GHSCI policy and spatial indicators analysis and reporting example: Te Whanganui a Tara / Wellington, New Zealand

<p dir="ltr">This repository includes PDF and code versions of a notebook and accompanying configuration files and data designed to introduce applied usage of the <a href="https://doi.org/10.1177/23998083241292102" rel="noopener" target="_blank">Global Healthy and Sustainable City Indicators</a> (GHSCI) software to analyse and report on policy and spatial urban indicators for healthy and sustainable cities for Te Whanganui-a-Tara, Wellington, New Zealand. The example was developed for the 21st International Conference on Urban Health (ICUH 2025), hosted in Wellington on 17-21 November 2025.</p><blockquote><i>Higgs C, Lowe M, Turner R, Heikinheimo V, Adlakha D, Resendiz E, Boeing G, Liu S, Hinckson E, </i><i>Schipperijn J, Sallis J, Cerin E, Giles-Corti B. 2025. Policy and spatial indicators for healthy and sustainable cities in diverse urban contexts: tools for analysis and reporting.</i><i> </i><i>21st International Conference on Urban Health.</i><i> </i><i>Wellington, New Zealand. 19 November 2025.</i></blockquote><p dir="ltr">The resources for running this analysis include</p><ul><li>PDF / code notebook tutorial (<code>GHSCI_NZ_Wellington_demo.ipynb</code> / <code>.pdf</code>)</li><li>Example configuration files (<code>NZ_Wellington_2025_*</code><code>.yml</code>)</li><li>Data (inputs and output resources including reports generated as a result of running the analysis)</li></ul><p dir="ltr">The analyses included in the example are defined in the following configuration (<code>.yml</code>) files for analysing spatial healthy cities indicators of the urban region of Wellington using three different official population datasets published by Stats NZ (respectively SA1 administrative counts, a 250m grid, and a 1km grid):</p><ul><li><code>NZ_Wellington_2025_SA1.yml</code></li><li><code>NZ_Wellington_2025_250m.yml</code></li><li><code>NZ_Wellington_2025_1000m.yml</code></li></ul><p dir="ltr">Repeating analyses using different datasets or parameters can help us to better understand the implications of our choice of data for our results. This kind of sensitivity analysis is useful for understanding the degree to which results obtained are contingent on the methods used and assumptions about which data best represents urban realities.</p><p dir="ltr">To follow along with the tutorial,</p><ul><li>install Docker Desktop and the GHSCI software following our <a href="https://healthysustainablecities.github.io/global-indicators/2.-Spatial-indicators-and-reporting-software/" rel="noopener" target="_blank">Wiki directions</a></li><li>copy the above configuration files to the GHSCI software <code>process/configuration/regions/</code> sub-folder</li><li>copy the <code>GHSCI_NZ_Wellington_demo.ipynb</code> notebook file to the process folder</li><li>copy the <code>NZ</code> folder to the GHSCI software <code>process/data</code> sub-folder</li><li>run the GHSCI software according to the linked directions by entering 'lab' to start Jupyter Lab, and open the <code>GHSCI_NZ_Wellington_demo.ipynb</code>using the file browser.</li></ul><p dir="ltr">The input data includes a range of open datasets published under CC BY 4.0 licences, as detailed in the datasets.xlsx spreadsheet.</p>