IV. Case Study
4.2 Alternative evaluation
4.2.2 Construction complexity evaluation
The construction complexity evaluated in this study contains 3 components:
Water body crossing index
Built-up area crossing index
Bad slope index
All the indexes are computed by tracing routes in a GIS using the topographical map and digital elevation data. There are many IT solutions that provide GIS interface. After some trials, ArcGIS was chosen to perform all necessary estimations.
First, water body crossings and built-up area crossings were analyzed using World Topo Map, provided by Esri on the scale of 1:25 000. Although the map is provided in the Mercator projection, it was transformed to the Lambert Azimuthal Equal Area projection to make distance measurement possible in a correct way. Routes are traced on the map according to several rules:
Route segments among cities should be as straight as possible.
The Dnipro River cannot be crossed more than once.
HSR line inside a city that has a HSR station can use the same station existing railway does, where possible.
Figure 18 illustrates Route 5 traced over a topographic map as an example.
47
Figure 18 Route 5 traced over the topographic map
As candidate routes have some similar parts, all of them were split into unique sections in order to avoid multiple analyses of the same sections.
The five candidate routes are as follows:
1. Kyiv - Cherkasy - Kremenchuk - Dniprodzerzhyns'k - Dnipropetrovs'k – Zaporizhzhya - Donets’k.
2. Kyiv - Cherkasy - Kirovohrad - Kryvyy Rih - Dniprodzerzhyns'k - Dnipropetrovs'k - Zaporizhzhya - Donets’k.
3. Kyiv - Cherkasy - Kirovohrad - Kryvyy Rih - Dniprodzerzhyns'k - Dnipropetrovs'k - Pavlohrad - Donets’k.
4. Kyiv - Cherkasy - Kremenchuk - Poltava - Kharkiv - Slav'yans'k - Kramators'k - Donets’k.
5. Kyiv - Cherkasy - Kremenchuk - Dniprodzerzhyns'k - Dnipropetrovs'k - Pavlohrad - Donets’k
For each section length of water crossings and living area crossings is computed, the results are represented in Table 19.
48
Table 19 Lengths of sensitive area crossings at each section
Route section Built-up area crossing, m Water body
crossing, m
Rural Urban Industrial
Kyiv - Cherkasy 24661 1624 1560 746
Cherkasy - Kremenchuk 15037 1443 0 2326
Kremenchuk - Dniprodzerzhyns'k 15398 8742 0 180
Dniprodzerzhyns'k - Dnipropetrovs'k 0 1341 0 0
Dnipropetrovs'k - Zaporizhzhya 5771 5615 4130 4214
Zaporizhzhya - Donets’k 7915 0 0 620
Cherkasy - Kirovohrad 11605 14538 0 772
Kirovohrad - Kryvyy Rih 1906 2973 0 1959
Kryvyy Rih - Dniprodzerzhyns'k 13047 5256 0 240
Dnipropetrovs'k - Pavlohrad 4015 4876 0 3020
Pavlohrad - Donets’k 32539 2374 0 1320
Kremenchuk - Poltava 12186 0 0 739
Poltava - Kharkiv 14247 14725 0 1141
Kharkiv - Kramators'k 9628 21147 0 701
Kramators'k - Donets’k 2038 6047 0 80
By combining data for the sections, overall information about each route is obtained as listed in Table 20.
Table 20 Lengths of sensitive area crossings at each route
Route Built-up area crossing, m
Water crossing, m
Rural Urban Industrial
Route 1 68782 18765 5690 8086
Route 2 64905 31347 5690 8551
Route 3 87773 32982 1560 8057
Route 4 77797 44986 1560 5733
Route 5 91650 20400 1560 7592
Finally, values of rural, urban and industrial zone crossing are combined into one under an assumption that land acquiring in the latter two is twice more complicated, so that values are multiplied by two. Then the indexes are calculated with respect to the route length as follows:
49 L
L L
IBA LRA2 UA 2 IA
where IBA is built-up area crossing index;
L
RA, L
UA, L
IA are total lengths of rural, urban and industrial area crossings respectively;L is a route length.
L IWB LWB
where IWB is water body crossing index;
L
WBis total length of water body crossings;
L is a route length.
The results are shown in the Table 21.
Table 21 Built-up area crossing and water body crossing indexes
Route Build-up area
crossing index
Water body crossing index
Route 1 0.163 0.011
Route 2 0.169 0.010
Route 3 0.206 0.011
Route 4 0.216 0.007
Route 5 0.205 0.012
On the next step, slope along a route is analyzed using DEM-datafile. DEM is a digital elevation model format that stores elevation data. In this study GTOPO30 dataset by Earth Resources Observation and Science (EROS) Center is used. Elevation data combined with semi-transparent topographic map is shown on Figure 19.
Figure 19 Loaded DEM data in ArcGIS
(34) (35)
50
Initially the routes traced on the basemap do not have z-feature with information about the elevation. To obtain it, each route line is interpolated with the surface DEM-file by Arc GIS (ArcToolbox-> 3D Analyst Tools-> Functional Surface-> Interpolate Shape).
After this action, elevation profile along each route vertex is obtained. Consequently, the slope for each vertex i can be calculated as follows:
1
Having the list of slope values, the number of bad slopes is counted. Usually critical slope for HSR line is assumed to be 3.5% - 4% (UIC, 2010). In this study the slope is considered to be bad if it exceed 3.5%.
s
i: slope value of the route section i that lies between vertexes i-1 and i along the route;L: route length;
N (si > 0.035): number of route sections with slopes over the critical value.
The results of the bad slope calculations are in Table 22.
Table 22 Bad slope index
Route Bad slope number Bad slope index
Route 1 6 0.0083
Route 2 2 0.0024
Route 3 3 0.0039
Route 4 6 0.0076
Route 5 7 0.0106
So, the components of the construction complexity have the values as shown in Table 23.
Table 23 Construction complexity summary
Route Built-up area
crossing index
51
Route 2: 0.169 0.010 0.0024
Route 3: 0.206 0.011 0.0039
Route 4: 0.216 0.007 0.0076
Route 5: 0.205 0.012 0.0106
4.2.3 External effects evaluation
The external effects analyzed in this study contain two perspectives: influence on the living areas and protected natural zones. They are evaluated in a way, similar to the construction complexity.
The first external effect – influence on living areas – partially utilizes the results of analysis that was performed in the previous stage. While built-up areas crossing index was calculated by 3 components: rural, urban and industrial area crossing distances, living area crossing index requires only the first two of them.
The second external effect that concerns influence on the protected areas was evaluated in a less precise way, because World Topo Map, used as a background in ArcGIS, do not provide such kind of information. First the paper topographic maps were studied for every region and then each protected area was found in the GIS, by which the distance of crossing was measured.
The calculations are done as follows:
L L ILA LRA 2 UA
where ILA is living area crossing index;
L
RA, L
UA are total lengths of rural and urban area crossings respectively;L is a route length.
L IPNZ LPNZ
where IPNZ is protected natural zone crossing index;
L
PNZ is total length of protected natural zone crossings;L is a route length.
The result of these estimations is provided in Table 24.
Table 24 External effects summary
Route Living area crossing index Protected natural zone crossing index
52
It is important to mention the similarity between built-up area crossing index and living area