transport infrastructure effects: case study -...

Appendix J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Transport infrastructure effects: case study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Transport infrastructure effects: case study

South Metro Connect, 2010. Transport Infrastructure Effects. Case Study, Perth, WA.

Transport InfrastructureEffects:

Case Study

Doc Number

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Table of Contents

1.0 Background ............................................................................................................12.0 Objective ................................................................................................................13.0 Approach and Design .............................................................................................24.0 Methodology ...........................................................................................................25.0 Outputs ..................................................................................................................36.0 Conclusions ............................................................................................................67.0 Limitations ..............................................................................................................6


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1.0 BackgroundThere is a perception that linear transport infrastructure can sever catchment hydrologicalprocesses by mechanisms such as:

Retarding natural surface water flow regimes;

Cutting below the maximum height of the ground water table, so severing or drainingthe groundwater;

Filling on grade, so retarding the rate, periodicity and/or direction of groundwaterflows by virtue of compression into the ground.

Beeliar wetlands are known to be heavily dependent on water provision from both regionaland localised aquifers, localised catchment inflows and direct rainfall. By examiningpotentially “at risk” sites on the Swan Coastal Plain, a pattern of effect may be discernedbased on a comparison of “Before” and “After” analyses of wetland footprints and keyhabitats.

Figure 4 (attached) shows the hydrological processes between Bibra Lake and HorsePaddock Swamp demonstrating the features of landscape proposed to be developed andputative development effects.

2.0 ObjectiveTo examine the magnitude of any measurable effect associated with the installation oftransport infrastructure in areal extent and timeframes.Note, it is possible to extend this assessment framework and methodology to any nominatedwetland receptors in order to further test the null hypothesis that transport infrastructure doesnot have an adverse effect on wetland properties.


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3.0 Approach and DesignLocation Before AfterConstruction of Roadpast SouthLake

1978 1989

Construction of Railpast LittleRush Lake

1958 1970

4.0 MethodologyHistorical aerial imagery of South Lake and Little Rush Lake was reviewed in order to assesswhether the prevalence, distribution or situation of vegetation has been affected by thepresence of road and rail infrastructure (respectively) over the time period 1947 to present.Five images prior to the construction of the road (pre 1980s) were analysed, although imageryis only available for Little Rush Lake from 1958 and the 1989 image is of poor quality.Of the eight images interpreted, seven were spatially referenced. These images wereimported into GlobalMapper along with a dataset containing 1m topographic contours. Eachimage was clipped to the boundary of the innermost contour line around each lake andexported to GeoTIFF format.

The 1953 image required geo-referencing in order to provide spatial reference. This was doneby selecting common control points between this image and existing data (road intersections,field corners, etc.) and applying a first order polynomial transformation. Once the image wasgeoreferenced, it was then clipped to the extent of each lake as described.

A pixel by pixel raster classification method could not be used to identify ground coverclasses, because such techniques are more suited to multi-band satellite imagery. In thiscase the images were either single band or three-band RGB, which limited the ability tocorrectly classify them. The application of an ISO cluster algorithm and maximum likelihoodclassification technique did assist in identifying some broad features, but also resulted inspurious classification (e.g. dark shadows were classified as water, and parts of each lakeappeared to be vegetated). Due to these limitations, the output of this technique inconjunction with the original imagery was used to make a visual judgement of varyingvegetation cover.


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A visual assessment of the imagery revealed three broad optic classes – water, grass andvegetation. For the purpose of this analysis, “vegetation” generally consisted of nativeterrestrial vegetation, as opposed to weed cover within the “grass” polygons.

Vector polygons were digitised for each year, delineating the boundaries of each class.Polygons were stored in ESRI Shapefile format and attributed with a ‘TYPE’ field, containingeither “Water”, “Grass” or “Vegetation”. The area of each polygon was then calculated anddivided by the total area of each lake to determine the percentage cover of “Vegetation”. Thevisual analysis as described is presented in Figure 1.

5.0 OutputsThe results for the calculated area of vegetation and water at each Lake for each year arepresented in Table 1 and Figure 1.

YearSouth Lake Little Rush Lake

ha Veg % Veg ha Water % Water ha Veg % Veg ha Water % Water1947 4.7 20 15 65 - - - -1953 6.0 26 8.7 38 - - - -1958 6.3 27 9.5 41 0.4 4 5.6 501970* 6.1 26 14.7 66 0.6 5 8.8 781978* 6.7 29 9.7 42 1.9 16 4.3 381989** 7.4 32 12.3 53 2.8 25 6.7 591999** 8.7 37 9.5 41 2.5 22 6.7 59

2008/09** 9.7 42 8.8 38 3.7 33 6.7 59* Post construction of rail infrastructure past Little Rush Lake** Post construction of road infrastructure past South Lake and Little Rush Lake

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Figure 1: South Lake and Little Rush Lake Vegetation Classification

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Figure 2 Historical change at South Lake

Figure 3 Historical change at Little Rush Lake

0

10

20

30

40

50

60

70

% C

over

Year

South Lake

% vegetation

% water

Road Construction

Linear (% vegetation)

Linear (% water)

0

10

20

30

40

50

60

70

80

90

1958 1970 1978 1989 1999 2008/09

% C

over

Year

Little Rush Lake

% vegetation

% water

Rail Construction

Linear (% vegetation)

Linear (% water)

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The area of “Vegetation” at South Lake within the fixed boundary has increased from 20% to 42%between 1947 and 2008/09. Given the consistent upward trend of vegetation cover prior to and afterthe construction of the road, the increase in vegetation is likely to be due to the cessation offarming/agriculture use of the area, and the natural recolonisation of native vegetation into thegrassland. The area of “Vegetation” around Little Rush Lake significantly increased from 4% to 33%.

The area of water cover at South Lake varied between 38% and 66% prior to the construction of theNorth Lake Road, while the area varied between 38% and 53% after the construction. There appearedto be a gradual decline in the percent cover of water, however levels tended to fluctuate throughoutthe years. The area of water recorded in Little Rush Lake averaged 50% prior to the road, and 49%after the road. Although no change in water cover could be detected, there was only one pre-construction value available. It might be expected that a road could influence the amount of waterpresent in the Lakes as a result of potential alterations to surface water and groundwater hydrology,however, no significant difference could be detected from this analysis.

The most obvious external influence on the changing dynamics of the two lakes was the cessation offarming/agriculture, which allowed natural rehabilitation processes to reclaim grassland/pasture andincrease the percentage of vegetation within the boundary. Based on the available imagery, it appearsunlikely that the prevalence and distribution of vegetation has been affected by the presence of roadand rail infrastructure over the time period 1947 – present.

6.0 ConclusionsThere is limited evidence to suggest that the construction of the road and rail infrastructure affectedhydrological processes around the lakes. Based on available data, it appears that the area ofvegetation cover has gradually increased at both South Lake and Little Rush Lake between 1947 and2008/09, while the presence of water in the Lakes has not varied significantly. It can be concluded thatit is unlikely that transport infrastructure has an adverse effect on wetland properties.

7.0 Limitations Imagery is only available for Little Rush Lake from 1958.

The 1989 image is of poor quality.

Images were captured at varying times of the year, which does not allow for accuratecomparison.

The statistical power of the Before/After analysis is likely to be relatively low based on limitedaerial photographic sequences that may not enable discernment of inter-annual rainfall andwet-dry cycle periods.

M:\60100953 - Roe Hwy Ext\6 Draft Docs\6.1 Reports\Environmental\Draft PER\11.0 Appendices (Tech Reports)\Transport Infrastructure effect case study.docxSouth Metro Connect, a partnership between Main Roads and AECOM for theproject development phase of the Roe Highway Extension

AECOM Australia Pty LtdABN 20 093 846 925

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transport infrastructure effects: case study -...

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