of cri
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In ArcGIS, create a new Field • S
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Using the Field Calculator • This
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This is the LAX Tank Farm & support
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The Location Quotient • Location
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Unemployment Example LQ UE 12 local
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Crime Concentration Index • Both
Page 35 and 36: The original reference Brantingham,
Page 37 and 38: Robbery in Roanoke: Concentration b
Page 40: Use a spatial join to create a Coun
Page 44 and 45: Populate the new field…
Page 46 and 47: Add a new field for the CCI • We
Page 48 and 49: The Formula: CCI Robbery C C BG BG
Page 50 and 51: The Sorted CCIs
Page 52 and 53: Interpretation • The two highest
Page 54 and 55: ± 0 1 2 4 Miles Robbery Concentrat
Page 56 and 57: The Problem • The Commander of th
Page 58 and 59: The Process • First, develop a la
Page 60 and 61: The Field Calculator
Page 62: 1.663018 1.465418 1.297896 0.519309
Page 65 and 66: Neighborhood Organizations • Like
Page 67 and 68: Generating the Neighborhood CCI •
Page 69 and 70: The CCI Formula CCI ( Robbery AreaS
Page 71 and 72: The Results Only 10 out of the 41 a
Page 73 and 74: Drilling down for a micro-spatial a
Page 75 and 76: Getting started • Using the “Go
Page 77 and 78: Finish it up • Do a spatial join
Page 79 and 80: An application to a linear analysis
Page 81 and 82: PALM MELROSE FOREST PARK OLIVE LAFA
Page 83 and 84: The Results CCI (Robberies close to
Page 85: The Results • But, to be realisti
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