The 2018 Australian National Liveability Study was conducted between 2018 and 2020 in order to produce measure a suite of policy relevant spatial indicators of local neighbourhood liveability and amenity access for residential address points across Australia's 21 largest cities. The indicators and measures included encompassed liveability sub-domains including community and health services, employment, food, housing, public open space, transportation, walkability and overall liveability.
The resulting Australian National Liveability Study 2018 datasets have been published elsewhere, and additional supplementary material was created including data dictionaries, metadata and usage notes.
The calculation of this data required development of methods to support comparable methods for residential analysis across multiple cities, and the results have been supported planners and policy makers at multiple levels of government across Australia, as well as research concerned with the influence of the built and natural environment through linkage with a variety of special interest survey datasets (e.g. household travel, child and adolescent development, apartment dwellers, residents of new urban developments in growth areas, COVID19 patients).
The project was conducted between 2018 and 2020 using Python 2.7 with PostgreSQL 9.6, Postgis 2.4, the ArcGIS 10.6 arcpy python library and network analyst extension. The code also draws heavily on the psycopg2, sqlalchemy, pandas and osmnx libraries. The code was developed across the duration of the project to meet evolving stakeholder needs for data and indicators. Unfortunately across this period, software versions also evolved, and when a newer version of ArcGIS was installed in 2020 following expiry and renewal of institutional licences this required the use of Python 3. While this initially provided impetus to re-factor and update the code, project priorities within our research group changed and it became apparent this code would not be used in future projects, and there was not funding or scope to complete final code re-factoring. The exception to this was the ‘highlife’ project branch which contains code developed to create built environment measures targeting 2019 for the separate High Life study:this is the branch with the most recent and complete development efforts. As such, it has been set as the project's default branch. An incomplete re-factoring for Python 3 is located on the 'python3_2020 branch'; and the final main working branch of the overall project is the one titled 'main'.
Many lessons were learnt about managing large code projects through the course of this study 1, however the code for this project was left in a state where it would ideally be re-factored but with no team members having capacity to do so for this completed project. Project experiences meant that the team had broad desire to move towards more open source software solutions, for which the methods developed for this study were adapted and applied in other projects 234.
Footnotes
-
Higgs C, Alderton A, Rozek J, Adlakha D, Badland H, Boeing G, Both A, Cerin E, Chandrabose M, Gruyter CD, Gunn L, Livera AD, Hinckson E, Liu S, Mavoa S, Sallis J, Simons K, Giles-Corti B. Policy-Relevant Spatial Inidicators of Urban Liveability And Sustainability: Scaling From Local to Global. Urban Policy and Research. 2022 2022/12//;40(4). en. doi:10.1080/08111146.2022.2076215. ↩
-
Alderton A, Higgs C, Davern M, Butterworth I, Correia J, Nitvimol K, Badland H. Measuring and monitoring liveability in a low-to-middle income country: a proof-of-concept for Bangkok, Thailand and lessons from an international partnership. Cities & Health. 2020 2020/09/07/;5(3):320-328. doi:10.1080/23748834.2020.1813537. ↩
-
Liu S, Higgs C, Arundel J, Boeing G, Cerdera N, Moctezuma D, Cerin E, Adlakha D, Lowe M, Giles-Corti B. A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data. Geographical Analysis. 2021. en. doi:10.1111/gean.12290. ↩
-
Boeing G, Higgs C, Liu S, Giles-Corti B, Sallis JF, Cerin E, Lowe M, Adlakha D, Hinckson E, Moudon AV, Salvo D, Adams MA, Barrozo LV, Bozovic T, Delclòs-Alió X, Dygrýn J, Ferguson S, Gebel K, Ho TP, Lai P-C, Martori JC, Nitvimol K, Queralt A, Roberts JD, Sambo GH, Schipperijn J, Vale D, Van de Weghe N, Vich G, Arundel J. Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities. The Lancet Global Health. 2022 2022/06//;10(6):e907-e918. en. doi:10.1016/S2214-109X(22)00072-9. ↩