UNIVERSITY OF NAIROBI
USE OF GIS IN ANALYSIS OF LOCATION AND
DISTRIBUTION OF RAILWAY STOPS WITHIN NAIROBI
AND ITS ENVIRONS
BY
MUIRURI JANET WANJIKU
F19/2552/2008
A project report submitted to the Department of Geospatial and Space Technology in partial
fulfillment of the requirements for the award of the degree of:
Bachelor of Science in Geospatial Engineering
APRIL, 2013
1
ABSTRACT
In an effort by the government to improve the chronically snarled up traffic of NMR (Nairobi
metropolitan region) on the major roads and highways, it has embarked on constructing new
railway stations and improving the existing ones as part of the larger project. This study
mainly aims at analyzing the locations and distribution of the railway stops within the study
area. The significance of having suitable locations for railway stops is recognized as a crucial
element in the drive to improve the quality of public transport in general. This study employs
the tools of Geographic Information System (GIS) in the determination of the suitability of
the railway-stop locations. For this study, determination of best locations for the railway stop
was based on five (5) criteria; the population distribution, location of a station relative to
other existing stations, land use, presence of an existing railway line and topography. This
study also aims at collecting and displaying all available information about each station on a
digital map. This information is useful to the commuters and managers of the commuter
system. Such information includes the spatial location and distribution of the railway stations,
also the facilities and travel information for each of this railway stations.
GIS was used for the preparation of the digital maps and carrying out the analysis procedures
(overlay and proximity studies). It was also used to organize non spatial data from excel
worksheets and to enable its display on a digital map. The final output is a digital map where
all the above data could be displayed at the click of a button on the digital map.
From the study it was concluded that indeed there is insufficiency of railway stops to provide
railway services. The analysis showed that most of the proposed and new railway stops were
located in the suitable sites that were identified from the suitability analysis. It was also
evident that all the old railway stops lacked the basic facilities of a railway stop but all the
new stops come with all those facilities. The major recommendation made in this study was
creation web based application to facilitate display of railway stop and railway line
information. It was also recommended that construction of railway line and stops in areas
with no existing railway line but have large population be considered.
i
DEDICATION
I dedicate this work to my parents, Mr. and Mrs. Muiruri, My sisters Charity and Jane and my
brotherWilliam.
ii
ACKNOWLEDGEMENTS
I thank God first for the wisdom and providence he has given me during the entire project.
Secondly, I would like to express my sincere gratitude to my supervisor Mr. P.C.Wakoli of
the Department of Geospatial and Space Technology, University of Nairobi. His guidance,
advice and supervision throughout the period of this project were pertinent and
immensurable.
I would also like to thank my family for their support throughout my time in school and
especially for their resolve to see me through college, their love and prayers. I will forever
remain indebted to them.
My appreciation also to the entire faculty, technicians and technologists in the department of
geospatial for all their support and technical assistance accorded. In a special way I would
like to thank Mrs. Mary Gwena and Mr.Matara for their unrelented advice.
My appreciation to the staff of KRC, S.o.K and RVR for their data and resources. Special
thanks to Mr. Gichuhi of KRC for his guidance, support and for providing part of the data
used for the project.
Last but not least I would also like to thank my fellow classmates with whom I had a
wonderful time in and out of class. I thank them for the help, guidance and critic throughout
this project.
iii
TABLE OF CONTENTS
ABSTRACT ............................................................................................................................... i
DEDICATION..........................................................................................................................ii
ACKNOWLEDGEMENTS .................................................................................................. iii
TABLE OF CONTENTS ....................................................................................................... iv
LIST OF FIGURES ...............................................................................................................vii
LIST OF TABLES .................................................................................................................. ix
ABBREVIATIONS .................................................................................................................. x
CHAPTER ONE ...................................................................................................................... 1
INTRODUCTION.................................................................................................................... 1
1.1
Background information ............................................................................................. 1
1.1.1
Overview .............................................................................................................. 1
1.1.2.
Public transport information system .................................................................... 1
1.1.2.
The need for geographic information system (GIS) ............................................ 1
1.2
Problem statement ....................................................................................................... 2
1.3.
Objectives of the project ............................................................................................. 3
1.4.
Scope and limitations .................................................................................................. 3
1.5.
Report organization ..................................................................................................... 4
CHAPTER TWO ..................................................................................................................... 5
LITERATURE REVIEW ....................................................................................................... 5
2.1
Definitions ................................................................................................................... 5
2.2.
History of railway transportation ................................................................................ 7
2.2.1.
The Kenya- Uganda railway ................................................................................. 7
2.2.2
Railway in Kenya ................................................................................................. 7
2.3.
Railway Stations .......................................................................................................... 8
2.3.1.
Station facilities ................................................................................................... 8
iv
2.3.2.
2.4.
Choice of location of a station ............................................................................. 8
Commuter Rail Service and network in Nairobi and Environs ................................... 9
2.4.1.
Current and proposed rail commuter network within and around Nairobi .......... 9
2.4.2
Commuter train service in Nairobi .................................................................... 10
2.5.
Vision 2030 and the rail network system .................................................................. 12
2.5.1.
Nairobi Urban Rail Terminal ............................................................................. 12
2.5.2.
Existing Rail Lines Optimization....................................................................... 13
2.5.3.
MRTS Corridors ................................................................................................ 13
2.5.4.
Underground MRTS .......................................................................................... 14
2.5.3.
Stations............................................................................................................... 14
2.6.
Geographical information system ............................................................................. 15
2.7.
Gis in transportation .................................................................................................. 16
2.8.
Gps (global positioning system) ................................................................................ 18
2.9.
The Geodatabase ....................................................................................................... 18
2.10. Suitability in GIS context .......................................................................................... 19
2.11. Summary of other similar project.............................................................................. 20
2.11.1. Analysis of Bus-stops locations using Geographic Information System in Ibadan
North L.G.A Nigeria. ........................................................................................................ 20
CHAPTER THREE ............................................................................................................... 21
MATERIALS AND METHODOLOGY ............................................................................. 21
3.1.
Overview ................................................................................................................... 21
3.2.
Area of study ............................................................................................................. 21
3.3.
Data sources and tools ............................................................................................... 22
3.1.1.
Data sources ....................................................................................................... 22
3.1.2.
Tools .................................................................................................................. 24
3.4.
Overview of methodology.......................................................................................... 25
3.5. Data capture................................................................................................................ 26
3.5.1.
Data identification .............................................................................................. 26
3.5.2.
Data collection ................................................................................................... 26
3.5.3.
Data preparation ................................................................................................ 27
3.5.3.
Data extraction ................................................................................................... 32
3.6
Analysis ..................................................................................................................... 33
3.6.1.
Buffering ............................................................................................................ 33
v
3.6.2.
Suitability analysis ............................................................................................. 35
CHAPTER FOUR .................................................................................................................. 40
RESULTS AND DISCUSSION ............................................................................................ 40
4.1.
Overview ................................................................................................................... 40
4.2.
Digital maps .............................................................................................................. 40
4.2.1.
Spatial distribution of the railway stops in the study area ................................. 40
4.2.2.
Railway line routes ............................................................................................ 41
4.3.
The Geodatabase ....................................................................................................... 44
4.4. Attribute data .............................................................................................................. 44
4.5. Service area analysis Results...................................................................................... 49
4.6. Overlay Analysis ........................................................................................................ 49
4.7.
Suitability analysis results .......................................................................................... 51
4.8. Chart Analysis ............................................................................................................ 58
CHAPTER FIVE ................................................................................................................... 60
CONCLUSIONS AND RECOMMENDATIONS............................................................... 60
5.1.
Conclusion................................................................................................................. 60
5.2.
Recommendations ..................................................................................................... 61
REFERENCES ....................................................................................................................... 62
APPENDICES………………………………………………………………………………66
vi
LIST OF FIGURES
Figure 2.1: Structure of a Geodatabase ................................................................................... 19
Figure 3.1: Area of study ........................................................................................................ 22
Figure 3.2: Methodology schema............................................................................................ 25
Figure 3.3: Flow chart showing process of data capture......................................................... 26
Figure 3.4: Choropleth map showing population Distribution within the study area. ............ 32
Figure 3.5: Railway line Buffer .............................................................................................. 34
Figure 3.6: Flow chart showing the simplified process of carrying out suitability analysis ... 36
Figure 3.7: showing the wizard for Euclidean distance to existing stations and the resulting
distances on a map ................................................................................................................... 37
Figure 3.8: showing the wizard for Euclidean distance from the railway line and the resulting
distances in a map .................................................................................................................... 38
Figure 4.1: map showing distribution of termini within Nairobi and its environs.................. 41
Figure 4.2: map showing the classification of railway line route within the study area ......... 42
Figure 4.3: map showing spatial distribution of railway stops within the study area ............. 43
Figure 4.4: Railway stations Geodatabase .............................................................................. 44
Figure 4.5: showing the identified attributes of syokimau railway station ............................. 46
Figure 4.6: showing the attributes of the railway routes as a result of relate operation ......... 46
Figure 4.7: query expression on definition query tab of the railway station attributes ........... 47
Figure 4.8: showing highlighted station on the map phase as a result of the query operation 48
Figure 4.9: map showing station domains .............................................................................. 49
Figure 4.10: An overlay of station domains with all the railway stations .............................. 50
Figure 4.11: An overlay of the station domains and railway stops on the population
distribution map ....................................................................................................................... 51
Figure 4.12: Reclassified land use .......................................................................................... 52
Figure 4.13: Reclassified Euclidean distances from existing railway stops ........................... 53
Figure 4.14: Reclassified percentage population .................................................................... 54
Figure 4.15: Reclassified distances from the railway line ...................................................... 54
Figure 4.16: Reclassified slope ............................................................................................... 55
Figure 4.17: Suitability Map ................................................................................................... 56
Figure 4.18: An overlay of the railway stops on the suitability map ...................................... 57
vii
Figure 4.19: proposed sites for other railway stops ................................................................ 58
Figure 4.20: Trip frequency chart ........................................................................................... 59
viii
LIST OF TABLES
Table 3.1: Data collected ......................................................................................................... 23
Table 3.2: showing simplified commuter table of departure to Nairobi ................................. 30
Table 3.3: showing simplified commuter table of departure from Nairobi ............................ 31
Table 3.4: percent weight of influence assigned to factors influencing location of railway
stops ......................................................................................................................................... 39
Table 4.1: attribute table showing part of the attributes of new stations ................................ 45
Table 4.2: attribute table showing attributes of the old stations.............................................. 45
Table 4.3: showing the highlighted result of the query in fig 4.7 ........................................... 47
Table 4.4: trip table ................................................................................................................. 58
ix
ABBREVIATIONS
BRT: Bus Rapid Transit
CBD: Central Business Transit
DEM: Digital Elevation model
DMU: Diesel Multiple Units
EARC: East African Railways Corporation
EAC: East African Corporation
FSI: Floor Space Index
GCS: Geographic Coordinate System
GIS: Geographic Information System
GPS: Geographic Positioning System
IBM: International business machines
ILRI: International Livestock Research Institute
JPEG: Joint Photographic Exchange Group
JKIA: Jomo Kenyatta International Airport
KRC: Kenya Railway Corporations
KNBS: Kenya National Bureau of Statistics
LRT: Light Rail Transit
MRTS: Mass Rapid Transit System
NRS: Nairobi Railway System
NMR: Nairobi Metropolitan Region
PT: Public transport
PDF: Portable document format
RVR: Rift Valley Railways
RAM: Random Access Memory
S.o.K: Survey of Kenya
SG: Standard Gauge
SQL: Structured Query Language
TB: Terra Byte
TIFF: Tagged Interface File Format
UTM: Universal Transverse Mercator
x
CHAPTER ONE
INTRODUCTION
1.1 Background information
1.1.1 Overview
The current levels of urbanization within Nairobi have led to increased population within
the city most residing in areas around Nairobi. This has led to a great demand of
transportation services which could not be met by the road transport only. The result of
this high demand is chronically snarled traffic on major roads and highways. The
government hence had to be committed to explore alternative means including the
construction and improvement of commuter rail system in Nairobi and environs.
1.1.2. Public transport information system
Considering the current trend of urbanization within Nairobi and its environs, there is
demand for an effective, fast and reliable public transportation system. Rail transport has
been restructured in order to improve the current situation. In a huge city like Nairobi,
which is mainly served by roads, it is imperative that commuters know all the available
and convenient modes of transport to take in order to arrive to their destinations. With the
improvement of rail system, commuters will need to have a rail information system. This
brings about the need for a public transport information system. With the availability of
the information system, all the information required by the users will be available to them
at the click of a button. This will also put an end to indecisiveness of commuters
regarding their transport needs. The planners and managers of public transportation will
be able to make informed decisions about the commuter needs.
1.1.2. The need for geographic information system (GIS)
Geographic Information Systems (GIS) have been widely used in the field of
Transportation since location information is critical for transportation applications such as
transportation planning, modeling, accident analysis and transit service planning. The
1
significant contribution that GIS offers is the ability to manage data spatially and then
overlay these layers to perform spatial analysis. Thus a transit routes layer and an
individual rail stop layer when overlaid on a land use layer we can analyze the socio
economic characteristics of the area surrounding transit route and rail stops by buffering
that area. These capabilities enable transit agencies to georeference their rail routes, time
points and other features to a digital street centerline. In the Gis environment, digital map
connected to spatial and non spatial data is the main output in this project. This digital
map will allow commuters to query database and identify specific stops which will be
displayed on a digital map without comprising cartographic requirements. Gis software‘s
have capability of making a system that will select most appropriate stop. GIS will
manage attributes such as physical, financial, traffic, maintenance and traffic travel
freight operations and passenger operations.
1.2 Problem statement
Recently, the government has undertaken the project of improving the commuter rail
system and the construction of new railway stations/ stops, all this aimed at improving the
chronically snarled traffic on major roads and highways. A spatial analysis of the
distribution and location of the existing, new and proposed train stops will enable the
determination of suitability of each station by the relevant authorities. Once suitability is
determined, informed decisions will be made regarding their location and distribution
hence better and efficient services will be rendered. Commuters will need to be informed
of the operation of the system and how and where to access its services. They will need to
know where all the station stops are located, which routes the trains will follow, the cost
of transportation and the departure and arrival times of trains at the stations or stops.
They will also need to be informed of services that are offered at the modern railway
stations that will be constructed such as the parking facilities that will come with the ultra
modern train stations. Some of the railways stops may not be located in away to best
serve an area and they will need to be identified, some areas have no such facilities and
they would be best served if they had such facilities. This information system will suffice
to attract commuters to opt for rail transportation hence decongesting the roads. The
management will also benefit from such information so that it can be able to identify such
trends and make informed decisions.
2
Capturing all of the above aspects on a simple map is impossible; a possible solution is
which this project seeks to address, is development of a of rail information system which
would, among other things,
Show spatial distribution of existing and proposed railway stops/stations within
Nairobi and its environs along the existing railway lines;
Show suitable sites to build new railway stations;
Help to determine the suitability of already existing stations.
The information/ output that will be developed will be useful to the local government,
ministry of information and communication or private entrepreneurs and the public.
1.3. Objectives of the project
The main objective is to create a Geodatabase of the existing railway stops that will enable
storage of information about railway stops and to carry out their spatial analysis to determine
their suitability as per their location and distribution.
Specific objectives
To map the spatial distribution of the existing and proposed railway stops along the
existing railway line within the study Area.
To create a comprehensive database containing attributes of the existing railway
stops.
To determine the suitability of all railway stops.
To propose suitable sites for additional railway stations.
1.4. Scope and limitations
The logistics that people tend to consider like condition of the termini, weather and rail
condition have not been considered. This project is limited to the capabilities of the GIS
software used and the extent of their customization. The study focuses on Nairobi and its
environs. Nairobi was chosen because it‘s a large city with much population needing
transportation services, the fact that railway stations are concentrated within this region and
the increasing need by commuters for an alternative means of transportation. Although there
are different modes of public transportation in Nairobi such as buses, taxis, pull carts,
3
motorbikes, etc. the study only covered transportation by rail due to time and resource
factors.
1.5.
Report organization
The report is organized in five chapters. Chapter one tackles the introduction to the concept
of public transport by rail, objectives, scope and the limitations of the project. Chapter two
addresses literature review with reference to rail transportation. Chapter three discusses the
materials used and the methodology applied in the project. Chapter four gives the results and
discussions and the final chapter addresses the conclusions and the recommendations.
4
CHAPTER TWO
LITERATURE REVIEW
2.1 Definitions
A railway stop is a spot along a railway line, usually between stations or at a seldom used
station, where passengers can board and exit the train. A station stop usually does not have
any tracks other than the main tracks, and may or may not have switches (points, crossovers)
(fowler, 1995).
An interchange station or a transfer station is a train station for more than one railway
route. It allows passengers to change from one route to another. Transfer may occur within
the same mode, or between rail modes, or to buses. Such stations usually have more
platforms than single route stations. In most rapid transit, an interchange station is a stop at
which a passenger can change from one line to another without incurring another full fare or
having to leave the station proper. Some interchange stations offer only transfer between
routes and do not have the ability for passengers to enter or exit the network.
Railway Gazette International is a monthly business journal covering the railway, metro,
light rail and tram industries worldwide. It is available by annual subscription and it is read in
over 140 countries by transport professionals and decision makers, railway managers,
engineers, consultants and suppliers to the rail industry. A mix of technical, commercial and
geographical feature articles, plus the regular monthly news pages, covers developments in
all aspects of the rail industry, including infrastructure, operations, rolling stock and
signaling.
A train station, also referred to as a railway station or a railroad station in US English
and often shortened to just station, is a railway facility where trains regularly stop to load or
unload passengers or freight. It mainly consists of a platform next to the track and a station
building also called depot that provides related services such as ticket sales and waiting
rooms. If a station is on a single track main line, it usually has a passing loop to facilitate the
traffic. The smallest stations are most often referred to as stops or halts in other areas of the
world. In Kenya, the railway stations have a shelter only and are small in size, they are
5
therefore referred to as stops. The new ones being constructed are bigger and with more
facilities such as parking space hence can be called railway stations.
Dual-purpose stations can sometimes still be found today, though in many cases goods
facilities are restricted to major stations. In rural and remote communities across Canada and
the United States, passengers wanting to board the train had to flag the train down in order for
it to stop. Such stations were known as flag stops or flag stations (fowler, 1995)
A terminal or terminus is a station at the end of a line. Trains arriving there have to end
their journeys or reverse out of the station. Depending on the layout of the station, this
usually permits travelers to reach all the platforms without the need to cross any tracks , the
public entrance to the station and the main reception facilities being at the far end of the
platforms. Sometimes the track continues for a short distance beyond the station, and
terminating trains continue forwards after depositing their passengers, before either
proceeding to sidings or reversing to the station to pick up departing passengers. Many
terminus stations have underground rapid-transit urban rail stations beneath, to transit
passengers to the local city or district. A terminus is frequently, but not always, the final
destination of trains arriving at a station.
A Junction/interlocking is a station where two or more rail routes meet. It could be a
terminus or an en-route station. It usually divides two or more lines or routes, and therefore
has remotely or locally operated signals.
A halt is a small station, usually unstaffed and with few or no facilities. In some cases, trains
stop only on request, when passengers on the platform indicate that they wish to board, or
passengers on the train inform the crew that they wish to alight.
Goods stations deal mostly with the loading and unloading of goods and may well have
marshalling yards (classification yards) for the sorting of wagons. The world's first Goods
terminal was the Park Lane railway goods station at the South End Liverpool Docks. Built in
1830 the terminal was accessed by a 1.25 mile tunnel. As goods have been increasingly
moved by road, many former goods stations, as well as the goods sheds at passenger stations,
have closed. In addition, many goods stations today are used purely for the cross-loading of
freight and may be known as transshipment stations. Where they primarily handle containers
they are also known as container stations or terminals.
6
2.2.
History of railway transportation
2.2.1. The Kenya- Uganda railway
The Kenya – Uganda Railway was built by the Imperial British East Africa Company back in
the 1890s. Construction of the line began at the Kilindini Harbour in Mombasa in 1895. The
line arrived at present site now NRS at around 1900. The railway arrived at Port Florence
(Kisumu) around 1901. Eventually, the British Government took over the territories of Kenya
and Uganda from the Imperial British East Africa Company. In 1920, Kenya became a
colony of the Crown under direct administration of the Colonial Office in London. The
railway was expanded from Eldoret to Kampala, bypassing the use of ships on Lake Victoria
from Kisumu. Additional branch lines were built from Nakuru to Nyahururu, from Nakuru to
Rongai and from Konza to Magadi. The invasion of Ethiopia by Italy during World War 2
forced the British to build a railway from Nairobi to Nanyuki in order to supply its forces.
British troops forced the Italians out of Ethiopia and restored Emperor Haile Selassie to his
throne. After independence in the early 1960s, railway and port operations in Kenya, Uganda
and Tanzania were administered by a single body: the East African Railways and Harbours.
The breakup of the East African Community in 1977 marked the beginning of the end for the
region‘s railway system. Each of the three East African countries took up running its own
system. In Kenya, railway and port operations were split between two state-owned
corporations: Kenya Railways and Kenya Ports Authority. The railway became starved of
funds.
2.2.2 Railway in Kenya
Kenya Railways Corporation (KRC), also Kenya Railways (KR) is the national railway of
Kenya. It was established in 1977 after the breakup of the east African community. The
original Uganda Railway was transformed into the East African Railways and Harbours
Corporation (EARC) after World War I. The EARC managed the railways of Uganda, Kenya,
and Tanganyika until the collapse of the East African Community in 1977. Subsequently KR
took over the Kenyan part of the EARC. Kenya Railways Corporation (KRC) was hence
established in 1978 under the Kenya Railways Act Cap397 of the Laws of Kenya. It is a
wholly owned government parastatal that took over the operations of the defunct East African
Railways Corporation (EARC), following the demise of the then East African Community
(EAC) in 1977. The Act was revised in 1986, and it details the duty of the corporation to
provide coordinated and integrated rail and inland waterway transport services, port facilities
7
in relation to inland water transport and auxiliary road transport services. Its operations are
Like the other members of the EAC, Kenya utilizes the gauge track of1, 000 mm (3 ft 3
3
⁄8 in) (metre gauge). The reason was that when the British started the railroad construction at
the end of the nineteenth century they utilized material and workers from India. The Indian
gauge and rolling stock was 1,000 mm (3 ft 3 3⁄8 in). The mainline of the KR is based on the
original Uganda Railway. Its 930 km (578 mi) main track connected the Indian Ocean port of
Mombasa to the port of Kisumu at Lake Victoria. Half way is the capital of Nairobi that was
founded as a rail depot of the UR. The British added several branch lines as well as a link to
Tanzania and a link to Uganda - the total system eventually had 2,778 km (1,726 mi) of track.
As of 2006 much of the overall railway system has been neglected or is in disrepair.
Nevertheless the mainline from Mombasa to Kisumu is operative though at reduced speed.
For passengers, the ―Jumbo Kenya Deluxe‖ connects Nairobi and Mombasa. The fourteen
hour overnight trip runs three times a week either eastbound or westbound on the single track.
The ―Port Florence Express‖ connects Nairobi with Kisumu. KR also operates the Kenyan
ferry system on Lake Victoria (Henry, 2002).
2.3.
Railway Stations
2.3.1. Station facilities
Stations usually have ticket booths (British English: "ticket office" or "booking office"),
ticket machines, or both; although on some lines tickets are sold on board the trains. Ticket
sales may also be combined with customer service desks or convenience stores. Many
stations include a form of convenience store. Larger stations usually have fast-food or
restaurant facilities. In some countries, stations may also have a bar or pub. Other station
facilities may include: toilets, left-luggage, lost-and-found, departures and arrivals
boards, luggage carts, waiting rooms, taxi ranks and bus bays. Larger or manned stations
tend to have a wider range of facilities. A most basic station might only have platforms,
though it might still be distinguished from a halt, a stopping or halting place that may not
even have platforms.
2.3.2. Choice of location of a station
The location of railway station is often a compromise. Although many railway stations are
well located with regard to source of traffic, a number are less than optimally situated.
Wasteful use is sometimes made of space in locations where land is valuable. Service
8
patterns may also be improved upon. For example radial routes may be linked in order to
reduce the need to dedicate land to city center terminal facilities, with the added bonuses of
making cross cities journeys easier and reducing the overall requirement for rolling stock.
This illustrates the need for holistic planning, commercial development, and operation. A city
centre location is frequently convenient for pedestrian access to shops, offices, place of
entertainment. In large cities a large proportion of commercial development means that
substantial proportion of passengers work within easy walking distance whilst a metro system
is able to provide convenient access for those working further away. A peripheral location,
near a main road or motorway may be convenient for ‗park and ride‘ and ‗kiss and ride‘
access. Journey times to city center locations will however be extended in absence of central
station. Since many businesses have relocated to suburban and out of town locations, there
exists a need for easy access to parkway stations either of the dedicated or informal type. In
some instances a combination of a city centre stations and one or more peripheral parkway
station may be convenient. Although it may be argued that the additional stops will reduce
the overall speed, and therefore competiveness of the rail service, increasing the train
frequency (using high acceleration DMU or EMU vehicles rather than traditional intercity
stock) will help restore the balance. Where increased traffic at the relocated stations is likely
to reduce road congestion or dependence on vehicles it would be reasonable to seek financial
assistance (Julian et al., 1998).
2.4. Commuter Rail Service and network in Nairobi and Environs
2.4.1. Current and proposed rail commuter network within and around Nairobi
Presently 3 rail lines of Kenyan Railways traverse the NMR (Nairobi metropolitan region). In
addition there is a long industrial siding from Konza to Magadi via Kajiado, owned and
operated by a private company. The track is of meter gauge (MG). The alignment is
circuitous, geometrics poor, rakes obsolete and service dismal. It takes more than 2 hours
from Nairobi to Thika. Though the fare is cheap, compared to bus and Matatu, patronage is
low due to poor quality of service. Overall the system is obsolete and requires scrapping and
rebuilding on modern standards and technology. Existing stations in Nairobi and its environs
are limuru, kikuyu dagorretti, Kibera, Nairobi, Thika, Ruiru, Kahawa, Makadara, Embakasi
and Dandora. All of these stations are operational. It is important to note that the Wayleave
for the railway line was 1km due to urbanization the corridor has been reduced to 30.48m on
either sides of the line. The one for railway stations is 90m.
9
The proposed stations and halts within the study area are: Syokimau, Imaradaima, Gitaru,
Githurai, Thogoto, Lenana, Riruta satellite, Olympic, Ngumo/lainisaba, Nyayostadium,
Kenyatta University, Kariobangi south, KPCU, Mwiki and Donholm/ pipeline. Among the
proposed stations, only the Syokimau station has been completed. The Imaradaima and
Makadara stations are under construction. For all the other proposed stations the construction
has not been started. The Infraco Company is the one responsible for proposal of the stations.
The new stations will be intermodal providing facility parking for cars and Matatu/bus
terminal to provide fast, reliable, safe and affordable commuter rail services and decongest
Jogoo Road and Mombasa Road. The major factors considered during the proposal of the
new stations are:
There has to be an existing line since construction of a new line will cost so much
money which the government cannot afford. A new station proposed on nonexistent
lines is a long term project.
The population. For a new station to be constructed there has to be a large population
that will be served. It is irrelevant to construct a station in a sparsely populated area.
It is also convenient to propose a new station in between stations to decongest them.
This can be established if train traversing the station is normally very congested and
many trips are made in between the stations.
The newly constructed syokimau station is connected to the mainline at Embakasi Station.
The distance between the two stations is two kilometers and the line connecting the two
stations is a newly constructed line. The main purpose of its construction was to offload
passenger traffic from, Mombasa Road that will decongest Uhuru Highway, provide
alternative access to JKIA through a 5 minutes shuttle service. The Station is built for
intermodal exchange for passenger traffic originating from Syokimau Estate, Mlolongo,
Athi/River, Kitengela and the surrounding. The station was officially opened by President
Mwai Kibaki in13th November 2012. Among the unfinished projects is the extension of a
railway line from Syokimau Railway station to the airport. This line is expected provide high
frequency, comfortable and affordable commuter services between JKIA and Nairobi CBD.
The journeys will take less than 20 minutes compared to 90 minutes currently by road.
2.4.2 Commuter train service in Nairobi
10
Commuter train services were introduced in Nairobi in the 1980s to provide a low cost public
transport alternative to the urban poor in the city, following a crippling economic inflation the
country was experiencing at the time. Although the existing railway system in Kenya was
built primarily for moving freight, long distance passenger services had been in operation
between Nairobi and Mombasa, as well as to Kisumu, since the railway service went into
operation in 1903. The Kenya Railways Corporation did not therefore have to acquire any
new passenger wagons for the new service.
Service Coverage
The commuter train service is available on four different lines serving a limited number of
areas in the city, including Kibera to the west of the city, Athi River to the south of the city,
Kahawa to the north of the city and the route to Embakasi. Presently there is a fifth route to
syokimau which where plans are underway to extend it to JKIA. All the lines converge at the
Nairobi Railway Station in the city centre, which also serves as one of the major Matatu
termini in the city. To move from one outskirt to another, one therefore has to change trains
at this station. On average, about 19,000 passengers are transported per day to and from the
outskirts through this service, amounting to less that 1% of the total daily commuters in the
city according to a 2007 report by the Ministry of Roads and Public Works. Due to this
limited capacity, the trains carry sitting as well as standing passengers, with some hanging at
the doors, and the more daring riding on the roof. On the plus side, getting to the city centre
by train is much faster than by road, and more affordable.
Accessibility
Commuters access the station facilities and services by walking to them. They do not follow
roads but instead try to follow the shortest routes most commuters prefer to walk for at least
20 minutes to get to the stations. The new stations that have been constructed contain parking
facilities hence providing a wide service area to get to the stations since driving people can
access the stations.
Schedules
The commuter trains operate on weekdays during rush hours in the morning and evening. The
service is not available on weekends, public holidays, and during certain times of the day
mostly not peak periods. The train picks up commuters at designated stops, it takes
approximately 20-30 minutes between stations. This includes a stoppage of 2 minutes at halts
to pick up or drop commuters.
11
Charges
This is the most cost-effective public transport system in Nairobi with current fares ranging
from a low of Ksh 20 for Kibera, to a high of Ksh 50 for Athi River. Other places fall in
between. The fare to syokimau from Nairobi is Ksh100.
2.5. Vision 2030 and the rail network system
2.5.1. Nairobi Urban Rail Terminal
The present Nairobi Railway Station area, including the yards, is proposed to be developed as
the Central Hub Terminal of Nairobi Mass Rapid Transit System (MRTS). All lines would
originate/ terminate at this terminal or traverse through this terminal. This would enable easy
transfer amongst the lines facilitating the long trips from one point of the region/city tithe
other. The Central Hub Terminal is also proposed to be planned and developed as multimodal
terminal. The main region/city bus/Matatu routes would originate/terminate at the Central
Hub Terminal, thus providing for integration of the different sub-modes of the total public
mass transport system. In addition the terminal would provide extensive parking access for
private modes.
The Central Hub Terminal would provide for seamless transfer amongst all rail lines
converging into it and also amongst all public transport modes of the city. Apart from multimodal complex, the terminal is proposed to be developed as a multi-use complex to contain
high value commercial activities like shops, malls, supermarkets, offices, hotels, information
technology parks, international business centers, cultural institutions etc. This would generate
considerable resources to fund the MRTS development and operations. In addition to the
railway terminal complex, it is proposed that the adjoining areas to be included in the
envelope bordered by Haile Selassie Avenue, Landhies Road, Lusaka Road and Uhuru
Highway. There should be provision to redevelop these areas high intensity commercial cum
office use zone. This would optimize the high accessibility location advantage, provide space
for the increased demand within the CBD due to growth, reduce demand for dispersal system,
and provide a landmark in the urban-scape of the city and, more important, generate
substantial resources for MRTS development.
It is proposed that: The railway land around the Nairobi Railway Station is brought under the
ownership of the authority/agency/SPV responsible for city/region transport system/MRTS
development. Development plans for the Central Hub Terminal as multi modal, multi-use
complex be prepared. The adjacent areas be zoned for commercial use with liberal Floor
12
Space Index (FSI) Property development and MRTS development be integrated to support
each other.
2.5.2. Existing Rail Lines Optimization
Kenyan Railways is planning the rejuvenation of the rail system, as a modern rail system of
about 1400 km length of standard gauge (SG) with high speeds (120 kmph), with ability to
carry heavy loads (4000 tonnes) per rake. It has been proposed that this rail line and system,
within NMR be re-aligned along the proposed regional bypass grid. This will be in the
interest of the railways themselves. It will free them from the constraints of land, geometrics,
urban traffic and other difficulties. With acceptance of the suggested re-alignment and
implemented, the existing rail line within the city would be available for exploitation as part
of city rail (MRT) network system. Three rail lines along the existing rail alignment are
proposed. They are: KR Line 1(NRS to Dagoretti), KR Line 2(NRS to Thika) and KR Line 3
(NRS to Mavoko). It is possible to plan and operate the first two rail lines as one single line
from Thika to Dagoretti via NRS.
In the first phase, the rail lines may be improved retaining the Meter Gauge (MG) and
services operated by Diesel Multiple Units (DMUs). This would optimize the use of existing
rolling stock. As the traffic increases, in the next phase, the rail line(s) may be developed to
the same standards and technology as other lines so that the rolling stack could be common
with the other lines. These three lines run through some of the high density areas where poor
people live and connect to industrial areas. As such they will be of importance in promoting
the mobility of the poor in the city. According to the study, Feasibility Study & Technical
Assistance for Mass Rapid Transit System (MRTS) for the Nairobi Metropolitan Region‟,
the travel demand is even much higher than the extended capacity of the Commuter Rail
System and none of the existing rail corridor deems suitable to satisfy the future demand.
Also, the commuter rail network is not parallel to road corridors. To serve the existing
demand of the development that has been taking place along major road corridors and for the
future expected development, a separate system of MRTS has been proposed.
2.5.3. MRTS Corridors
A Mass Rapid Transport System (MRTS) has been proposed to serve the major corridors as
trunk service. Intermediate Public Transport modes have also been proposed to constitute
feeder services as residential capillary accesses. However, the Commuter rail system is
13
expected to remain as inter-city passenger transport system within the NMR. A numbers of
corridors are identified for the development of the rail based MRT system. Study corridors
with passenger load below 5000 phpdt are expected to be served by the generalized existing
public transit modes such as bus and Matatu. Bus Rapid Transit (BRT) is a road based system
comprising high capacity buses with dedicated lanes either at median or at kerb side. Cost of
initial investment for BRT is much lesser scale than that of a rail based system. A BRT
system can carry passenger from 5000phpdt to 12000 phpdt. Light Rail Transit (LRT) is a rail
based public transport system. It is energy efficient, high speed, high comfort system.
Capacity of LRT is higher than BRT system and can carry passenger from 12000 phpdt upto
30000 phpdt.
2.5.4. Underground MRTS
In the identification of Rail Line (corridors), it has been the assumption that the line will run
as elevated system along the reserve of the road corridors. However, there may be some
objections from urban aesthetics that the elevated track structure would be a physical
obstruction for view of cityscape, particularly in the CBD area and at other locations where
heritage or historical landmarks exist. The system design and materials have developed so
high and sophisticated that it is possible to build elevated MRTS which can add value to
cityscape rather than downgrade it. Also, underground system is extremely costly and the city
may not afford to invest such large sums at this stage. However, if aesthetic values are prime
and funds are not major constraint then, the railway lines may run underground, particularly
in and around the CBD. The probable underground stretches of corridors are: CBD Section of
Thika LRT route, CBD section of Juja LRT corridor, CBD section of Jogoo LRT corridor,
CBD section of Ngong Road LRT corridor and CBD section of Waiyaki Way LRT corridor.
The 5 lines may start/end at NRS with arrangements for transfer amongst them, with other
rail lines and other modes. Also, the 5 lines may be formed into 2 lines, one from Limuru –
Kenya Soil Survey – Westlands – NRS – JK Airport – Mavoko and the other from Thika –
Kenyatta University – Kasarani – NRS – Kenyatta Hospital – Dagoretti – Ngong Town, with
crossing at NRS. The feasibility study will evaluate these underground corridors vis-à-vis
elevated lines and make suitable recommendations.
2.5.3. Stations
MRTS stations along the lines have been tentatively located based on the general principles
of traffic potential, land use, ease of dispersal and physical constraints. The feasibility study
14
would finalize the station locations along the final recommended lines. It is important to
reserve and allocate adequate extent of land at each of the stations for MRTS needs including
parking and dispersal facilities.
Terminal and Inter-change Stations
As the MRTS network is proposed as an integrated system, a number of stations will be
interchange stations, enabling seamless transfer between the lines. NRS will be the most
important and complex interchange station enabling seamless transfer amongst all lines
converging at the terminal.
Interchange Stations
Githurai Station (between Thika Road Line and KR Commuter Rail), Ruaraka Station
(between Thika Road Line and Outer Ring Road Line), Pangani Station (between Thika Road
Line and Juja Road Line), Kariobangi Station (between Outer Ring Road Line and Juja Road
Line), Donholm Station (between Outer Ring Road Line and Jogoo Road Line), Airport Road
Station (between Mombasa Road Line and KR Commuter Rail) and Museum Station
(between Kabete Line and Limuru Line)
Terminal Stations
Ruiru Station (Interchange between LRT, BRT and General PT), Ruai Station (Interchange
between LRT and General PT), JKIA Station (Terminal for BRT), Athi River Station
(Interchange between BRT, KR Commuter Rail and General PT), Bomas Station
(Interchange between BRT and General PT), Dagoretti Corner Station (Interchange between
LRT, BRT and General PT), Kabete Station (Interchange between LRT, BRT and General
PT)
Source (G.o.K, 2008)
2.6. Geographical information system
Geographic information system (GIS) is a system designed to capture, store, manipulate,
analyze, manage, and present all types of geographical data that is spatially referenced and at
all scales. The acronym GIS is sometimes used for geographical information science or
geospatial information studies to refer to the academic discipline or career of working with
geographic information systems. In the simplest terms, GIS is the merging of cartography,
statistical analysis, and database technology. A GIS can be thought of as a system—it
digitally creates and manipulates spatial areas that may be jurisdictional, purpose, or
application-oriented. Generally, a GIS is custom-designed for an organization. GIS
15
applications are tools that allow users to create interactive queries (user-created searches),
analyze spatial information, edit data in maps, and present the results of all these operations
(Clarke, 1986). GIS uses spatial-temporal (space-time) location as the key index variable for
all other information. Just as a relational database containing text or numbers can relate many
different tables using common key index variables, GIS can relate unrelated information by
using location as the key index variable. The key is the location and/or extent in space-time.
2.7. Gis in transportation
The main advantage of using GIS is its ability to access and analyze spatially distributed data
with respect to its actual spatial location overlaid on a base map of the area of coverage that
allows analysis not possible with the other database management systems. The main benefit
of using the GIS is not merely the user-friendly visual access and display, but also the spatial
analysis capability and the applicability to apply standard GIS functionalities such as
thematic mapping, charting, network-level analysis, simultaneous access to several layers of
data and the overlayment of same, as well as the ability to interface with external programs
and software for decision support, data management, and user-specific functions (Vonderohe,
1993).
The major planning in different aspects of transportation network can be attributed to the lack
of availability of large volume of data required for this purpose. Even if this data is made
available, the next problem is how to manage and access that data. The valuable information
related to existing transport infrastructure is scattered all over the country at different
organizations. The attribute data of the network is available in pieces in different
organizations of the state level system, and it is rarely utilized effectively by planners. At
present any exercise on sufficiency of the existing network in the regional context or
nationwide plan generation for primary network like expressway cannot use any of the
existing data. Thus practically the present available data at a large number of locations in all
possible formats are waste and resources spent for collection and maintenance of this data is
draining the economy as a routine ritual and not fulfilling the objectives (Fazal, 2001).
The use of GIS for transportation applications is widespread. Typical applications include
highway maintenance, traffic modeling, accident analysis, and route planning and
environmental assessment of road schemes. A fundamental requirement for most
16
transportation GIS is a structured road network. Additional information concerning general
topography, land cover and land use is pertinent to the consideration of the impact of
construction. The lack of appropriate data for GIS remains a chronic problem. GIS describes
a world in terms of longitudes and latitudes and other projection systems consisting of a
hierarchical structure of graphical objects. The typical GIS represent the world as a map. The
major requirements and issues surrounding GIS management technology are building and
maintaining a database, selecting and upgrading hardware and software, using the technology
to solve problems, funding, networking, providing access, and others. Standard GIS functions
include thematic mapping, statistics, charting, matrix manipulation, decision support system,
modeling and algorithms and simultaneous access to several databases. The main advantage
of using GIS is its ability to access and analyze spatially distributed data with respect to its
actual spatial location overlaid on a base map of the area of coverage that allows analysis not
possible with the other database management systems. The main benefit of using the GIS is
not merely the user-friendly visual access and display, but also the spatial analysis capability
and the applicability to apply standard GIS functionalities such as thematic mapping,
charting, network-level analysis, simultaneous access to several layers of data and the
overlayment of same, as well as the ability to interface with external programs and software
for decision support, data management, and user-specific functions (Vonderohe, 1993).
The existing database does not allow the user to manipulate, access, and query the database
other than in a very limited way. The user is limited to textual queries only, the selection and
viewing of crossing attribute data with respect to spatial and topological relationships is not
possible. Over related data, such as land use, population, and the road network characteristics
of the area in the crossings vicinity, cannot be accessed in the present database. This ability of
GIS, along with the final presentation of results on a digital base map, will allow the user a
better perception of the problem, enable better decisions, and allow a better understanding of
what is to be achieved in a broader sense. The ability to define conditional queries, perform
statistical analysis, create thematic maps, and provide charting chances the crossing safety
program by allowing for better understandability of the data. Furthermore, the ability of most
GIS software to provide many basic transportation models and algorithms may also be useful
in specific situations. The ability to link up to external procedures and softwares also
provides flexibility, as these procedures can access data within the GIS and present the results
of analysis to the GIS for viewing and analysis (Waters, 1992a).
17
2.8. Gps (global positioning system)
The Global Positioning System is extremely useful in precise positioning of geospatial data
and collection of data in the field. Hence it is a valuable tool in GIS data collection, surveying
and mapping. The GPS is divided into three major components. They are the control
segment, the space segment and the user segment. All three segments are required to perform
positional determination. The control segment consists of five monitoring stations spread
over the globe. The space segment consists of the constellation of Earth-orbiting satellites.
The user segment consists of all Earth based GPS receivers. The GPS uses satellites and
computers to calculate positions anywhere on earth based on satellite ranging. Using the GPS
for field data collection, data such as longitude, latitude height (and sometimes time), can be
recorded instantly. We can integrate GPS positioning in GIS.GPS is an effective tool for GIS
locational data capture. The GPS can be easily linked to a laptop Computer in the field, or the
data fed into a PC, and with appropriate software, users can place all their data on a common
base with little distortion. GPS is also used in remote sensing methods such as
photogrammetric and aerial scanning. GPS is very advantageous in the construction of
accurate and timely GIS databases (B. Hofmann et al., 2001).
2.9. The Geodatabase
Geodatabase is simply the short form for Geographic database, and database that contains
geographic or place information. In its simplest form, it can be thought of as a container for
storage of information used in a GIS system. The preferred storage mechanism is the file
Geodatabase for individual users and small workgroups. It is stored in binary format within a
file folder and each subfolder can be up to a single terabyte (1TB) in size. Geodatabase can
be stored within standard multiuser relational database systems including Oracle, IBM‘s
DB2, Microsoft SQL server and even the open source PostGreSQL. These are attached to
ArcGIS system through use of ArcSDE and support extremely large database systems.
The terminology used to construct a geodatabase is hierarchical. The feature dataset is created
inside a file geodatabase. It is composed of feature classes that have been grouped together so
that they can participate in the relationship with each other. All the feature classes must share
the same coordinate system and spatial reference. Feature classes are simple objects, points,
polylines and polygons. The three types of geodatabase are personal geodatabase, file
geodatabase and ArcSDE geodatabase. The characteristics of a file geodatabase are that it is
18
stored in a folder, stores up to one TB per dataset, used in any platform, has single editor and
few readers few readers and does not require versioning.
Figure 2.1: Structure of a Geodatabase
Source (ArcGIS 9.3.1 help information, 2007 edition)
2.10
. Suitability in GIS context
Suitability analysis in a GIS context is a geographic, or GIS-based process used to determine
the appropriateness of a given area for a particular use. The basic premise of GIS suitability
analysis is that each aspect of the landscape has intrinsic characteristics that are in some
degree either suitable or unsuitable for the activities being planned. Suitability is determined
through systematic, multi-factor analysis of the different aspect of the terrain (Murphy,
2005). Model inputs include a variety of physical, cultural, and economic factors. The results
are often displayed on a map that is used to highlight areas from high to low suitability
A GIS suitability model typically answers the question, "Where is the best location?"
Whether it involves finding the best location for a new road or pipeline, a new housing
development, or a railway station, For instance, a commercial developer building a new retail
store may take into consideration distance to major highways and any competitors' stores then
combine the results with land use, population density, and consumer spending data to decide
on the best location for that store.
19
2.11. Summary of other similar project
2.11.1. Analysis of Bus-stops locations using Geographic Information System in
Ibadan North L.G.A Nigeria.
This study focuses on the determination of best location for bus stops to enhance public
transport in Ibadan north, Oyo State. The significance of having suitable locations for Bus
stop is recognized as a crucial element in the drive to improve the quality of bus services and
public transport in general. This study employs the tools of Geographic Information System
(GIS) in the determination of the suitability of the bus stops location, stop spacing and the
evaluation of characteristics of the existing stops in the study area. The major roads and bus
stops in Ibadan North Local Government were identified and the roads were digitized as line
features. Garmin 12 Global Positioning System Receiver (GPS) was used to get the locations
of the bus stop. The GPS was calibrated to Geographic Coordinate System (GCS) and World
Geodetic System 84 (wgs84) as the datum. For this study, determination of best locations for
the bus stop is based on three (3) criteria; these are four hundred (400) meters bus stop
interval on the major road, available setback from the road ideal for bus Stop shelter and
slope. Thereafter, poorly located bus stops were identified by adding the existing bus stop
layer on the suitability map derived from determination of best locations for the bus stops. In
all, seventy two (72) existing bus stops were identified, using the stated criteria for
classifying the already existing bus stops. The analysis showed that there are four (4) very
good bus stops, thirty five (35) good bus stops and thirty three (33) bad bus stops. The paper
recommends that guidelines for locating stops should be followed to reduce the risk,
accessibility to stops should be considered by standard spacing and by considering marginal
walking distance (Olowosegun et al, .2012).
20
CHAPTER THREE
MATERIALS AND METHODOLOGY
3.1. Overview
This chapter seeks to describe all the operations and procedures carried out in order to come
up with the final output. The following have been covered: the description of study area,
description of all the data sets used in this project and how they were used, the methodology
that was adopted in carrying out the study. It also describes the data capture process which
includes how the data was identified, collected, prepared, extracted and corrected for errors
before being used for analysis. Data preparations are all process meant to put data in an
organized manner and in a manner compatible with GIS software without altering their
original form, such processes included conversions, georeferencing, creating of Geodatabase,
organizing population statistics, clipping and organizing tabular data. Data extraction is the
process of generating more data and information from already prepared data. The data
generated in this stage was a useful output for analysis function that was next carried out. The
types of data extraction carried out here are: digitizing, updating attribute tables, Euclidean
distance calculation and slope calculation. Data correction and verifying of the data was done
to make sure it was correct and could be used in analysis and also be imported into the
Geodatabase. The data analysis was also covered in this chapter. Analysis are common Gis
functions such as database query, derivative mapping and modeling applied to data to
generate information.
3.2.
Area of study
Nairobi is the capital city of Kenya, in East Africa. The city is located 1 ° 16'South and 36 °
48' East, 140 kilometers (87 miles) south of the Equator. The city is at altitude 1,680 meters
(5,512 feet) above sea level hence it enjoys tolerable temperatures year round (CBS 2001,
Mitullah 2003). It has an area of 689 sq km (266 sq mi) at the south-eastern end of Kenya‘s
agricultural heartland. The average daily temperatures range from 29º C in the dry season to
24ºC during the rest of the year. The mean annual temperature is170C and mean daily
maximum and minimum are 230C and 120C respectively. The average annual rainfall is
875mm, with variation range 500-1500mm.The western part of the city is the highest, with a
21
rugged topography, while the eastern side is lower and generally flat. The Nairobi, Ngong,
and Mathare rivers traverse numerous neighborhoods and the indigenous Karura forest still
spreads over parts of northern Nairobi. The Ngong hills are close by in the west, Mount
Kenya rises further away in the north, and Mount Kilimanjaro emerges from the plains in
Tanzania to the south-east. Minor earthquakes and tremors occasionally shake the city since
Nairobi sits next to the Rift Valley, which is still being created as tectonic plates move apart.
At a population growth rate of 4.7-4.8% annually, the population of Nairobi grew from about
0.8 million in 1979, to 2.1 million in 1999 and 3.1 million in 2009. The environs of Nairobi
include Kiambu district, Machakos district, Thika district and Kajiado district part of which
are included in this study.
Figure 3.1: Area of study
3.3. Data sources and tools
3.2.1. Data sources
22
Table 3.1: Data collected
DATASETS
DATA SOURCE
Digital maps of Nairobi and survey of Kenya
environs.
Satellite images
Google earth
Road maps, and sub ILRI Website
location maps/ location
maps, land use map and
topography data
Geographical coordinates Kenya railways corporation
(KRC)
of railway stations
Field work and Google earth
imagery
Commuter train tables
Population statistics
RVR
KNBS
CHARACTERISTICS
Scales
(1:25000, 1:250000)
Geo eye, 0.1m resolution, as
at 2011
Shape files
Excel worksheets from KRC,
GPS coordinates in UTM
projection, Arc 1960 datum
from field work.
Excel worksheets
As at 2009 in hard copy form
a) Digital maps of Nairobi
Digital map of Nairobi was obtained from survey of Kenya in jpeg and tiff formats covering
sections with railway coverage. The map clearly showed buildings, railway line roads and
open spaces which were important for the study. The maps also had grids superimposed on
the contents and coordinates shown as well as the marginal information. Names of features
were also visible. The main purpose of the maps was to be used as base maps to digitize and
overlay other data.
b) ILRI Shapefiles
The shapefile obtained for this study were, road maps, location and sub location maps and
land use maps. They were already georeferenced hence they could also be used as base maps.
The shape file of roads contained their attributes such as their names and length. The roads
covered areas of interest. The shape file containing information about Nairobi province sub
locations and locations was obtained from ILRI website. It covered the study Area (Nairobi
and environs). This data was used to assist in analysis of the distribution of railway stops
23
within the study area. The shapefile also contained attributes such as names and areas of the
locations.
c) Geographical coordinates
An excel worksheet containing the coordinates of all the existing old railway stops within the
study area was obtained from Kenya Railways Corporation. The coordinates of the newly
constructed railway stations were obtained by carrying out field work using a handheld GPS.
The coordinates of the proposed railway stations were obtained from Google earth images
that were obtained from Kenya railways showing their locations. The coordinates were used
to show the spatial distribution of the railway stops.
d) Population statistics
A hardcopy record of the 2009 general census was obtained from Kenya National Bureau of
Statistics. The relevant fields were entered into an excel worksheet to be used in the analysis.
The population statistics were needed to help in carrying out the analysis of railway stops
distribution.
3.2.2. Tools
Hardware

Computer with specifications of 80 GB memory, 0.99 RAM and 2.00 GHz of
speed.

A hand held Gps (Garmin 60Cxs)

A flash disk of 4GB space

Printer

A digital camera
Software

Arc GIS 9.3

Arc View GIS 3.2a

Global Mapper V10

Adobe Photoshop v7.0

Adobe reader v10

Microsoft office 2007 suite
24
3.4. Overview of methodology
Figure 3.2 represents a summary of the methodology used in carrying out this study. The first
step in the methodology was data identification. Spatial and non spatial data were collected.
Georeferencing was carried out, Shapefiles were created by digitizing, attributes of all the
data were added into the attribute tables of the feature classes. Querying criteria was built to
identify all the available information about a station or a route depending on the interest of
the user. Results were displayed and highlighted on the digital map. Overlay, buffering and
suitability analysis was also done to find out the area served by a specific station, the
suitability of existing stations and identify new sites for building new railway stations within
the existing ones.
Spatial data (digital
maps, coordinates
and shapefiles)
Data
Data preparation
(transformation,
importation and
georeferencing)
No
Is data
correct?
Data
editing
Data collection
identification.
Non spatial Data
(commuter tables and
population statistics)
No
Data organization
(input into Ms excel
and save as csv file
format)
YES
Geodatabase
creation
ANALYSIS
Overlay analysis,
Buffering,
querying
suitability analysis
Discussion of
results
Figure 3.2: Methodology schema
25
3.5. Data capture
This involved the processes of identification, collection, data preparation, data extraction and
correction of errors for the data necessary to build the Geodatabase and further carry out
analysis.
Data
identificati
on
Digital and
analog
data
collection
Data
preparatio
n
Data
extraction(
Digitization
and
Editing)
Add to GIS
database
YES
Is Data
correct
?
NO
Figure 3.3: Flow chart showing process of data capture
3.5.1. Data identification
During this stage, data to be used in the project was identified. The sources of the data were
identified through visiting relevant institutions. Such institutions included the survey of
Kenya, Kenya urban roads authority, Rift valley railways, city council of Nairobi, Kenya
Railways Corporation and other private institutions.
3.5.2. Data collection
This stage involved getting the identified relevant data from the relevant source. This data
was in analogue and digital forms requiring different collection methods. The data collection
also involved field work using a hand held Gps.
26
a) Analogue data collection
The data collected through this means was written materials from some institutions by getting
their photocopies. Such Data was the population statistics from KNBS.
b) Digital data collection
Portable memory devices were used for collection (4GB flash disk). The data collected
through this means were digital maps of Nairobi, shape files for roads, railway lines and
location maps and excel tables. Before this data was collected it was evaluated for quality,
completeness and complexity.
c) Field work using Handheld Gps
The coordinates of all the newly constructed stations were obtained by carrying out field
work using a handheld Gps that was obtained from the department. This coordinates did not
exist in the RVR or the KRC database. In order to obtain the coordinates of the stops, the Gps
was held with the hand at a corner of the station building and making sure there was no
obstruction of the signal, the Gps was allowed to settle after a minute where the accuracy
achieved was +/- 3m which is the allowed accuracy when using a GPS. The new railway line
was picked by boarding a train from Nairobi railway stop to Syokimau Railway stop, and
then the Gps was set to pick the line while in the train at intervals of a minute as the train
moved. The coordinates obtained were in UTM projection, Datum Arc 1960 and Spheroid
Clarke 1880.
The field work was also to do ground truthing by visiting the various stations. The stations
visited were Imaradaima, Syokimau, Dandora, Kikuyu, Nairobi railway station and
Makadara. The purpose of visiting the stations was to perform a ground truthing, establish the
facilities contained at each of this stations and to determine the amount of time taken when
using the train as compared to the roads.
3.5.3. Data preparation
a) Downloading GPS coordinates
The GPS coordinates obtained during the field work were downloaded from the GPS and
saved in an excel worksheet. This was done by connecting the GPS to a computer via a cable
and using the software to download.
27
b) conversions
This is the process of converting images to formats recognized by particular software. The
digital maps obtained from survey of Kenya were in PDF and JPEG formats also the satellite
images were in PDF formats, GIS could not open the PDF images and there was need to
convert them to a format recognized by it. Adobe Photoshop v7 was used to import rasterize
and save the image in JPEG file interchange format. The JPEG format is usually compressed
and hard to maneuver using most GIS software hence Global Mapper was used to export the
images in tagged interface file (TIFF) format. Railway stop coordinates and other excel
tabular data were saved in text files (csv comma delimited) which could be imported and
opened in ArcGIS.
Conversion to raster from vector data
For suitability analysis purposes, the vector data was also converted into raster data using the
raster conversion tool in ArcGIS. This was done so that it would be possible to reclassify and
weight the data. The data converted to raster was the population data and land use data.
Conversion of Excel worksheets
Original excel work sheets could not be used with ArcGIS in text formats. They were
converted into CSV comma delimited formats. The data converted into this formats were the
geographic coordinates of the Railway stops, commuter tables and population statistics.
c) Georeferencing
Georeferencing is the process of linking an image to a map projection system using a
geometric transformation. A transformation is a function that relates the coordinates of two
coordinate systems. A coordinate system consisting of a set of points, line, and/or surfaces,
and a set of rules, used to define the position of points in space in either two or three
dimensions. A map coordinate system is defined using a map projection. The ability to
accurately describe geographic locations is critical in both mapping and GIS. Georeferencing
enables elements in a map layer to be located on or near the earth‘s surface and to be viewed,
queried and analyzed with other geographic data. This process requires spatial reference
information which are geographical coordinates of control points within the area covered by
the map image. On maps, locations are given using grids, graticules and tick maps labeled
with various ground locations (both in measures of latitude-longitude and in projected
28
coordinate systems such as UTM meters). Root mean square (RMS) is the error in distance
between the input location ground control points (GCP) and their transformed location for the
same GCP. RMS error is calculated with the equation below
RMS error= ((xr-xi) 2-(yr-yi) 2)1/2
Where xi, yi are input source coordinates and xr, yr are transformed coordinates.
Georeferencing map images
Map images were loaded using global Mapper version 10, map mounting was done using
four corner points as GCP. Since the map images were at large scale, the geographical
coordinates of the four corner points could be read, the universal transverse Mercator
projection was used and the datum used was Arc 1960. The georeferenced image was then
exported in TIFF format for use in ArcGIS. RMS resulting was zero which was acceptable
for the project.
d) Defining map projections
For all shape files, map projection was set using Arc Catalogue which was done before
carrying out any form of processing. The shapefile whose extents did not match already
existing shapefile were converted using ArcView GIS 3.2a. Projection was set for the whole
study area, also Arc datum 1960, and spheroid: Clarke_1880_GRS and UTM projection zone
37s were used.
e) Coordinates of the railway stops
The coordinates of the railway stops obtained from Kenya railways and field work were
initially saved in excel files in text formats, were now saved as CSV comma delimited and
exported into arc map as shapefile and as tables too. They were classified into old stations,
new stations and proposed stations.
f) Creation of a Geodatabase
A Geodatabase is a collection of geographic datasets of various types used in GIS and
managed in either a file folder or a relational database. It is the native data source for GIS and
is used for editing and data automation. To create a file Geodatabase, a Geodatabase was
created in arc catalogue and named railwaygeodatabase.Gdb, feature datasets were then
created inside the geodatabase, and then finally the feature classes were created inside the
29
feature datasets. To populate the geodatabase with more data, the feature classes and tables
were imported into it. It contained the following feature classes: roads, railway line, rivers,
railway stops and study area. It also contained feature datasets such as railway station tables
and commuter tables and raster images. The tables in the geodatabase could be opened and
edited in excel.
g) Creation of a route travel times tables
The commuter table obtained from RVR could not be used in ArcGIS as it was hence it was
simplified into two tables. The table contained the departure and arrival times of different
trains from and to Nairobi railway stations. The table was simplified into a table showing the
departure times to Nairobi station and another from Nairobi station. The tables are as shown
on table 3.2 and table 3.3 consecutively:
Table 3.2: showing simplified commuter table of departure to Nairobi
30
Table 3.3: showing simplified commuter table of departure from Nairobi
h) Joins and Relates
Joining data is typically used to append the fields of one table to those of another through an
attribute or field common to both tables. For this exercise a join was created between location
shapefile and census data in excel. The census data joined to the shapefile appeared as part of
the attribute table of locations. The resultant shapefile was named cencus_2009. Relate is an
operation in ArcGIS that establishes a temporary connection between records in two tables
using a key common to both of them it can also be a connection between a shapefile and a
table. Relating tables simply defines a relationship between two tables. The associated data
isn't appended to the layer's attribute table like it is with a join. Instead, you can access the
related data when you work with the layer's attributes. For this study, the route shapefile was
related to departure to Nairobi and departure from Nairobi tables (route travel time tables).
When this was done, on identifying the attributes of the route, the related attributes are also
displayed.
i) Population statistics
The hard copy data of population obtained from KNBS was entered into excel worksheet and
saved as CSV comma delimited which then was joined to the shapefile of location. The
population distribution was represented as a percentage of the total population calculated
using the formula below:
Percent population = population in a location/ total population
Five classes were generated using the symbology property in ArcGIS. The census data that
was entered in excel was joined to the location shapefile such that it appeared as additional
31
attributes of the locations. The result was a choropleth map showing how the population was
distributed within the study area. The distribution was shown using graduated color
symbology as shown on figure 3.4.
Figure 3.4: Choropleth map showing population Distribution within the study area.
j) Clipping
Clip is an operation in ArcGIS that is used to enable a GIS user extract his/ her area of
interest. For this study, most shapefile covered the whole of Kenya yet the study area was
Nairobi and environs, hence clipping was used to extract the area of interest.
3.5.3. Data extraction
a) Digitization
Digitizing is the process of converting features into digital format. This process creates new
data. One can digitize on screen or heads up over an image, digitizing a hard copy of a map
on a digitizing board or using automated digitization. For the sake of this study, onscreen
digitization was used. The features of interest were digitized and they included railway line,
rivers and open spaces. These features were necessary for the identification of appropriate
railway stops and enriching the Geodatabase. After digitizing, other data which was obtained
as shape file was plotted on the digitized map.
32
b) Updating attribute table
After digitizing attribute tables are added by default in ArcGIS these default attribute tables
had default fields which record location information about features. More fields were added
to the default attribute table. They included names, areas lengths and descriptions of
geographical features that were digitized. Attribute tables of point data was imported from
excel and more attributes added in their resulting attribute tables by adding more fields to
describe the stops.
c) Data editing
The main tasks in editing digitized graphic data includes
a) Error correction: errors such as gaps in linear features, error in edited polygons and
lines joining at wrong places were corrected.
b) Entering missing data: details left out accidentally during digitization were verified
visually on screen and entered in digitizing environment
Tables were also checked for completeness and spelling of words. Also autolabelling of
features was used to check information stored in attribute tables. When all the errors were
checked for, the feature data sets were imported into the Geodatabase.
3.6 Analysis
3.6.1. Buffering
A buffer zone is an area that is within a given distance from a map feature. When you buffer
on a set of features, the output is a set of polygons. Buffering points or lines creates a new
polygon layer. These polygons define an inside region, an area less than the specified buffer
distance from the features of interest (e.g. less than 90 meters from the railway line), and an
outside region, an area more than the specified buffer distance from the features of interest.
These inside and outside regions are typically distinguished by different codes in an attribute
table. A fixed distance buffer as used for this study applies the same distance for each of a set
of features in question. Fixed distance buffering may be applied to points, line, or polygon
input, and creates polygon output. For this analysis fixed distance buffers were used. All the
existing and proposed stations were buffered. Buffering was also done for the railway line to
show the Way leave or corridor for the railway line.
33
Railway line buffer
The two buffers of the railway line were drawn. The first buffer was 500 meters on either
sides of the railway line. The other buffer was 30.48meter buffer on either sides of the
railway line. The purpose of the buffers was to show the corridor or the Wayleave for the
railway line. The 500m buffer represents the buffer on either side which was set aside for the
line during the colonial times when there was enough land for development and expansion.
The buffer also shows the region within which a railway station should be located and it‘s
also the region within new stations should be located.
Figure 3.5: Railway line Buffer
Due to current increase in demand for land the size of the buffer has reduced to the 30.48 m
buffer.
Service area analysis buffers
34
A service area also known as station domain is an area around a station with a boundary up to
which the station usually attracts passengers to use its services. Service area buffers were
created for each station to show the area served by a particular station. Two assumptions
were made which were that people access the station services by walking to the stations and
they are willing to walk at a minimum speed of 5km/h for at most 20 minutes which
translates into a distance of 1666m. The buffers were created for the old railway stations
only. The buffers were done for the old railway stations so as to be able to visualize regions
that do not have access to the services and also justify the building of the new stations and
proposal of the new stations along the existing lines.
3.6.2. Suitability analysis
Figure 3.6 represents the process of carrying out suitability analysis. The suitability analysis
was done to identify suitable sites for locating new railway stations relative to the existing old
stations, this analysis was also used assist in determining if the new and the proposed stations
are within the suitable sites. The layers used for the analysis are slope, population, distance
from other stations, distance from the railway line and land use. These layers represented the
constraints that were used in determining suitable sites for a railway stop. The process
involved calculating all the Euclidean distances, converting the vector population and land
use data into raster. Reclassification was then carried out to assign weights to classes within a
map layer. The final suitability map was obtained by carrying out a weighted overlay.
35
Best site for a
new railway
station
Close to the
railway line
Away from
existing stops
On large
population
density areas
Calculate
distance
Euc_dist to
stops
Relatively flat
land
Calculate
slope
Convert to
raster
Calculate
distance
Euc_dist to
line
Suitable land
use
Convert to
raster
Percent
population
Land use
Elevation
Reclassification
Weighted overlay
Suitability map
Figure 3.6: Flow chart showing the simplified process of carrying out suitability analysis
1) Euclidean distance calculation
36
The Euclidean distance functions describe each cell's relationship to a source or a set of
sources. Euclidean Distance gives the distance from each cell in the raster to the closest
source. Example of usage in this study is: What is the distance to the existing railway stops?
Or what is the distance of a station from the railway line? The Euclidean distance output
raster contains the measured distance from every cell to the nearest source. The distances are
measured as the crow flies (Euclidean distance) in the projection units of the raster, such as
feet or meters and are computed from cell center to cell center. The Euclidean Distance
function is used frequently as a standalone function for applications, this function can be used
when creating a suitability map, when data representing the distance from a certain object is
needed. For this study, the distance to each station was calculated and the distance to each
railway line was calculated too and the output was in raster format. This type of information
was extremely useful for finding a suitable site for a new station since a new station has to be
located a certain distance from the existing stops. It should also be located a certain distance
to the line.
Figure 3.7: showing the wizard for Euclidean distance to existing stations and the resulting distances on a map
37
Figure 3.8: showing the wizard for Euclidean distance from the railway line and the resulting distances in a map
The above is the Euclidean distances to all the existing stations as in figure 3.7 and Euclidian
distances to the railway line as shown in figure 3.8. The maximum distance within which
Euclidean distances were calculated was set to 1000m since a railway stop on existing line
cannot be beyond that distance.
2) Calculation of slope
The slope data was obtained by converting a DEM (digital elevation model) to slope using
the slope calculator tool in the arc toolbox of ArcGIS. The slope distance was important since
a station cannot be located on a very steep slope.
3) Reclassification
Reclassification is the process of assigning weights to various classes of a map layer
according to how important they influence an output. Each map layer was ranked by how
suitable it was as a location for a new station. Values were assigned to each class in each
layer on a scale of 1–10, with 10 being the best. This is often referred to as a suitability scale
and the process of assigning these values is called reclassification. No Data was used to mask
off areas that should not be considered. Having all measures on the same numeric scale gave
them equal importance in determining the most suitable locations. For each map layer, they
were divided into classes and the values for each class in each layer were related to scale 1-10
with most suitable having a value 10 and the least suitable assigned a value of 1.
4) Weighted overlay
38
The last step in the suitability model was to combine the reclassified outputs (the suitability
maps). To account for the fact that some objectives have more importance in the suitability
model, the datasets were weighted, giving those datasets that should have more importance in
the model a higher percentage influence (weight) than the others. The most preferable
objective to satisfy was to locate the stations where there was large population, and the next
is to locate away from existing stations then close to existing line. The following percentage
influences shown on table 3.4 were assigned to the suitability maps. The values in
parentheses are the percentage divided by 100 to normalize the values. These normalized
values were assigned to each suitability map during the weighted overlay process:
Table 3.4: percent weight of influence assigned to factors influencing location of railway stops
Factor
Percentage Influence
Ratio of influence
Percent population
35%
0.35
Distances to railway line
10%
0.1
Distance to other stations
30%
0.3
Slope
10%
0.1
Land use types
15%
0.15
39
CHAPTER FOUR
RESULTS AND DISCUSSION
4.1. Overview
This chapter undertakes on explaining and describing the results that were acquired during
data preparation and analysis that was carried out during the implementation of this project.
The main analysis functions carried out for this project were proximity studies (buffering),
overlay analysis and suitability analysis using spatial analyst extension tool. In the view of
the set objectives the following results were obtained:

A digital map showing spatial distribution of the stations.

A digital map showing the main railway line routes including the new route.

A Geodatabase that contained various elements that were used for analysis.

Attribute tables containing the attributes associated with every railway stations( their
coordinates, facilities at each station, description of the stations and other
information)

A map showing the service areas served by existing railway stations.

A suitability map showing the best sites to locate new railway stations and to help
appreciate or criticize the location of the currently proposed stops.
4.2.
Digital maps
The resulting digital maps were as a result of georeferencing, mosaicking, clipping
overlaying and digitizing.
4.2.1. Spatial distribution of the railway stops in the study area
The railway stations were classified into new, old and proposed stations and plotted on the
digital map. The map also showed the old railway line together with the newly constructed
2km line from Syokimau to Embakasi railway station. Figure 4.1 is the map showing the
distribution of the Railway stops within Nairobi and its environs.
40
Figure 4.1: map showing distribution of termini within Nairobi and its environs
4.2.2. Railway line routes
The five routes of the railway stations were represented on the digital map in different colors.
The routes were digitized from the topographical map. The attributes for each route were
length, id and name of the route. Other attributes which were joined and related to the route
could be displayed by clicking on the route. The length of each route was calculated using the
attribute table calculator. The route was named according to the station at the end and
beginning of the route. It‘s important to note that all the routes originate from Nairobi station
which can then be referred to as an interchange station. Figure 4.2 shows the railway line
routes.
41
Figure 4.2: map showing the classification of railway line route within the study area
All the layers were then overlaid to come up with the final map on figure 4.3, of study area
showing all the classes of railway stops, railway line and other conspicuous features that were
used to carry out the spatial analysis of the railway stops. Among the 29 stops mapped, 17
were old stops, 3 new stops and 9 proposed stops. The map is important since it helps the
commuters to identify the location of a station by looking at the features surrounding it. It
simply helps in orientation purposes.
42
Figure 4.3: map showing spatial distribution of railway stops within the study area
43
4.3.
The Geodatabase
A file Geodatabase was created and named railwaygeodatabase.gdb.The Geodatabase was
populated with feature datasets (census, railway stations, railway line and study area) with
each feature dataset containing feature classes. Tables and the raster images were included in
the Geodatabase. The Geodatabase provides an easy way of organizing the data and also
retrieving it since all the information is stored in one basket. The result of the populated
Geodatabase is shown on figure 4.4 below:
Feature dataset
Feature class
Tables
Figure 4.4: Railway stations Geodatabase
4.4.
Attribute data
Attribute data was created and entered for all the feature classes stored in the Geodatabase.
The attribute information for digitized features was added manually in the attribute table. The
data in excel files/worksheets was joined or related to the default attribute tables for specific
feature classes. The attributes in excel about the arrival and departure times were joined to
both the routes and the stations feature classes. Table 4.1 and table 4.2 below show an
44
example of attribute tables showing attributes of stations entered manually into the attribute
tables.
Table 4.1: attribute table showing part of the attributes of new stations
Table 4.2: attribute table showing attributes of the old stations
a) Displaying the attributes of desired features
In order to identify and display information in the attribute tables about a route or a railway
station or the other feature classes, the identify tool was used. Using the identify tool and
clicking on an item on the map, all the information about that feature was displayed as long
as was available in the attribute table or if it was joined or related to the particular feature
classes. For example identifying attributes of a station (e.g. Syokimau).
45
Figure 4.5: showing the identified attributes of syokimau railway station
The identify tool was also used to retrieve information about route and travel times for all the
stations by clicking on the route or the station since the travel time tables were related to
route layer as shown in the example below. When identify tool was placed on Nairobi Kikuyu
route it displays the information shown on figure 4.6 below:
Figure 4.6: showing the attributes of the railway routes as a result of relate operation
46
b) Querying the attribute table
Any desired information as long as it was contained in the Geodatabase could also be queried
and the result displayed on the map and the attribute table. To identify which stations use the
electronic ticketing method, select by attribute function is used as shown on figure 4.7 below;
Figure 4.7: query expression on definition query tab of the railway station attributes
The results of the query are highlighted on table 4.3. It is only Nairobi railway station that
uses electronic ticketing method among the old stations.
47
Table 4.3: showing the highlighted result of the query in fig 4.7
The result above is also highlighted on the map (the blue color) as shown on figure 4.8
Figure 4.8: showing highlighted station on the map phase as a result of the query operation
The query technique enables one to find just the required information but the identify tool
displays all the information there is about the feature class in question as long as its stored in
the Geodatabase. The information in the attribute tables has only been organized for this
project. A commuter or a decision maker from any organization wanting to access this
information can‘t because it is not available online. In order for it to be useful, an online
application is supposed to be developed (web based mapping) so that it can be accessed by
anyone anywhere with internet accessibility.
48
4.5.
Service area analysis Results
From figure 4.9, it‘s evident that not all the areas where the railway line is passing through
have access to the railway stops. It can be seen that there is a deficiency in rail transportation
services. The areas not served are those in between the railway stops. Indeed there is a
deficiency for railway services in the region.
Figure 4.9: map showing station domains
4.6.
Overlay Analysis
Overlay is an analysis operation carried out in ArcGIS in order to come up with the final map
in order to identify hidden trends. The map on figure 4.10 shows an overlay for the service
area buffers together with the new and proposed stations.
Figure 4.10 show that the new stations have been constructed within the areas where there is
no buffer coverage. The proposed stations too are within the same buffer coverage. It‘s
evident from the map below that there are areas between the service area buffers with no
49
stations proposed. These were established to be some of the possible areas to construct new
stations but subject to more analysis.
Figure 4.10: An overlay of station domains with all the railway stations
An overlay was also created for population distribution map with service area buffer and all
the railway stops. Figure 4.11 represents the overlay. The population of kamukunji, pumwani,
kaloleni, makongeni and starehe has low population according to the choropleth map. This is
so because they are not residential areas. The population needing transportation services is
high in these locations since people come to work in these places and they definitely need
transportation back to their residential areas. A railway station within this area is very
convenient. It can be seen that the railway line traverses regions with high population except
the section of Tigoni location. The existing stations are also located in the locations with high
population. This is an indication that they are appropriately located considering the factor of
population. All the proposed stations are in highly populated locations. There is no proposed
50
station between limuru and Muguga since it‘s a region of low population. There are also
locations away from the railway line whose population is high yet they do not have railway
services. Such locations are kawangware, kangemi, Eastleigh, kasarani and Mathare. These
regions would also be termed as suitable sites to build railway stops although they will
require a railway line construction first.
Figure 4.11: An overlay of the station domains and railway stops on the population distribution map
4.7.
Suitability analysis results
The suitability analysis was carried out so that other factors such as land use and topography
could be included in determining suitability of the railway stops.
a) Reclassified datasets
51
Figure 4.12: Reclassified land use
The land use was divided into seven classes as shown in the map legend. The forest class was
assigned a value of 1since it was not suitable to build a railway stop and town class had a
value of 7 since it was suitable to build railway stops.
The reclassified Euclidean distances from the existing railway stations were as in figure 4.13
shown below. The most suitable areas are those away from the existing stations. The current
allowed distance between stations is 25-30km although other factors come to play and they
could not be captured in this study. From the map it‘s evident that value of 10 was assigned
to the most suitable region and 1 to the least suitable as shown on the legend.
52
Figure 4.13: Reclassified Euclidean distances from existing railway stops
The map of percentage population was converted to raster. It showed areas with high to low
population. Since the map was in raster form, reclassification was carried out. Value10 was
assigned to the area with high population which was the most suitable for locating a railway
station. Value 1 was assigned to lowly populated regions. This is illustrated in the figure 4.14.
The population that is best served by a railway line is one close to a railway line. For the
purposes of this study, new railway stations should be built on an existing line. The closer a
place is to the existing line the more suitable it is. Hence areas closer to the railway line were
given higher value than those far away. This is illustrated on figure 4.15. The legend showed
the assigned values.
53
Figure 4.14: Reclassified percentage population
Figure 4.15: Reclassified distances from the railway line
54
Figure 4.16: Reclassified slope
The slope which represents topography is a factor that is very essential for location analysis.
Reclassification was done and 3 classes were created, the low medium and high. Regions
with high slope were less suitable for locating New and proposed stations.
b) Combining the suitability maps/ weighted overlay.
Once the suitable sites have been established from the spatial analysis, verification should be
done by visiting the site to see what actually exists on the ground which might have not been
accounted for. The final suitability map is on figure 4.17. It is the result of combining
population, slope, distance to existing stations, distance to the railway line and land use.
55
Figure 4.17: Suitability Map
The proposed and new stations were then overlaid on the suitability map on figure 4.18 and
the following suitability was established: stations located on the most suitable sites (value 6)
are Githurai, Mwiki and Riruta railway stations. Those located on the next suitability (value
5) were KPCU, pipeline, Lenana, Ngumo/lainisaba, Gitaru and Olympic stations. Donholm,
Nyayo stadium and Thogoto stations were located on the next suitability level (value 4). This
was an indication that they were appropriately located considering all the five constraints. It‘s
also evident that some of the suitable sites have no proposed stations yet they are suitable
regions. With suitability map no single location can be selected but more suitable region is
identified. The new stations overlaid on the suitability map also lie on the suitable sites hence
they were correctly located. The least suitable sites identified on the suitability map are
regions with existing railway stops.
56
Figure 4.18: An overlay of the railway stops on the suitability map
From the figure 4.18 above, it‘s evident that there are some suitable sites where other railway
stations could be proposed. These sites were marked in green as shown on figure 4.19. One
such site is in Tigoni location between Muguga and limuru railway stations, the other is in
Eastleigh between Nairobi railway station and Makadara station. The dots do not indicate the
exact position on the ground but their purpose was to highlight the suitable sites. Further
survey of those sites should be carried out to determine the exact positions on the ground.
The survey will take into consideration the availability of public land which could not be
covered in this study.
57
Figure 4.19: proposed sites for other railway stops
4.8. Chart Analysis
a) Trips per route
The commuter table obtained from RVR containing the departure and arrival times for each
route enabled the prediction of the number of trips made by the trains during the morning and
evening journeys. This data was generated and represented in the chart on figure 4.20:
Table 4.4: trip table
Route
Total trips
Evening Trips
Morning Trips
Nairobi-Kahawa/Ruiru
Nairobi-kikuyu
Nairobi-Embakasi village
Nairobi-Athiriver
Nairobi-syokimau
10
2
6
2
3
4
1
3
1
2
6
1
3
1
1
58
Figure 4.20: Trip frequency chart
The Nairobi Kahawa route had many trips as compared to the other routes. This could be
attributed to the large population living in those locations around that section of the railway
line.
59
CHAPTER FIVE
CONCLUSIONS AND RECOMMENDATIONS
5.1.
Conclusion
A digital map showing the spatial distribution of railway stops was successfully drawn as
shown on figure 4.3. The map showed a total of 29 railway stations, the railway line, rivers
and roads. All the available information about the railway stops was also successfully
collected and entered into the attribute table. This information could be displayed by using
the identify tool or using the query tool.
A map of demographics was successfully drawn which showed the percentage of population
as per locations. When the stations were overlaid on it, it was clear that the railway line
traverses between the regions with high population. This was a good indication that those
who planned the railway line had considered the population factor. Within the areas where
there was no railway line the population was high and it was an indication that transportation
services were vital.
The suitability analysis was carried out successfully, the suitability of proposed and new
stops were determined. Three other suitable sites were identified as shown on figure 4.17.The
suitability study showed that most proposed stations were located in the suitable areas.
The chart also showed that the route to Ruiru had many trips to and from Nairobi railway
station. The route with fewer trips was the one to kikuyu this was attributed to the
discrepancies in the population distribution.
Due to limitation of time and financial resources, samples of 10 stations were visited during
field work. From the visit to syokimau, the newly constructed railway station, it was evident
that there were no people residing around the station say a distance of 5 km away. This is an
indication that people from around cannot be able to walk to the stations hence it does not
adequately serve the area. The transport cost to and from syokimau is 100 shillings which is
very expensive as compared to 50 shillings payed when one boards a Matatu, this also is an
indication that people would not opt for it as a means of transportation. The train to syokimau
serves people best in the evenings when it carries commuters from Nairobi and passes
60
through the Makadara and Dandora stations otherwise considering the financial status of
people they would not opt for this train.
The new railway stations being constructed have parking facilities which means that people
from far off place can access the train services by parking the trains at those stations and
boarding the train. This will help reduce the traffic jam along the major roads. The syokimau
stations decongests Jogoo road hence Mombasa road. It‘s also faster using a train to and from
Nairobi since the train does not stop on the way. From a comparison done during the field
work, it takes only 30 minutes to get to Nairobi from syokimau using a train and at least an
hour when using the Matatu.
From the study it is clear that Gis is a powerful with enormous functionality and applications.
It is a tool that is very useful in identifying trends and problems and coming up with solutions
to them .it helps represent the larger picture on just a map face with all the parameters
associated to it.
5.2.
Recommendations
As Nairobi is growing and hence population the transport demands are increasing which
cannot be met by the bus services only. The government should make sure it implements its
proposals regarding the construction of the new railway stops and be committed to improve
the conditions of existing stations to make them more attractive to the commuters so that they
opt for the railway transportation.
From the study it is evident that the only areas served by the railway are those along the
railway. Regions where we have a large population yet no rail, there should be constructed
railway lines hence railway stations. Such areas are kasarani, Mathare, Embakasi, Eastleigh,
kangemi and kawangware.
A web based application should be created by the commuter service managers so that the
digital maps and all the attribute tables associated with them can be displayed online. When
this happens the commuters can be able to access the information at the comfort of their
mobile phones or laptops.
A passenger information system should be created so that as people wait at the stations, they
can be informed of delays or change of plans. There should be a way of informing the public
in advance if the trains will not operate on certain days of the week
61
REFERENCES
1. AletaVienneu (1999). Using Arc Catalogue.
2. ArcGIS.
A
complete
Integrated
System.
http://www.esri.com/software/arcgis/index.htm.
3. B. Hofmann- Wellenohof and H. Lichtenegger and J. Collins, (2001). Global
positioning system theory and practice. Springer- verlagwienNewyork.
4. Clarke. K. C., (1986). Advances in geographic information systems, computers,
environment and urban systems, Vol. 10, pp. 175–184.
5. ESRI (2007). ArcGIS 9.2 Help, Online Manual. Environmental System Research
Institute
Inc.,
Redlands,
California.
WWW
document,
http://webhelp.esri.com/arcgisdesktop/9.2/ [accessed12th January 2013]
6. Evaristus M. Irandu, (October 2000). Improving railway transport in kenya:policy
options and achievement to date. Usaid/redso/esa’s strategic objective # 623-002-01:
Ph.D.University of Nairobi Increased use of critical information by USAID and other
decision-makers in the region.
7. Fazal, s. (2008). GIS Basics. India: Ram printographdelhi.
8. Fowler H W and Fowler F C, (1995). The concise oxford Dictionary 9thed
9. Government of kenya ,(2008).Nairobi Metro 2030.ministry of Nairobi metropolitan
development
10. Julian Ross, Jeremy Rewse Davies, (1998).railway stations planning, design and
management.
11. Jambonairobi,(2011).Commuter
Train
Services
in
Nairobihttp://www.jambonairobi.com.
12. MairuraOmwenga,(2011).Integrated
Transport
System
for
Liveable
City
Environment: A Case Study of Nairobi Kenya, 47th ISOCARP Congress 2011
13. Michael D. Murphy, (2005).Landscape Architectural Theory.
14. OlowosegunAdebola andOkokoEnosko, (2012).Analysis of Bus-stops locations using
Geographic Information System in Ibadan North L.G.A Nigeria.Department of
Transport Management Technology, School of Management Technology, Federal
University of Technology.
62
15. T.L.C. Vinodh, C.M.K.T. Chandrasekara, A.M.K.T. Abeysinghe, R.A.B.V.
Ranasinghe, J.M.S.J. Bandara, (2008). A Methodology to identify an Optimum Rail
Network for Colombo Metropolitan Region. ENGINEER - Vol. XXXXI, No. 05, pp.
105-115,
16. Vonderohe, A. P. Travis, L., Smith, R. L. and Tasai, V., , (1993), Adoption of
Geographic Information System for Transportation, Transport Research Board,
National Research Council, NCHRP Report 359Washington, DC,
17. Waters N M, (1992a), Relational databases and the development of GIS_The
operational Geographer.
18. William W Hay,(1989).An introduction to transportation Engineering_history and
development of public transportation
63
APPENDICES
Appendix 1: Coordinates of old railway stops obtained from KRC
STATION
Nairobi
EASTING NORTHING HEIGHT
Central 258307.28
9857417.38
1660.21
Station
Kibera
251481.35
9855968.8
1773.83
Dagoretti
243644.26
9857370.9
1888.73
Kikuyu
238599.12
9862450.79
2039.78
Muguga
238258.76
9869858.96
2144.67
Limuru
237600.59
9877078.79
2238.47
Makadara
262681.69
9856668.67
1635.91
Dandora
265867.58
9861086.85
1598.22
Kahawa
267589.47
9868989.13
1553.28
Ruiru
272980.36
9873083.32
1526.53
Embakasi
265501.39
9851011.11
1638.61
Marimbeti
271446.12
9843783.77
1558.45
Athi River
274639.29
9840024.66
1508.22
Appendix 2: GPS Coordinates of new stations
Station
easting
Northing
Imaradaima 263343
9853426
Makadara
263034
9856719
Syokimau
266991
9849850
Appendix 3: Coordinates of proposed railway stops obtained from Google earth
imagery
Station
Easting
Northing
Donholm
264671.54
9856461.89
Kariobangi
264314.57
9859070.53
kalimoni
279599.06
9887766.54
KU
269623.43
9869847.18
64
Githurai
268575.97
9866649.12
Gitaru
240903.23
9861465.40
Thogoto
241943.87
9858289.62
Lenana
246150.74
9856020.20
Riruta
248660.94
9856244.36
Nyayo
257795.98
9853808.39
Ngumo/lainisaba
255855.86
9854894.22
Olympic
253331.19
9854735.15
KPCU
268025.88
9862086.93
Mwiki
270431.92
9863080.51
pipeline
265739.07
9854448.90
Appendix 4: sample population statistics obtained from KNSBS
Fid
Location
Total
Households % population
population
0
biashara
46636
14486
1.966
1
Juja
34134
11233
1.439
2
gatuanyaga
9047
2316
0.381
3
Ruiru
59679
19356
2.516
4
limuru
42878
11719
1.808
5
Tigoni
11511
3749
0.485
6
ndeiya
26387
6327
1.112
7
ngecha
12473
3410
0.526
8
kikuyu
45720
12842
1.928
9
Kahawa
56437
14950
2.379
10
Muguga
45901
12936
1.935
11
nyathuna
28771
7794
1.213
12
roysambu
47678
15003
2.01
13
parklands
11117
3312
0.469
14
Kabete
41460
12802
1.748
65
15
njiru
49453
15411
2.085
16
kasarani/Ruaraka
252646
79225
10.652
17
karai
31452
8339
1.326
18
kinoo
72525
22332
3.058
19
Dandora
142046
47808
5.989
20
Kariobangi south
55989
17119
2.361
21
Mathare
87097
31426
3.672
22
kangemi
80699
26859
3.402
23
kalimoni
43122
11350
1.818
24
Embakasi
87970
25982
3.709
25
eastleigh
174389
47820
7.352
26
starehe
9857
2366
0.416
27
bahati
44823
13439
1.89
28
ngara
25354
7749
1.069
29
kawangware
113286
38249
4.776
30
waithaka
31054
9439
1.309
31
Makadara
48489
13516
2.044
32
Riruta
99334
31407
4.188
33
pumwani
23052
7539
0.972
34
mutuini
17973
5454
0.758
35
s/area
21789
6651
0.919
36
kamukunji
19591
6757
0.826
37
maringo/mbotela
25396
8031
1.071
38
viwanda
71390
27740
3.01
39
kaloleni/makongeni 20063
6280
0.846
40
Kenyatta/golf
35355
9401
1.491
course
41
Karen/Langat
33303
5434
1.404
42
kibera/Woodley
87549
28878
3.691
43
mugumoini
47037
13079
1.983
66
67