http://creativecommons.org/licenses/by/3.0/au/ © Commonwealth of Australia (Department of Sustainability,
Environment, Water, Population and Communities) 2012
Photos on cover courtesy of John Baker and John Houldsworth

Executive Summary ........................................................................................................................ 1
1. Introduction ................................................................................................................................. 2
2. Methods ...................................................................................................................................... 3
2.1 Data issues and resolutions ................................................................................................ 3
2.2 Determining distance........................................................................................................... 5
3. Results........................................................................................................................................ 6
4. Discussion .................................................................................................................................. 9
5. Areas for improvement .............................................................................................................. 11
6. Opportunities ............................................................................................................................ 11
7. References ............................................................................................................................... 12
8. Data acknowledgments ............................................................................................................. 12

Tables
T
ABLE
1. D
IRECT DISTANCE COMPARISON BETWEEN
L
OCAL
G
OVERNMENT
A
REAS AND INTERNATIONAL
STANDARDS ............................................................................................................................... 8
T ABLE 2. N ETWORK DISTANCE COMPARISON BETWEEN L OCAL G OVERNMENT A REAS AND
INTERNATIONAL STANDARDS ....................................................................................................... 8
Figures
F IGURE 1. E XAMPLE OF INCREASED NETW ORK CONNECTIVITY USING CADASTRAL PARCELS UNDERLYING
ABS "P ARKLAND " M ESH B LOCKS . .............................................................................................. 4
F IGURE 2. C OMPARISON OF AVERAGE NETWORK AND AVERAGE DIRECT DISTANCE TO G REENSPACE ...... 6
F IGURE 3. C OMPARISON OF MAXIMUM NETWORK AND MAXIMUM DIRECT DISTANCE TO G REENSPACE ...... 6
F IGURE 4. C UMULATIVE PERCENTAGE OF G-NAF ADDRESSES BY DIRECT DISTANCE TO G REENSPACE IN
THE L OWER H UNTER .................................................................................................................. 7
F IGURE 5. C UMULATIVE PERCENTAGE OF G-NAF ADDRESSES BY NETWORK DISTANCE TO G REENSPACE
IN THE L OWER H UNTER .............................................................................................................. 7
F IGURE 6. L OWER H UNTER COMPARISON WITH INTERNATIONAL STANDARDS ...................................... 10

Open spaces can play a vital role in the physical and psychological health of urban communities.
They provide areas for recreation, exercise and socialising. Additionally, these areas can provide valuable contributions to the surrounding ecosystems. Two terms commonly used to group urban spaces which support the above functions are “Open space” and “Greenspace”. These terms are currently used interchangeably by the Department of Sustainability, Environment, Water,
Populations and Communities. This is reasonable considering that within existing definitions these two terms share many commonalities. One suggestion to differentiate between these terms is to consider Greenspace as the vegetated subset of Open space, where Open space includes all publicly available space. The following report uses the term Greenspace as the data available is closely aligned with the concepts stated above.
This report focuses on the Lower Hunter region which includes the Local Government Areas of
Cessnock, Lake Macquarie, Maitland, Newcastle and Port Stephens, as the pilot study location. It delivers a direct distance to Greenspace as well as a network distance to Greenspace for every
G-NAF address within the region. Options are explored to improve the data used for this analysis, improvements have been achieved for the Geocoded National Address File ( G-NAF) address system as well as the Greenspace layers.
Proximity to Open space is a metric which has been used by policy makers internationally. Existing maximum distance standards of 400 metres and 800 metres are used in the United States (US) and United Kingdom (UK) respectively. These distances are vestiges of early 20 th century practices and may need to be revised to reflect current mobility trends. In both these jurisdictions, proximity to Open space is used in conjunction with a measure of area of open space per person. This concept has not been explored further in this report and has not been included in the analysis.
The analysis undertaken for the report does highlight areas of advantage, however due to the quality of the data, definite conclusions on areas of disadvantage cannot be made. These areas should be considered for further investigation to ensure that perceived disadvantage is not caused by other factors, such as unidentified Greenspaces or peri-urban locations where Open space requirements may to some extent be fulfilled by private open spaces.
Note: Standardised definitions for Open space and Greenspace have not yet been established within the department and the two terms are often used interchangeably. Open space is a very general term that can be adapted to suit a variety of different planning needs and existing definitions reflect these needs. A broad definition can include any publicly accessible area that is used to fulfil the physical, recreational or social needs of the community. Greenspace can be seen as a subset of Open space, where non-vegetated Open spaces are excluded. This report uses
Australian Bureau of Statistics (ABS) “Parkland” Mesh Blocks as a surrogate for Open space boundaries. These Mesh Blocks align with the concept of Greenspace as a subset of Open space and hence the term Greenspace is used throughout this report.
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The benefits of Greenspaces to the communities they service have been well established. They provide communities with areas to undertake recreational activities, socialise and exercise which enhances physical (Godbey et al, 2005) as well as psychological health (Kaplan, 1995). In addition to providing for the communities, Greenspaces can provide vital refuges for native species and may potentially serve as stepping stones in a continuous urban forest (Marulli and Mallarach,
2004).
Providing adequate levels of Greenspace within urban environments is a common problem faced by urban planners and standards have been developed to tackle this issue. There are multiple approaches to standardising the Greenspace needs of a community. Some of the earliest methods were to define a standard maximum distance to Greenspace or calculate the area of Greenspace required per head of population. The option to set aside a percentage of the area for any new development was later adopted by some jurisdictions (Byrne and Sipe, 2010).
The US and UK officially implemented Greenspace standards of
10 acres per 1000 residents at a maxim um ¼ mile (400m) distance and 4 acres per 1000 residents at a maximum of ½ mile (800m) distance respectively in the latter half of the 20 th century (Byrne and Sipe, 2010). This is not the case in Australia where the concept of distance to Greenspace has not been adopted. Instead, Australian standards of 7 acres per 1000 residents have been in place since the 1940s, with variation to this in Queensland which has standards of
10-12.5 acres per 1000 residents and Western Australia, which implemented a different policy of retaining 10 per cent of any subdivision as Greenspace (Byrne and Sipe, 2010; Western Australian
Planning Commission, 2002).
The use of distance and area standards can be criticised for emphasising quantitative measures of
Greenspace whilst ignoring qualitative measures, leading to bland Greenspaces which do not fulfil the requirements of communities they service and may therefore be underused (Byrne and Sipe,
2010). This concept could be extended to include qualitative measures of the ecological services that these Greenspaces can provide for the surrounding environment. However, ensuring that quantitative standards are met provides a strong platform on which to focus on qualitative requirements.
Using the Esri ArcGIS program package, this report aims to determine how well the Lower Hunter region conforms to existing international standards for proximity to Greenspace.
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This analysis focussed on using a Geographic Information Systems (GIS) to determine proximity of urban cadastral parcels to Greenspace within the five LGAs located in the Lower Hunter region. To achieve this, Public Sector Mapping Agencies (PSMA) and Australian Bureau of Statistics (ABS)
Mesh Block data was used. The PSMA Geocoded National Address File (G-NAF) along with
PSMA CadLite ® cadastral data were used to determine the location and number of addresses within the Lower Hunter region. PSMA
“Greenspace” and ABS
“Mesh Block - Parkland” data were compared to determine which best represented Greenspace.
The PSMA Greenspace dataset is comprised of a mosaic of polygons and their legal identifiers as provided by individual Australian states and territories (PSMA 2012). This leads to variation in the dataset based on the differing interpretations of Greenspace between jurisdictions. As this analysis needs to be reproducible in other regions, it was decided that the ABS Mesh Block data was more suited to this project as it is more consistent than PSMA data. PSMA “Roads” data was also used in this analysis and formed the basis for measuring network distance to Greenspace.
2.1 Data issues and resolutions
2.1.1 G-NAF data
It was noted that there were issues with the version of G-NAF data that was used during this project, most notably that an entire suburb had been removed in the target region. Therefore, a method was developed to automate the process of filling in any detectable data gap. This was achieved by combining aspects from several different datasets PSMA G-NAF, PSMA CadLite ® and ABS Mesh Block data. New address points were generated by using centroids from cadastral plots that conformed to the dimensions of average suburban plots within the target region. The criteria for detecting these additional blocks were quite strict. Cadastral parcels without an existing
G-NAF address were selected. From these, cadastral blocks with a perimeter to area ratio of less than 1:3 were extracted and the following equation was used to determine this ratio:
(Perimeter/4)/Sqrt(Area) :1
This ratio is based on the relationship of the perimeter and area of a square wher e ¼ of the perimeter is equal to the square root of the area. As the perimeter increases in relation to the area, the polygon represented becomes longer and thinner, this increases to the point where cadastral blocks no longer conform to regular household blocks. It was noted that using this ratio would exclude battleaxe blocks and also does not hold true for larger suburban and peri-urban blocks.
The loss of battleaxe blocks was not seen as a major risk as these are relatively rare and would likely be represented by the G-NAF data.
A size limit of one acre was also implemented to maintain a focus on urban zones. These blocks were further whittled back by removing all blocks smaller than 250 m
2
, under the rationale that this would reduce the chance that non-residential remnants or slivers would be included in the final data. Again, the risk of removing valid residential blocks was considered small as these would
3 Lower Hunter Open Space | Final

likely be represented by the G-NAF data. These remaining blocks were further reduced by removing blocks which intersected with PSMA “Roads”, “Rail” or “Drainage” data, as well as removing all blocks apart from those whose centroids were located within ABS “ Residential ” Mesh blocks. A random subset of these blocks was then compared to satellite imagery of the region to gauge how well these additional blocks represented residential addresses. Centroids for these remaining cadastral parcels were given new unique address IDs and added to the G-NAF data.
2.1.2 Mesh Block Parkland
ABS Mesh Blocks are the base units used in Australian Statistical Geography Standards (ASGS).
They provide the building blocks for all larger regions of the ASGS and can also be aggregated into non-ABS Structures, including but not limited to Local Government Areas, Postal Areas, State
Suburbs and Natural Resource Management Regions (ABS, 2011). Although ABS Mesh Blocks have been assigned land use categories, the main focus is on creating blocks with similar attributes which can be aggregated to generate demographic statistics.
Mesh Blocks themselves are based on aggregations of cadastral parcels. In doing so, the ABS
(2011) has stated “Where practical, Mesh Block boundaries do not cross cadastral boundaries.
Essentially Mesh Blocks are designed to be an aggregation of land parcels.
” While the aim is to avoid cutting across cadastral parcels this is in some cases unavoidable, and as the focus for the
ABS is directed at collecting demographic data it is more likely that other cadastral parcels of lower perceived importance, such as parkland data, would be more likely to be cut. The results of this can be seen below (Figure 1), where the cadastral parcel representing the “Parkland” extends to include the access pathway between residential blocks.
By using the extent of the cadastral parcels to define parklands (see Figure 1), we can improve the connectivity for the network analysis (black circles). Even so, there are areas where this method will not affect connectivity and there is no effect on the network analysis (black squares). It is interesting to note that the black square on the lower edge of the Greenspace polygon is an example of a battleaxe block which was overlooked during the G-NAF data improvement process
(Subsequent investigation using Google Earth imagery confirmed this).
Figure 1. . Example of increased network connectivity using cadastral parcels underlying ABS "Parkland" Mesh Blocks.
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2.2 Determining distance
Two separate methods were used to measure distance from Greenspace. These were to measure direct “ as the crow flies ” distance to Greenspace and to network “along roads and paths” distance.
Both methods were undertaken as there is a significant difference in the level of technical difficulty posed by each the two analyses. The direct distance method is fast and simple but does not take into account various obstructions and detours between the target and the destination, while the network distance analysis simulates more realistic potential paths that can be taken to reach
Greenspace, it requires much more intensive processing.
2.2.1 Direct distance
The direct distance to Greenspace was measured using the “near” tool in ArcGIS from the G-NAF address points to the edge of the nearest ABS “Parkland” Mesh Blocks.
2.2.2 Network distance
An Origin/Destination (OD) analysis was performed to determine the distance along a network. In this case the PSMA roads dataset was used as the basis for the network. It is noted that this dataset is not comprehensive but includes many of the potential pathways to reach Greenspace.
During the OD analysis all features are allocated a point on the nearest segment of the network, therefore during the analysis the distance between the feature and the network is not factored into the total distance estimates. This isn ’t considered to be a problem as it is assumed that the majority of residential G-NAF addresses would be quite well represented by this singular point.
The method to generate the destinations was more complicated as Greenspace polygons are too large to be adequately represented by a single point. Additionally, because the network analysis automatically assigns the feature a position on the nearest network segment, it effectively reduces access to that Greenspace feature down to one point on the network. This also does n’t take into account obstacles which would preclude segments of the network from being suitable as access points.
To overcome this issue, points were generated every 10 metres along the edge of the Greenspace polygon and assigned an ID identical to the parent feature. The distance of 10 metres was chosen to balance the need to maintain accuracy, whilst factoring in processing limitations during the analysis. To reduce the size of the destination dataset even further, all points greater than 20 metres from the network were excluded. A distance of 20 metres was chosen under the assumption that in general, Greenspace within this distance of the network will be accessible by pedestrians from the network.
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Figures 2 and 3 below show a comparison of the average and maximum direct distance as well as the average and maximum network distance to Greenspace by Local Government Areas (LGAs).
As expected, the direct distance is noticeably shorter than the distance along a network.
Interestingly, there is a high level of variation in distance to Greenspace between the five LGAs used in this analysis. This variation holds true whether we are looking at the direct distance or the network distance.
)
1000
900
800
700
600
500
400
300
200
100
0
Cessnock Lake
Macquarie
Maitland Newcastle Port
Stephens
Average network distance
Average direct distance
Figure 2. Comparison of average network and average direct distance to Greenspace
12000
10000
) 8000
6000
Maximum network distance
Maximum direct distance
4000
2000
0
Cessnock Lake
Macquarie
Maitland Newcastle Port
Stephens
Figure 3. Comparison of maximum network and maximum direct distance to Greenspace
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The large discrepancy between the average distance and the maximum distance suggests that these maximum distance measurements may consist of outlier points. This is shown in Figures 4 and 5, where 90 per cent of the G-NAF addresses are located within 500 metres of a Greenspace as measuredby direct distance and 800 metres of a Greenspace as measured by network distance.
100
90
80
70
60
50
40
30
20
10
0
0 5 10 15 20 25
Distance to Greenspace (x100m)
30 35 40
Figure 4. Cumulative percentage of G-NAF addresses by direct distance to Greenspace in the Lower Hunter
100
90
80
70
60
50
40
30
20
10
0
0 5 10 15 20 25
Distance to Greenspace (x 100m)
30 35 40
Figure 5. Cumulative percentage of G-NAF addresses by network distance to Greenspace in the Lower Hunter
7 Lower Hunter Open Space | Final

Tables 1 and 2 below show how the five LGAs of the Lower Hunter compare when looking at the percentage of total G-NAF addresses which are within the international standards for distance to
Greenspace. From Table 1 we can determine that Newcastle is very well represented in terms of direct distance to Greenspace, with 99.99 per cent of G-NAF addresses occurring within 800m of a Greenspace. The other LGAs are also quite well represented, with Cessnock having the least number of G-NAF addresses occurring within 800m of a Greenspace at 80.55 per cent.
Table 1. Direct distance comparison between Local Government Areas and international standards
LGA
Newcastle
Lake Macquarie
Maitland
Port Stephens
Cessnock
Whole of Lower Hunter
G-NAF addresses within 400m (UK standard) Direct distance of Greenspace
(%)
G-NAF addresses within 800m Direct (US standard) distance of Greenspace (%)
96.53
99.99
94.04
97.85
73.29
88.76
84.08
91.68
64.05
80.55
88.05
94.88
Table 2 shows a reduction in the percentage of G-NAF addresses occurring within both UK and US standards. However, Newcastle is still very well represented with 99.18 per cent complying with US standards and Cessnock again having the lowest percentage (74.49 per cent) of G-NAF addresses within US standards.
Table 2. Network distance comparison between Local Government Areas and international standards
LGA
Newcastle
Lake Macquarie
Maitland
Port Stephens
Cessnock
Whole of Lower Hunter
G-NAF addresses within 400m (UK standard) Network distance of Greenspace
(%)
82.31
74.76
56.56
68.05
49.38
71.47
G-NAF addresses within 800m (US standard) Network distance of
Greenspace (%)
99.18
94.54
79.43
85.92
74.49
90.97
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International standards for maximum distance to Greenspace have been set at 800m and 400m for the US and UK respectively (Byrne and Sipe, 2010). Using these standards we can clearly see that, based on current data and methodologies, each LGA of the Lower Hunter region contains at least one G-NAF address which does not conform to these international standards. However, if we compare the maximum distance to Greenspace with the average distance, these vary by an order of magnitude which suggests that the data may be skewed. By looking at the frequency distribution for the data we can see that this is the case: the number of G-NAF addresses drops off dramatically as distance to Greenspace increases.
To determine how well a LGA conforms to international standards the proportion, in this case the percentage, of G-NAF addresses which conform to these international standards was calculated.
Using these measures Newcastle LGA seems to comply well with international standards. Based on both direct and network distance to Greenspace, over 99per cent of G-NAF addresses are within
800m of a Greenspace in both cases. The level of compliance drops based on the LGA in question. Cessnock LGA is the worst performer with 80.55 per cent and 74.49 per cent of G-NAF addresses within 800 metres of direct and network distance to Greenspace respectively. Whether this variation is a reflection of the analysis undertaken or a reflection of the actual distance to
Greenspace within these areas is unknown and will need to be investigated further.
The quality of the residential cadastre, roads network and Greenspace data affect the analysis to varying degrees. Both the distance estimations for direct and network distance will be overestimated due to the nature of the Greenspace dataset used. This is mainly due to the incomplete nature of the Greenspace dataset used.
Although the ABS Parklands Mesh Block data is accurate and aligns with general criteria for
Greenspace, many potentially viable Greenspaces have been overlooked. The ABS data was never intended to provide a definitive land use dataset, due partly to a single land use category being attributed to Mesh Blocks, which can be aggregations of several land use types. Some other areas where the ABS Mesh Block data are limited include multi-use zones where Greenspace is not the primary land use, including ovals and sporting grounds belonging to other institutions which are also open to the public at certain times.
The network distance to Greenspace is reliant on the PSMA roads network which may not be comprehensive. Although it includes some pedestrian pathways and cycleways, many minor access pathways to Greenspace have been omitted, leading to reduced connectivity. A method for improving the connectivity between the roads network and the existing Greenspace data has been included in the data preparation. However, this is by no means a complete solution (see Figure 1).
As noted earlier in this report, a whole suburb had been removed from the G-NAF data for which new data needed to be generated. It could be argued that when looking at the Lower Hunter region as a whole, the sheer number of residential parcels would mask the addition or subtraction of a small number of residential cadastral parcels. However, this would not have a great effect on theoutcome of the analysis.
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Comparing the Lower Hunter region as a whole with individual LGAs shows a variation in distance to Greenspace between LGAs. It is expected that if this analysis were completed at a finer scale using subsets of these LGAs, the analysis would highlight additional variation between these subsets. These additional residential cadastral parcels represent a significant number of addresses and will become more important as the analysis is further refined.
Figure 6. Lower Hunter comparison with international standards
By mapping the results of this analysis we can begin to spatially identify areas which are well represented by Greenspace, as well as highlighting areas where there may be further investigation required (Fig.6). Cadastral parcels which occur within 400 metres of Greenspace comply with UK standards and areas between 400 and 800 metres network distance from a Greenspace are within
US standards. Areas greater than 800 metres from a Greenspace do not comply with these existing international standards, and these would need further investigation to determine whether this is a reflection of the real situation or whether there are data issues which need to be addressed.
It is very unlikely that any additional improvement in the data will increase the estimates of distance to Greenspace garnered from this analysis. Any improvement in the network would lead to increased connectivity and therefore a reduction in estimates for distance to Greenspace.
Additionally, even though the ABS parklands data may not be comprehensive, it lines up well when compared with remotely sensed imagery. Any refinement to this data would result in additional
Greenspaces being included. This would in turn lead to more potential destinations and reduce estimates for distance to Greenspace. Therefore, residential cadastral parcels which currently conform to the international standard using current analysis would not change status based on any further analysis.
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
There are issues with incomplete roads and paths, leading to a reduced number of potential pathways to Greenspace.

The analysis generates a number of potential access points to Greenspaces based on assumptions about proximity and accessibility. Having a definitive dataset would prove useful.

The currently available datasets for Greenspace are inadequate. The existing datasets underestimate the level of available Greenspace as well as affecting any area estimates.
These estimates could provide insight into the area of Greenspace per head of population which is the current standard for measuring Greenspace adequacy. Additionally, this data set should be based on a clear definition of Greenspace, as required for sustainability indicators.

Improved G-NAF completeness and accuracy. There is potential to include zoning information
(e.g. residential, commercial) to assist in extracting residential information.

Defining and extracting urban residential environments would help to determine how/if peri- urban and rural localities are skewing the results.

Re-evaluation of existing international standards for proximity to Greenspace and to determine suitability to the Australian environment.

There is potential to investigate subsets of each LGA (maybe suburbs and localities) to determine how well each of these areas comply with existing international standards for proximity to Greenspace. This may highlight focus areas where local councils can coordinate effort. This analysis can be completed using existing methodology.

Local councils may be able to use this information during the planning stage to identify areas where the roads and pathways network requires additional linkages to increase accessibility to
Greenspace.

The inverse of the existing analysis can be used to determine the number of G-NAF addresses serviced by each Greenspace. This could allow a measure of use pressure faced by individual
Greenspaces.

This analysis can be used in conjunction with other measures of Greenspace quantity and quality in urban environments such as:
- the area of Greenspace available per head of population
- how individual Greenspaces support the social requirements of the surrounding communities, and
- how individual Greenspaces support the ecological processes of the surrounding environment.
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Australian Bureau of Statistics, 2011 ASGS: Volume 1 – Main Structure and Greater Capital City
Statistical Areas
Byrne, J. and Sipe, N., 2010, ‘Green and open space planning for urban consolidation – A review of the literature and best practi se’ Urban Research Program: Issues paper 11 Griffith University
Godbey, G.C., Caldwell, L.C., Myron, F. and Payne, L.L., 2005, ‘Contributions of leisure studies and recreation and park management research to the active living agenda ’ American journal of preventative medicine 28, pp.150-158
Kaplan, S. 1995. The restorative benefits of nature: Toward an integrative framework. Journal of
Environmental Psychology 15, 169 –182.
Marulli, J. and Mallarach, J.M., 2004, ‘A GIS methodology for assessing ecological connectivity: application to the Barcelona Metropolitan Area ’ Landscape and Urban Planning 71, pp. 243-262
PSMA Australia Limited, 2012, Product Description: Transport and Topography
Western Australian Planning Commission, 2002. ‘Public Open Space in Residential Areas’ Policy
Document 2.3
Figure 1.
G-NAF, Roads, Cadastre data © PSMA 2012
Mesh Blocks © Australian Bureau of Statistics 2011
Figure2.
G-NAF, Roads, Cadastre, Towns data © PSMA 2012
Mesh Blocks © Australian Bureau of Statistics 2011
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