Transport infrastructure is a major tool that is not only necessary for the existence of the economy due to its necessity in both production and consumption but also to minimize spatial disparities as well as enhance regional cohesion (Ferrari, Bottaso, Conti & Tei, 2019). As Melbourne and Sydney are the capital cities of the two states with the highest Gross Domestic Product (GDP) in Australia and are its strongest economic centers (“Composition of the Australian Economy�, 2019), it is imperative that they are strongly connected. Hence, the Victorian Rail Authority (VRA) aims to construct a new subsection for their new high-speed rail which will deliver passengers from Melbourne to Sydney (refer to map 1 for site context).
To determine the best possible alignment for a high-speed rail based on four main criteria: the steepness of the slope, rates of occurrence of flooding, the presence of on-site protected vegetation and the existence of built road transport infrastructure.
Map. 1 Location of proposed alignments (ArcGIS, 2019)
The first criterion of slope steepness was considered as the VRA guide specified that it is inadvisable to construct the rail on one steeper than 25 degrees. This is due to reasons including passenger comfort, added pressure to the track as well as cost. The next factor of a flood analysis was necessitated by the high rate of erosion due to flooding in the flat areas prime for rail construction. Thus, flood-prone areas were identified in order to determine not only where floor precaution tools would need to be set up but also which alignment would be most costly to maintain. The third consideration was the intersection of alignments with national parks, which is undesirable as it negatively affects wildlife habitats. In addition, this particular trait is associated with the nonenvironmental costs of slower train speeds and supplemental feeding as a result of mitigation options. The last criterion is the presence of existing infrastructure on the site. Making changes to existing infrastructure will increase costs hence it is best to avoid intersecting sites with them.
With the added pressure to the track and the need to consider passenger comfort, the new rail cannot be built on a slope steeper than 25 degrees.
Including national parks, surrounding vegetation, bushland which create habitat for local wildlife
To prevent damage to the rail and the added commercial risk of cancellations the track cannot follow a path prone to flooding
Potential surrounding infrastructure such as buildings, existing roads and railway which may generate greater economic costs to the project
No.
Steps
Additional notes
1.
Select literature review to help complement the research/analysis process of the project
See page 7
2.
Set up alignments on loaded map of VIC
See page 3 map 1
3.
Clip portion of elevation dtm of VIC to alignments and use as the base map with proposed alignments
4.
Use distance tool to measure line in km - create a new field in alignments attribute table (name: distance, type: double) and use calculate geometry: length
See page 9 map 2
5.
Use contouring to find out rise and fall on the map
See page 10 map 4
6.
Use reclassify to determine obstacles from the more detailed raster data
6.1. Obstacle 1 - slope over 25 degrees (use intersection tool between points and reclassify tool) 6.2. Obstacle 2 - flood map - calculate flow accumulation from elevation 6.3. Obstacle 3 - ENVIRONMENTAL: national parks (contain sensitive vegetation) 6.4. Obstacle 4 - ECONOMIC: road infrastructure (economic costs to remodel)
7.
Use buffer tool to measure distances of the track against nearby obstacles
See appendix last image
8.
Calculate the sum of rise and fall, mean, and max height through the raster calculator and the summary statistics tool
See page 10 table 2
9.
Use the slope tool from surface analysis to calculate slope
10.
Use dataset for areas prone to flooding and input on the map
11.
Load locations of protected vegetation onto the map.
12.
Generated maps containing flood lines through fill, flow direction, and flow accumulation and afterwards, check for any possible intersections between areas of the rail and that of inaccessible areas such as rivers, roads, areas prone to flooding, or that of protected vegetation through outlining them from external software.
13.
Weigh benefits of each track individually based on all the criteria mentioned while also considering the disadvantages so far as well from the proximity of the track with inaccessible areas and slope steepness as well as areas prone to flooding
14.
Make a ranking on which alignment is the best track
15.
Export the maps to be used in the report
See page 14 table 4
Table. 1 Steps and tools used for conducted analysis on proposed analysis
For sound analysis of the slope of any railway alignment, the limitations are not restricted to those specified in the guidelines. It is necessary to take into account the effect of various gradients of the slope on the passengers in the train. Liu, Han & Wang (2018), highlight the cons of building on an extreme steep slope which correlate to costlier economic development of ecological resources. They derived this analysis from cities in the C2 Terrain (Eastern piedmont plain of the Qinling Mountains) which are steeper than others studied, hence leading to an expensive development. This method of analysis allows a clear understanding of the economic and ecological costs of building on a slope. Another aspect to take into account is the comfort of passengers travelling in the train. According to analysis by Yi (2017), the section of slope, hence the angle of the slope, should be gentler to avoid frequent rise and fall of the track which may cause heavy discomfort to the passenger. This book takes a heavy mathematical approach towards the analysis by conducting a simulation of vehicle vibration decay time. In this approach, the author takes into account the reduction of force of the high-speed railway as it reaches and passes the vertical curve of a slope to calculate the effect of the slope on the passenger sitting inside. For the purpose of our decision making assignment, it is not possible to use a heavy mathematical approach but we can use the results of the analysis to guide ours.
Fig. 1 Factors affecting railway infrastructure (Pant, R., Hall, J., & Blainey, S, 2016)
Fig. 2 Flood risk map (Pant, R., Hall, J., & Blainey, S, 2016)
David, Ilyes and Baros (2011), state the significant effect that railway slopes have on erosion which may be caused by flooding. Railway lines require gentler slopes hence more of the slope area is exposed which is prone to greater erosion. The case study of the 170km Assam-Bengal railway line in India which took 2 years to recover from heavy erosion enhances the analysis. Pant, Hall and Blainey (2016) analyze the flood risk of Great Britain’s railway system through a Vulnerability Assessment. In this study, they refer to assets related to the railway which allow revenue of capital and these assets (see fig. 1) are put under vulnerability assessments to evaluate the risk if each of them were to fail. In their flood vulnerability, they test the failure of each asset and its negative impact on railway infrastructure. First they gather a national flood risk assessment and map it with the rail infrastructure. This allows a clear visual of the intersections between flood risk areas and railway lines. To present the results of the flood risk, they present three categories; low, moderate and significant, each category relating the percentage of flood risk during a year, as shown in Figure 2. This categorization gave them a clear list of all assets which were in the vicinity of a low, moderate or significant flood risk area. In this study, they provide an area of improvement for the datasets which would show them the current infrastructure in place to prevent flooding to increase accuracy of data but without the dataset, the worst-case scenario is chosen to map..
The study overall reveals that the exposure of even a small number of assets to significant flood risk can cause severe damage to the railway infrastructure. Spatially, the vulnerability risk can also map the assets around the busiest areas which would cause major disruptions to the railway system if they were to fail. Hence, the additional data needed for this analysis would be passenger ticketing information to evaluate peak and non-peak hours to estimate disruptions. For our analysis, we are able to use this analysis to determine which alignments fall in the â&#x20AC;&#x2DC;significantâ&#x20AC;&#x2122; flood risk category and are unusable as future railway alignments. A common consequence of railway tracks built in vegetated areas is the fragmentation of the vegetated ecosystem into smaller parts which limits the connectivity for wildlife habitats in the specific area. In addition to this, there are many socioeconomic and ecological impacts of the proximity of forests to transport networks (Chomitz and Gray, 1996). Therefore, according to Sahana and Ganaie (2017), a buffer is required along road networks to evaluate the impact of transport networks on deforestation. The constant human and animal activities along roads create greater opportunity for accidental/man-made fires. In our analysis, we are able to derive the buffer from Sahana and Ganaie (2017) who used 4 buffers ranging from <500m to >2km to evaluate the influence of road on deforestation. The impact of railway on wildlife is seen through the pattern of fragmentation of land area which can modify the behaviour and movement of some wildlife species in the area. Each species has a specific movement pattern and their path is obstructed when railway tracks are put down. Small species such as turtles can get stuck between train tracks and are destroyed by railway as was shown in the study by Dorsey, Olsson and Rew (2015). Their study provides mitigation options such as wildlife crossing structures (Figure 3), habitat alteration, exclusion systems, reduced train speeds and supplemental feeding. These are all increased costs to the project to be considered if the railway alignments run through heavy vegetated patches.
Fig. 3 Diagram of tunnel structure under railway track for small animals to cross (Dorsey, B., Olsson, M., Rew, L.J., 2015)
In order to install new railway tracks, several changes to existing infrastructure are necessary as shown in the case study by Metro Tunnel about the Western Turnback Development (Station Works) in 2019. The study identifies existing railway lines in the area which need to be realigned. In addition, new CCTV, lights, furniture and technology have to be reinstalled hence driving up additional costs. To analyze our alignments, we can acquire data about existing railway to overlap with proposed alignments and create an obstacle map showing which lines generate great costs to the project. A high speed train running on the tracks can cause vibrations of the track and the impact can be felt on buildings built above a rail tunnel, hence if the proposed alignments were built in proximity of existing building infrastructure, the vibrations inside the building would be felt at a level higher than the standard limits. This study can be used in our analysis to predict extra costs incurred to reduce vibrations on existing infrastructure surrounding the alignments. The analytical methods provided by spatial engineering literature provide great base for our proposed alignments and ways to analyze extra costs that may incur due to impact of the railway on surrounding areas. There are limitations to every analysis due to limited data and limited experience in mathematical analysis but the results can be used to discuss the impact on our criteria.
Map. 2 Total distance of each alignment (ArcGIS, 2019)
Map. 3 3D Length of each alignment (ArcGIS, 2019)
Map. 4 Cumulative rise and fall of each alignment (ArcGIS, 2019)
Alignments
Sum of rise and fall (m)
Mean
Maximum height
A
18270
2.3
15.8
B
23707
2.5
14.6
C
13074
2.4
13.9
D
25733
2.8
14.8
Table. 2 Sum statistics for each alignment obtained from map analysis
Map. 5 Obstacle 1: points on alignments where slope > 25 degrees (ArcGIS, 2019)
Map. 6 Obstacle 2: points on alignments that intersect with flood line(ArcGIS, 2019)
Map. 7 Obstacle 3: points on alignments that intersect with existing road infrastructure (ArcGIS, 2019)
Map. 8 Obstacle 4: Buffer of 1 km around alignments intersecting with protected vegetation (ArcGIS, 2019)
Alignment
A
B
C
D
Distance Covered (km)
157.3
191.6
107.7
184.1
3D Length (km)
158.3
192.9
108.5
185.9
Cumulative Rise & Fall (km)
18.72
23.70
13.07
25.73
7736 (24.16%)
9406 (29.37%)
5310 (16.58%)
8915 (27.84%)
Count for Obstacle 2 (points on alignments that intersect with flood line)
46
39
12
28
Count for Obstacle 3 (points on alignments that intersect with existing road infrastructure )
37
36
8
30
2 12.14 + 2.02 = 14.16 sq. km
3 3.58 + 1.39 + 6.16 = 11.13 sq. km
0 0 sq. km
4 16.68 + 5.07 + 10.27 + 23.07 = 55.09 sq. km
7821
9484
5330
8977
Count and percentage for Obstacle 1 (points on alignments where slope > 25 degrees)
Count and area for Obstacle 4 (Buffer of 1 km around alignments intersecting with protected vegetation) (sq. km) Total Count for Obstacles
Table. 3 Analysis of numeric data from maps based on criteria/limitations
Alignment
A
B
C
D
DIstance Covered (km)
3
999
1
999
3D Length (km)
3
999
1
999
Cumulative Rise & Fall (km)
2
3
2
3
Obstacle 1
3
3
2
3
Obstacle 2
999
999
2
3
Obstacle 3
999
999
1
3
Obstacle 4
2
2
1
999
Total obstacles
3
999
2
3
Table. 4 Ranking table for alignments based on criteria/limitations
Key for constraint values: Distance and 3D length rating for value of: 100- 120 km: 1 (No constraints) 120- 140 km: 2 (Slight constraint) 140- 160 km: 3 (Many constraints) 160+ km: 999 (Unfeasible)
Obstacles 1,2,3,4 (obstacle 1 percentage numeric value and obstacle 4 area value) & Cumulative Rise-and-Fall rating for value of: 0-10: 1 (No constraints) 10-20: 2 (Slight constraint) 20-30: 3 (Many constraints) 30+: 999 (Unfeasible) Total obstacles rating for value of 0-3000: 1 (No constraints) 3000-6000: 2 (Slight constraint) 6000-9000: 3 (Many constraints) 9000+: 999 (Unfeasible)
Map. 9 Alignment route suggested for VRAâ&#x20AC;&#x2122;s new speed rail (ArcGIS, 2019)
Through the results, distance-wise, it is apparent that track C covers the shortest distance, hence it has the advantage compared to the other alignments in this respect. Elevation-wise, however, track C has the best advantage, as it has a cumulative rise and fall of only 13.07 km compared to the other three alignments. It is also supported by the fact that it has the lowest max height, 13.925 meters. However, it has the second lowest mean, of which is 2.42 meters, as compared to track A which has 2.32 meters. Because of it still being more advantageous compared to the two other factors, however, we can still say that it is still better in the aspect of elevation. It also has the fewest slopes of 25 degrees along the track, which is one of the most important constraints as was outlined within the problem statement. In regards to areas prone to flooding, we can see that track C would be in the most advantageous position, as it has the least areas that are prone to flooding. The track also does not cross over any protected vegetation areas. This will definitely help to reduce the costs from policy negotiations in regards to how to go ahead with deforesting the protected vegetation and from public outrage in general if it does happen. Track C has the least amount of intersections with existing roads, allowing for much more flexibility for development. This will also help to reduce costs significantly as it prevents too much costs from being incurred from redirecting the roads and building over the existing ones. Overall, through the analysis conducted from the chosen parameters, we would recommend track C as the optimal track to be built for the Melbourne-Sydney high speed rail, as it offers the most advantages compared to the other tracks, mostly economically since it is cost-efficient as well as constraint-wise from the problem statement. Because it does not cross protected vegetation, it is environmentally the most advantageous. It also has the shortest distance, hence the fact that it could get passengers from one city to another in the shortest possible time. Supporting this is also that because it has the least obstacles that could cause potential delays including potential flood areas through the flood lines that flow through the map, it will definitely be functioning well over the course of its operation time. There is no single track that supports the constraint of following no path prone to flood or that it is built on no slope steeper than 25 degrees, but at the very least we can select one that minimizes on both constraints. This, however, comes with the cost of it having a higher mean of rise and fall when compared to track A, though it is made up for by its moderate length as well. A shorter route would definitely benefit those travelling between the cities, unless we would be considering the scenario where more stops are needed along the way. Furthermore, an decision otherwise would also depend on where the stop should be located at in Sydney, as the distances between the final stopping positions vary by quite some distance.
One main limitation was the lack of comprehensive data that covered the entire site area. This includes railway data in the NSW area that the railway extends to hence our analysis is limited to the small section of proposed alignments in Victoria we are provided. In terms of additional criteria, we did not have access to data about specific animal and tree types spread along the alignments hence our analysis was constrained to the effect that National Parks in Victoria containing majority of protected vegetation and wildlife in general could be assumed to have. The analysis is also restrained with no idea of the true cost and expenditure that each obstacle will incur hence our economic analysis is cut short. A major limitation is that all data used is static data, hence any changes in topography or infrastructure cannot be recorded which creates inaccuracy in the analysis.
On the grounds of the criteria of steepness of slope, proneness to flooding, on-site vegetation and existing infrastructure, the alignment recommended is Alignment C. In terms of the distance of the actual rail to be constructed, Alignment Câ&#x20AC;&#x2122;s track is the shortest and thus the most economical. Additionally, Alignment C has the gentlest slope, which is evident from its cumulative rise-and-fall of only 13.07km. In regards to total obstacle count, Alignment C also has the lowest count of only 5330. This number is comprised from points where slope exceeds 25 degrees, intersect flood lines, roads and national parks. Thus, from all the collected information and analysis conducted, it is clear that Alignment C is the best choice economically and environmentally.
Chomitz, K., Gray, D. (1996). Roads, Land use and Deforestation: A Spatial Model Applied to Belize. The World Bank Economic Review, 10(3), (487-512). David, L., Ilyes, Z., Baros, Z. (2011). Geological and Geomorphological Problems Caused by Transportation and Industry. Central European Journal of Geosciences, 271-286. DOI: 10.2478/s13533-011-0026-2 Dorsey, B., Olsson, M., Rew, L.J. (2015). Ecological Effects of Railway on Wildlife. In: van, D. R. R., Smith, D. J., & Grilo, C. (eds.). Handbook of road ecology (219-227). John Wiley & Sons, Incorporated Ferrari, C., Botasso, A., Conti, M., Tei, A. (2019) Economic Role of Transport Infrastructure: Theory and Models. https://doi-org.ezp.lib.unimelb.edu.au/10.1016/C2016-0-03558-1 Ho, K. S. (2001). Geotechnical Engineering: Meeting Society's Needs : Proceedings of the Fourteenth Southeast Asian Geotechnical Conference, Hong Kong. In: K. S. Ho, S. Li (eds.), Volume 1 of Geotechnical Engineering: Meeting Society's Needs, (48-50). CRC Press. Liu, H., Han, B., & Wang, L. (2018). Modeling the spatial relationship between urban ecological resources and the economy. In X. Zhang, B. Bayulken, M. Skitmore, W. Lu, D. Huisingh (eds.), Journal of Cleaner Production, (173, 207-216). Lucas P.S., de Carvalho R.G., Grilo C. (2017) Railway Disturbances on Wildlife: Types, Effects, and Mitigation Measures. In: L. Borda-de-Ă gua, R. Barrientos, P. Beja, H. Pereira (eds) Railway Ecology (81-93). Springer, Cham Pant, R., Hall, J., & Blainey, S. (2016). Vulnerability assessment framework for interdependent critical infrastructures: case-study for Great Britainâ&#x20AC;&#x2122;s rail network. European Journal Of Transport And Infrastructure Research, 16(1). Sahana, M., Ganaie, T. (2017). GIS-based landscape vulnerability assessment to forest fire susceptibility of Rudraprayag district, Uttarakhand, India. Environmental Earth Science. 676. Yang, J., Zhu, S., Zhai, W., Kouroussis, G., Wang, Y., Wang, K., Xu, F. (2019). Prediction and mitigation of train-induced vibrations of large-scale building constructed on subway tunnel. Science of the Total Environment, 668, 485-499. Yi, S. (2017). The Minimum Length of Grade Section. G. Jones (eds.), Dynamic Analysis of HighSpeed Railway Alignment: Theory and Practice, (277-286). Academic Press.
Figure 1: Pant, R., Hall, J., & Blainey, S. (2016). Vulnerability assessment framework for interdependent critical infrastructures: case-study for Great Britain’s rail network. European Journal Of Transport And Infrastructure Research, 16(1) pp. 186 Figure 2: Pant, R., Hall, J., & Blainey, S. (2016). Vulnerability assessment framework for interdependent critical infrastructures: case-study for Great Britain’s rail network. European Journal Of Transport And Infrastructure Research, 16(1). pp. 190 Figure 3: Dorsey, B., Olsson, M., Rew, L.J. (2015). Ecological Effects of Railway on Wildlife. In: van, D. R. R., Smith, D. J., & Grilo, C. (eds.). Handbook of road ecology (225). John Wiley & Sons, Incorporated Map 1. Manasi Chopdekar. “Site context with respect to proposed alignments” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 2. Manasi Chopdekar. “Total distance covered by each alignment” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 3. Map 1. Manasi Chopdekar. “3D length of each alignment” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 4. Manasi Chopdekar. “Cumulative rise and fall of each alignment” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 5. Manasi Chopdekar. “Obstacle map 1: points on each alignment having slope > 25 degrees” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 6. Manasi Chopdekar. “Obstacle map 2: points on each alignment showing intersection with flood line” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 7. Map 1. Manasi Chopdekar. “Obstacle map 3: points on each alignment showing intersection with existing road infrastructure” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 8. Manasi Chopdekar. “Obstacle map 4: Intersection of each alignment with protected vegetation areas” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019. Map 9. Manasi Chopdekar. “Final suggested route based on conducted analysis” [map]. Scale on the map. Using: ArcGIS [GIS Software]. Version 10.6. Melbourne, University of Melbourne, 2019.
Jacqueline Darwis (1000557) The focus of my contribution was summarizing information. I was in charge of the Introduction, Motivation, Problem Statement, Approach, Conclusion and the Table of Results. I believe that I contributed sufficiently to this project as I not only did my assigned part but also volunteered to do additional parts Manasi Chopdekar (935401) I volunteered to do all the mapping for this report, and we discussed as a group, the final ranking of each alignment as per set criteria and analysis from these maps. I believe I contributed sufficiently for this assignment. I made all the maps, while keeping in mind my teammatesâ&#x20AC;&#x2122; feedback regarding layout and color choices as well as feedback from assignment 2 Census GIS (to make any last minute changes). This assignment has helped me learn a lot first-hand about how GIS can be used in a practical situation. I really enjoyed learning the different tools GIS has to offer, such as buffer, intersection, extract values to points and how these tools can be used to obtain different results for analysis. Using these maps, we were able to arrive at a collective decision on which alignment to suggest as the best route and thus efficiently propose a solution to a given problem. Renaldi Gondosubroto (956566) In this assignment, I have had a better insight into how teamwork is done within the context of GIS-related mapping, which seems like the foundation of how a professional GIS team would work in scenarios such as those that were outlined in workplace experiences within the lectures. In particular, I completed the methodology section of how the maps were done based on the mapping process while contributing ideas as the maps were created in that respect and the discussion section in regards to analyzing the individual tracks during and after the creation of the maps necessary. I believe that we have managed to work well as a team and that I have managed to efficiently and effectively contribute equally through my part and did so while learning from other parts such as the overall mapping process as well. Through my contribution in the project, I did not only improve my teamwork skills, but also learn more aspects of GIS mapping in regards to tools and new resources to be able to solve the real world-styled problem analytically through the mapping done as assigned through this project. I could improve my contribution by learning more of the tools/resources needed through research to supplement some of the limitations discussed. Shruti Dalvi (993220) The main aspect which I was involved in was researching and writing the literature review while we joined together in analyzing each alignment and ranking each criteria. Personally, I believe I have contributed sufficiently, as have the whole group, to the assignment. I provided my knowledge if a problem came up in the mapping but I could have assisted more when it came to the initial mapping stages. This project has helped me learn ways to research otherâ&#x20AC;&#x2122;s analytical work and understand how to work that into our own project to assist with creating a better solution and how to effectively problem solve in ArcMap with new tools.
Using ‘Interpolate Shape’ tool to calculate 3D length of each alignment. This aligns the alignment along the curve of the elevation DTM.
Attempt to convert ‘Reclassify Slope’ from raster to polygon so both reclassify slope and points along alignments are vector data. Allows for easier use of the ‘Intersection’ tool to acquire slope values above and below 25 degrees along each point.
Running ‘Summary Statistics’ for the change in elevation
Finding area of intersection between buffer and national parks