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Advanced Hotspot Analysis Course Information
Course Dates

3 May 2012

Venue Details

Contact

Catherine Wheatcroft
Email: c.wheatcroft@ucl.ac.uk
Tel: +44 (0)20 3108 3206




Advanced Hotspot Analysis

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Advanced hotspot analysis (1 day GIS-based course for users of MapInfo, ArcView, ArcGIS, or Cadcorp SIS)

“‘Fantastic – has really strengthened my spatial analysis skills’” Police Intelligence Analyst

This one day hands on GIS-based training course aims to further develop the skills an experienced intelligence/crime/community safety analyst has for understanding hotspots by introducing several advanced techniques that can assist them explore spatial patterns in crime data.  In particular, the course aims to develop the analyst’s skills in spatial statistical techniques that provide a means of testing for significance (i.e. testing and observing in statistical terms whether a geographic pattern is particularly unusual).  The course may introduce new techniques and demystify others, with the aim of exploring their practical application for understanding hotspots.

The course is held at our offices in London, but can also be delivered at your site for a minimum of 6 staff.

Advanced hotspot analysis (1 day GIS-based course for users of MapInfo, ArcView, ArcGIS, or Cadcorp SIS)

Aimed at: Police and CSP analysts, researchers and information officers
Interest groups: hotspots, spatial statistics, spatial significance, spatial autocorrelation, spatial association, Local Indicators of Spatial Association, dual kernel density estimation

Entry Requirements: At least a foundation in GIS software and already experienced in using KDE. The course is only suitable to users of Mapinfo, ArcView, ArcGIS, or Cadcorp SIS.


Methods and techniques that are taught on the course include,

  • Clustering techniques that use a secondary variable:  Techniques such as dual kernel density estimation and the Geographical Analysis Machine allow for a secondary variable (e.g. population) to be considered in determining hotspots.  That is, these techniques can be used to identify hotspots based on not only the distribution of crime, but how the underlying population influences this spatial distribution.  We explore dual KDE and its practical application.
  • Spatial autocorrelation techniques: Moran’s I and Geary’s C – these spatial statistical techniques provide a means of exploring whether the distributions of crime (or other event data) are related to each other.  Each technique is tested and their practical application is discussed.
  • The K and L functions – these second order spatial statistics explore certain spatial qualities of crime data beyond which can be discerned by first-order tests such as the nearest neighbour index.  The module explores their utility for determining the distance at which spatial association between crime points remains significant, and how they can be used to help expose how crime patterns have changed over time, and how patterns differ between crime types
  • Local Indicators of Spatial Association: Local Moran’s I, Local Geary’s C, and the Getis and Ord Gi and Gi* statistics – this new breed of spatial statistics provides a means of extending beyond methods such as kernel density estimation by identifying (in map form) those areas where the clustering of crime points is significant.  That is, they can determine areas that can be statistically defined as hot from those that are not, plus rank each hotspot according to significance thresholds (i.e. 95%, 99%, 99.9%).  This module guides the delegate through these techniques and discusses their practical application.


Some of the functionality we teach on the course is not available in standard GIS packages.  ArcGIS v9.3 and above has the functionality for most of what we teach on this course.  We therefore make use of freeware software that includes CrimeStat and RooksCase to perform some of the analytical techniques, displaying the results in your preferred GIS.

Course tutor:
Spencer Chainey

Advanced hotspot analysis (1 day GIS-based course for users of MapInfo, ArcView, ArcGIS, or Cadcorp SIS)

9.30am - 9.40am
Welcome and introduction
9.40am - 10.30am

Risk based clustering techniques

-Clustering techniques that use a secondary variable

BREAK
 
10.50am - 11.30am
Spatial autocorrelation techniques: Moran’s I and Geary’s C
11.30am - 12.30pm
The K and L functions
LUNCH
 
1.40pm - 3.00pm

Local Indicators of Spatial Association

-Local Moran’s I and Local Geary’s C

Local Indicators of Spatial Association

-Getis and Ord Gi and Gi* statistics

BREAK
 
3.20pm - 4.45pm

Local Indicators of Spatial Association

-Getis and Ord Gi and Gi* statistics

4.45pm
Summary and finish

May, 2010
“Very useful, especially the edge effects stuff!”  Partnership Analyst

February, 2010

“Very well structured and delivered.”

“One of the few courses I’ve been on where I feel I can easily apply the skills and techniques to real world problems in the office.”  Julia West+

“The tutor takes time to make sure you understand each section.” O Ducran

December, 2009

“In a word – ‘excellent’.”  Police Analyst

“Excellent course, well presented.” Police Analyst

“Fantastic – has really strengthened my spatial analysis skills” Police
Intelligence Analyst

Course Dates:

3 May 2012; 27 September 2012

Course Cost

£425 per delegate

Group discount: 10% discount for bookings of two or more.  To qualify, all group delegates must be booked at the same time.

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Page last modified on 14 oct 10 12:45 by Nicola M Roberts