CommunityLy: More Public Spaces

Project Info

Team SMAD thumbnail

Team Name


Team Members

Sai Valipireddy , Amit , Shub and 1 other member with an unpublished profile.

Project Description

CommunityLy is an application we have developed to enable NSW planning to identify sites for more public space developments.

CommunityLy sources the public spaces data from NSW planning resources. According to this dataset, there are more than 27000 public spaces in the state of NSW. It could be a challenging task to identify regions of lower public space availability by just surfing though a map interface.
CommunityLy provides an advanced analytics approach to identify potential areas of public space development. The analytics is surfaced on a map-based interface on CommunityLy.

To explain the analytics approach - We have sourced the population data from ABS using the ABS data API. The data is sourced at an SA2 level of aggregation. We have also sourced the SA2 geographical boundaries from ABS, which is currently not available through the API, but could easily be made available.
We have identified the number of different types of public spaces within each SA2's and have created a score of “public space counts” to “population” for all SA2s. The score is indexed against an average at the state level to normalise the values.

We can then plot these scores for a particular type of public space, and it becomes quite easy to understand regions of public space gaps. The lighter colored areas on the map indicate that the number of parks per population is significantly low in these regions.
We can switch between different types of public spaces to understand the gaps in each types. For example, this is the gap region identification for Picnic areas in NSW...

To further enhance the abilities of NSW planning in identifying opportunities to develop more public spaces, we have used the Zone map layer from NSW planning. The identified zones which are suitable for public space developments when plotted against the gaps in public spaces depict a clear picture for opportunities for development.
If we look at the Marsden park area in Greater Sydney, the number of parks per population ratio is quite low, once we plot the zonal information and select a zoned region, we can see the zoned land that could be utilised for Park development.

CommunityLy provides easily accessible information for all types of public space development and further planning information can be plotted to make the site discovery for necessary public space creation as easy as possible.

Data Story

Combining Points of interest data with population from ABS to get a good understanding of lack of public spaces for a given region.

ABS datasets:
Population -,ANNUAL_ERP_ASGS2016/all?format=csv
SA2 boundaries - ABS shape files
Points of interest/public spaces :
Zone layers : ABS shape files

Evidence of Work


Team DataSets

NSW planning and zoning

Description of Use Used to identify land zones ideal for public space development

Data Set

SA2 bounbdaries

Description of Use Used to link public spaces and population from ABS

Data Set

NSW Points of Interest (POI)

Description of Use Used to identify public spaces, location and type of public spaces. Also used to identify parking locations.

Data Set

Population at SA2 levels

Description of Use Used to merge with public spaces at SA2 levels to identify population to public space ratios

Data Set

Challenge Entries

MORE Public Spaces

How do we unlock underutilised government owned land and property to create new, high quality public space?

Go to Challenge | 9 teams have entered this challenge.

Create a solution to a customer need using the ABS Data API

We are excited to provide innovators with machine to machine access to ABS Data and see what exciting customer solutions can be created. Here is a chance to draw in ABS Data and answer an important question through visualisation, mapping or even blending with other data sources. Create a solution to a customer need using data drawn from the ABS Data API.

Go to Challenge | 20 teams have entered this challenge.