Advanced GIS Methods Training: AHAH and Multi-Dimensional Indices

This course presents the Access to Healthy Assets & Hazards (AHAH) dataset and the methods used to create them, multi-dimensional indices. Multi-dimensional indices are used to create many different data sets, including the Index of Multiple Deprivation. This course will explain the AHAH dataset, how and why it was created, and what it can be used for. You will also learn how to use the multi-dimensional indices method to create your own index, using AHAH as an example.

It is split into two parts, each with a video clip and a series of commands to work through:

  • Part 1: Access to Healthy Assets & Hazards (AHAH)
  • Part 2: Multi Dimensional Indices (MDI)

You need some prior knowledge of R to get the most from this course. If you are new to R, we recommend you complete the Short Course on Using R as a GIS first. Use the search box above to find this course.

After completing the material, you will:

  • Know what AHAH is and what it can be used for
  • Be aware of how AHAH was created
  • Understand some of its key strengths and weaknesses
  • Know how to use Access to Healthy Assets & Hazards (AHAH) in RStudio
  • Be able to recreate the AHAH MDI
  • Understand why we need to transform some of the data
  • Feel confident to add/remove domains from this index and understand the results
  • Be able to create your own multi dimensional index

To access the course, click on Download next to the 'Part 1: AHAH - Workbook' or 'Part 2: MDI - Workbook' files below. It is recommended that you have the course material open in one window, and RStudio open in another window next to it, using either a big monitor, or two monitors. If you have any comments or feedback, please email us.

This course is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International licence.

Tutorial

Data and Resources

Additional Info

Field Value
Source Office of National Statistics (ONS), NHS England, NHS Scotland, NHS Wales, OpenStreetMap, Sentinel Satellite, Local Data Company (LDC), Department of Environment, Food and Rural Affairs (DEFRA), DLUHC, OCSI, NISRA, Scottish Government, GeoDS
Author Bearman, Nick
Maintainer Mark Green
Last Updated May 8, 2025, 15:21 (UTC)
Created November 28, 2024, 13:15 (UTC)
Attribution The data for this research have been provided by the Geographic Data Service (geods.ac.uk), a Smart Data Research UK Investment: ES/Z504464/1.