Techniques Used to Analyse the Affordability, Commutability and Demographics of Real Estate in School Catchment Areas

schedule May 7th 04:50 - 05:20 PM place Red Room
School catchments, otherwise known as priority placement areas or intake zones are a zone where children are entitled to enrol in a public school. Recent media coverage has drawn attention to the increased demands for residential real estate within high performing school catchments. While school catchment areas remain a controversial and influential factor in determining student enrolments, the impacts of school catchment areas on its local community is only recently being studied. This presentation will describe some of the analytical techniques used to analyse school catchment areas, as expressed as geospatial concepts as well as some of the results obtained from analysing school catchments across Australia. This analysis involved combining different spatial and non-spatial datasets across various jurisdictions. These geospatial analytical techniques were used to draw insights on the affordability, commutability and demographic changes that school catchments may have on urban environments. Urban environments and school catchments across Australia have been analysed. The insights obtained from this analysis could be used to influence property investment decisions for individuals, and policy decisions on:
- public housing locations,
- public transport infrastructure,
- school catchment area designs, and
- future school locations
for government agencies.
1 favorite thumb_down thumb_up 0 comments visibility_off  Remove from Watchlist visibility  Add to Watchlist

Outline/Structure of the Case Study

- Overview and context of school catchments

- Examples of school-related data sets

- School zone affordability

- School zone commutability

- School zone demographics

- Lessons learnt

Learning Outcome

- An awareness of open data sets available.

- Examples of spatial data analytical techniques used with real-world data.

- Techniques for merging multiple datasets into a single dataset for analysis.

Target Audience

Data analysts, particularly analysts who work with open data and/or spatial data.

Prerequisites for Attendees

Any of the following skills:

  • Data analytics, particularly an interest in spatial data sets
  • Spatial analytical techniques
  • Managing issues with merging multiple datasets

As this presentation is a case study, I will be including references to key documentation to allow further study on concepts covered.

schedule Submitted 2 months ago