Date(s) - 19/10/2018
9:30 am - 4:30 pm
Categories No Categories
This one-day course will follow a linear format, with a series of lectures and practical exercises leading attendees through the key steps involved in performing basic crime analysis in ArcGIS. Starting with an overview of environmental criminological theories, the course will also include information on: (i) accessing open source crime data, (ii) locating complementary data sets e.g. area boundary files, (iii) advantages/disadvantages of different data sources, (iv) importing crime data and spatial data into ArcMap, (v) mapping data and querying data in ArcMap, and (vi) interpreting results of analysis.
- Understand how spatio-temporal convergences can influence crime patterns
- Develop a critical awareness of different data sources
- Learn how to format data ready for analysis in a GIS
- Gain practical experience of working with ArcCatalog, ArcMap, and ArcToolbox
- Use mapping techniques to identify crime hot spots
- Consider how results might translate practically
This course is taught by Emily Sheard, a 3rd year PhD student at the University of Leeds. Having completed an MSc in GIS in 2015, Emily has demonstrated Geographical Information Systems on various undergraduate and postgraduate courses in the School of Geography, as well as those run by the Consumer Data Research Centre. Emily is particularly interested in how ‘new’ forms of data can be applied, in conjunction with open source software such as R, to emerging crime problems. Prior to returning to academia, Emily worked for a number of years as a police intelligence analyst, and for a lesser time as a retail analyst, and therefore has experience of working with both crime and incident data in a real-world setting.
Is this course for me?
This course is suitable for anyone wanting to perform basic crime analysis in ArcGIS. Attendees do not need to have any prior knowledge of geographical information systems, although basic computer skills are required.
Academic, public and charitable sector staff: £120
All others: £300