Assessing the Accessibility of Fire Vehicles in Khulna City

Assessing the Accessibility of Fire Vehicles in
Khulna City
The Thesis Submitted to the Department of Urban and
Regional Planning, Khulna University of Engineering
& Technology (KUET), in Partial Fulfilment of the
Requirement for the Degree of
Bachelor of Urban and Regional Planning.
Session: 2017-2018
Submitted By
Arijit Biswas Arghya (1417011)
Department of Urban and Regional Planning
Khulna University of Engineering & Technology
April,2019

Khulna City
Session: 2017-2018
Submitted By
Department of Urban and Regional Planning
Khulna University of Engineering & Technology
April,2019

Khulna City
Submitted by
Session: 2017-2018
This thesis in its content is the intellectual property of the submitting student.
The submitting student is solely responsible for the citing and referencing of
literature and avoiding plagiarism. The thesis supervisor and committee
members are not responsible for any plagiarism and data manipulation.
Thesis Supervisor
Palash Chandra Das
Assistant Professor
Department of Urban and Regional Planning,
KUET.
Examiner
Md. Esraz-Ul-Zannat
Assistant Professor
KUET.
Head of the Department
Dr. Md. Mustafa Saroar
Professor and Head
KUET.
April,2019

Khulna City
Submitted by
Session: 2017-2018
Thesis Supervisor
Palash Chandra Das
Assistant Professor
KUET.
Examiner
Md. Esraz-Ul-Zannat
Assistant Professor
KUET.
Head of the Department
Dr. Md. Mustafa Saroar
Professor and Head
KUET.
April,2019

i
ACKNOWLEDGMENT
Firstly, I would like to thank to God for His grace so that I can complete this Undergraduate
Thesis. I would also like to thank my thesis supervisor Palash Chandra Das, Assistant
Professor, Department of Urban and Regional Planning, Khulna University of Engineering &
Technology, Khulna for the patient guidance, encouragement and advice he has provided me
throughout the time. I was extremely fortunate to have a supervisor who took so care of my
work and answered all our questions so prompt. It was a privilege for me to work under his
supervision. I would like to thank my thesis external Md.Esraz-Ul-Zannat, Assistant Professor,
Department of Urban and Regional Planning, Khulna University of Engineering &
Technology, Khulna for his invaluable support and advices.Mr. Ripon Karmakar,Graduate
Research Assistant of Memorial University of Newfoundland who helped me during my
ongoing research and he gave me some valuable advices during my work. Finally, I wish to
thank my parents for their love and encouragement, without whom I would never have enjoyed
so many opportunities.

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ABSTRACT
Urban fire is one of the serious issues in developed and developing countries now -a-days. It
causes serious damage to properties and habitats. A huge amount of property and lives got
damaged due to fire. In our country there is lack of accessibility of fire vehicle in extinguishing
fire. The main objective of this study is to investigate the accessibility of fire vehicles in the
Khulna City. Khulna city corporation area has been selected as the study area. Fire incident
occurred between 2016-2017 was geocoded in ArcGIS and spatial analysis was performed to
know the pattern of fire incidents’ model has been adopted here to identify the area which are
vulnerable to fire hazard in terms of accessibility & site suitability analysis for locating future
fire station will be determined. ArcGIS network analysis has been performed in this study to
determine the response coverage of existing fire station. An OD matrix will be generated and
Finally a geodatabase was developed to identify the optimal path from the closest fire station
to the incident spot. About 30.70% area are found highly vulnerable area in terms of
accessibility. It has been found that only 25.23 % area can be covered by the existing fire
stations within 4 minutes which represents the poor accessibility of fire vehicle. Among 143
high vulnerable destination, 96 destinations can be reached by the existing fire stations in 8
minutes. To cover all the destinations with the existing fire stations maximum time required
from the closest fire stations is 17.4014 minutes. Finally, a road network geodatabase was
created for determining the optimal path from the closest fire stations to incident location which
is based on travel time. BFSCD Khulna can use this geodatabase in route choice during fire
rescue mission and this database can be used for making routing application.
Keyword: Urban fire, Fire Vehicle Accessibility, Network Analysis, AHP, Optimal Path, O-
D Matrix, Site Suitability, ArcGIS, BFSCD

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TABLE OF CONTENTS
ACKNOWLEDGMENT………………………………………………………………………I
ABSTRACT…………………………………………………………………………………. II
TABLE OF CONTENTS………………………………………………………………...III-IV
TABLE OF LISTS…………………………………………………………………………...IV
TABLE OF LISTS…………………………………………………………………………...V
Chapter 1: Introduction .....................................................................................2
1.1 Background .................................................................................................................2
1.2 Objective .....................................................................................................................4
1.3 Justification .................................................................................................................4
1.4 Scope...........................................................................................................................4
1.5 Limitations ..................................................................................................................5
Chapter 2: Literature Review............................................................................7
2.1 Basic Terminology......................................................................................................7
2.1.1 Fire Incident ...........................................................................................................................7
2.1.2 Fire Services ...........................................................................................................................7
2.1.3 Response time........................................................................................................................7
2.1.4 Service Area ...........................................................................................................................8
2.2 Bangladesh Fire Service & Civil Defense (BFSCD) ..................................................8
2.2.1 Standards and Codes of Fire Service......................................................................................9
2.3 Different Research on Fire ..........................................................................................9
2.3.1 Incident Pattern .....................................................................................................................9
2.3.2 Incident Density Mapping....................................................................................................10
2.3.3 Fire Vulnerability Mapping...................................................................................................10
2.3.4 Response Time modelling....................................................................................................11
2.4 Case studies:..............................................................................................................11
Chapter 3: Study Area Profile.........................................................................14
3.1 Study Area.................................................................................................................14
3.2 Land Use Profile of the Study Area ..........................................................................14
3.3 Khulna Fire Stations..................................................................................................15
Chapter 4: Methodology...................................................................................18

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4.1 Desk Review .............................................................................................................18
4.2 Study Area Selection.................................................................................................18
4.3 Data Collection..........................................................................................................18
4.4 Data Preparation........................................................................................................19
4.4.1 Creation of Geodatabase .....................................................................................................19
4.4.2 Building Network Topology..................................................................................................19
4.4.3 Building Network Dataset....................................................................................................20
4.5 Incident Pattern Distribution.....................................................................................20
4.5.1 Nearest Neighborhood Method...........................................................................................20
4.6 Vulnerability Mapping..............................................................................................21
4.6.1 Analytical Hierarchy procedure ...........................................................................................21
Steps of AHP..................................................................................................................................23
4.7 Existing Response Coverage.....................................................................................25
4.8 Site Suitibility Analysis for Fire Station ...................................................................26
4.9 Origin-Destination Cost Matrix ................................................................................27
4.10 Optimal Path..............................................................................................................27
Chapter 5: Analysis...........................................................................................29
5.1 Existing Scenario of Roads .......................................................................................29
5.2 Incident Pattern Distribution.....................................................................................29
5.3 Vulnerability Mapping..............................................................................................31
5.4 Existing Service Area................................................................................................35
5.4.1 Percentage of the Served Area:...........................................................................................37
5.4.2 Landuse Wise of Area Coverage : ........................................................................................37
5.5 Suitable Site for Future Fire Stations........................................................................38
5.6 Origin-Destination Cost Matrix ................................................................................40
5.7 Optimal Path..............................................................................................................42
Chapter 6 :Findings & Conclusion..................................................................46
References..........................................................................................................47
Appendices…………………………………………………………………………………………………………………..……50-61

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LIST OF TABLES
Table 1.1: Year-wise number of fire incidents and economic loss in Bangladesh....................3
Table 3.1: Existing land use classification of KCC.................................................................13
Table 3.2: Khulna Fire stations names and locations ..............................................................14
Table 4.1: Sources of data........................................................................................................17
Table 4.2: Speed according to the classification of road .........................................................18
Table 4.3: Value of R and its Pattern.......................................................................................18
Table 4.4. The intensity of relative importance scale developed by Satty. .............................21
Table 4.5: Criteria for locating future fire station....................................................................25
Table 5.1: Area percentage of the vulnerability map...............................................................33
Table 5.2: Land Use wise of area coverage .............................................................................40

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LIST OF FIGURES
Figure 3.1: Fire station location...............................................................................................15
Figure 4.1: Types of pattern.....................................................................................................20
Figure 4.2: Selection of the number of sub-criteria ...............................................................23
Figure 4.3: Writing the name of the criteria and sub-criteria ..................................................23
Figure 4.4: Assigning the level of importance.........................................................................24
Figure 4.5: Priorities of sub-criteria.........................................................................................24
Figure 5.1:Fire vehicle road accessibility percentage..............................................................29
Figure 5.2: Incident Location...................................................................................................30
Figure 5.3: Average Nearest Neighborhood Analysis Report .................................................31
Figure 5.4: Vulnerability map using AHP ..............................................................................34
Figure 5.5: Service area of fire stations ...................................................................................36
Figure 5.6: Percentage of area coverage..................................................................................37
Figure 5.7: Site suitability map...............................................................................................39
Figure 5.8: Origin destination map.........................................................................................40
Figure 5.9.: Origin-Destination cost matrix............................................................................41
Figure 5.10: Optimal path based on travel time.......................................................................42
Figure 5.11: Direction of Optimal path based on travel time ..................................................43
Figure 5.12: Optimal path based on length..............................................................................44
Figure 5.13: Direction of Optimal path based on length .........................................................44

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Chapter 1
INTRODUCTION

Assessing the Accessibility of Fire Vehicles in Khulna City
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Chapter 1: Introduction
1.1 Background
Urban areas are vulnerable to different types of natural and man-made hazards. It is one of the
intense issues in developed and developing countries. It is a disastrous event which creates
damages to life and property. Urban fire is a threat to human lives and habitats. Sometimes fire
becomes so destructive if any effective measure has not been taken (Hossain, 2016).As the
urban area is more densely populated and it is more prone to fire. ( Rahmawatia, et al., 2016).
With a huge population density, it is difficult to respond to the fire incident. Day by day
population is increasing, as a result, it has become more complex to manage rescue operation.
Around 54% of the world's population resides in urban areas and is projected to rise to 66% by
2050 (World Urbanization Prospects, 2014)
Bangladesh is one of the densely populated countries. After the liberation war of 1971,
the total population of Bangladesh has been increasing at the rate of 1.37% per year and the
urban population is growing at about 3.27% per year (BBS Statistical Year Book 2013).
Recently the fire incident of Dhaka chalk bazar killed 78 people. Effective handling of this fire
requires sufficient planning response system (Forku & Quaye-Ballard, 2013).
Time is a vital role in rescuing operation of fire. Fire can expand in its volume within a
minute and it can be said that more travel time or response time results in more losses (ESRI,
2012). Table 1.1 represents the number of deaths and the total amount of economic loss due to
the fire incidents occurred in the last nine years in Bangladesh.
Fire services are responsible for protecting human lives, habitats, and property (GIS for
the fire service, 2012). In Bangladesh fire service and civil defense ensure the fire safety. Fire
safety depends on the capacity, service area and accessibility of fire vehicles. Accessibility is
an important term in recusing. Fire vehicles cannot reach the accident spot through all roads.
Location of the nearest water source close to the incident area is also a big concern. As time
plays a crucial role so the route choice for fire vehicles is the most important thing to reach the
incident site in the shortest time

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Table 1.1: Year-wise number of fire incidents and economic loss in Bangladesh
Source: Annual report of BFSCD 2018
Travel time is not the same for all roads. Different roads have speed limits. The path
which is the shortest in distance might require more travel time to reach the incident site. It
cannot be said that the shortest route is the optimal route. According to the Authority of
Bangladesh Fire Service & Civil Defense (BFSCD) unplanned overpopulated areas of the city
are regarded as the most inaccessible site (Islam, et al., 2017).If the fire vehicles could reach
earlier to the spot the amount of economic losses and the number of deaths can be minimized.
According to the National Fire Protection Act (NFPA), all areas should be reached within 4
minutes from the fire station (Cote, 1997).
The frequency of fire incident is comparatively low than Dhaka city as it is less densely
populated. In August 2018 two people have burned to death and nine people are seriously
injured at the Meghna oil depot in Khulna. (Molla, 2018) The fire broke out at FR Jute
Mill in Khulna city on 27 March 2018 in Khulna city. It took 15 minutes to reach the incident
spot with an economic loss of 100 crores (Azad, 2018)
The fire incident of Khulna city is not negligible. Effective planning is required for
efficient rescue operation. Here a GIS-based analysis performed for vulnerability mapping,
incident pattern analysis, suitability analysis for new station location and developed a GIS-
based system which can be used for identifying the optimal route from the fire station to
incident spot.
Year
Economic loss
(Billion)taka
Death
2010 3.25 719
2011 2.93 1385
2012 4.82 759
2013 7.79 1385
2014 3.59 210
2015 8.56 216
2016 2.40 247
2017 2.57 269
2018 3.85 664

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1.2 Objective
The objective of this research is
✓ To investigate the accessibility of fire vehicle in Khulna City.
The research will look in to identify those area which are vulnerable to fire hazards in terms of
accessibility, Incident pattern of fire incident, response coverage of existing fire station in
different response time, site suitability analysis for locating future fire station will be
determined. An origin destination cost matrix will be generated and Finally a geodatabase was
developed to to identify the optimal path from the closest fire station to the incident spot.
1.3 Justification
A GIS-based road network dataset has been created to locate an incident spot and find out the
best route to reach the affected area from the fire station. In our country, GIS-based emergency
service is not available. There are several difficulties in choosing the route. Emergency rescue
vehicle chooses the route according to their personal experience which may not be the optimal
route. As a result, the response time increases. One of the important purposes of the study is to
reduce the response time. To select the optimal route a GIS-based system has been developed.
While vulnerable zones have been identified and existing coverage map of the fire station will
be generated. Effective integrated fire rescue system and operation can be developed by the
fire service and civil defense of Bangladesh.
1.4 Scope
Many factors can be considered for fire vulnerable zone mapping in terms of accessibility. But
due to lack of data, all factors could not be considered. One of our main objectives is to create
a vulnerability map of Khulna city. Vulnerable zone mapping was constructed by adopting
expert opinion survey and GIS-based analysis. We also determine the area which are less
accessible. The response coverage of the existing fire station is determined by network analysis.
The area which cannot be covered in standard response time will also be identified. A suitability
analysis will be performed for a new location for the future fire station. Finally, a GIS-based
system has been developed for the optimal route from the fire station to fire incident which is
based on the travel time.

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1.5 Limitations
Every study has some limitations. This study has some too. The limitations are difficult to
overcome but here we tried to mitigate as far as possible. The limitations are given below:
1. Real-time travel time is not considered. Here average speed of the vehicle has been used
according to the road category. Travel time is not always same all the day long. It varies
different time of the day. There are many roads which are so busy during peak hour. This type
of data is not available in our country. For more accuracy those types of data are needed.
2. Traffic congestion is not considered as it is not constant all the day long for all the roads.
3. Road condition was not considered, whereas vehicle speed depends on the condition of the
road. Pucca and smooth road has higher speed. On the other hand if the road condition is bad
it decrease the speed of vehicle.

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Chapter 2
LITERATURE REVIEW

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Chapter 2: Literature Review
2.1 Basic Terminology
2.1.1 Fire Incident
Fire incident can be occurred by human or natural process. Human life and property are
proportional to the acuteness of fire incidents. Fire is actually an oxidation process (Addai et
el.,2017) and caused by different intensities of heat and light. Fire mainly occurs due to the
unconscious human behavior and misuse of utilities and it can spread in any direction within a
minute.
2.1.2 Fire Services
Fire service is one of the government's most important services, and efficient deployment is a
key factor in responding to service calls in time. The responsibility of the fire service is to
protect life, property and natural resources against fire and other emergencies. (GIS for the fire
service, 2012)
2.1.3 Response time
Response time is the time that is required for fire vehicle to arrive the spot from the fire station.
It is mainly the travel time. Response time is one of the most manageable segments of times in
the entire sequence. It can be managed by choosing the strategic fire station locations based on
the amount of time that it takes to travel from the fire station along the most efficient travel
route to the occurrence spot. (GIS for the fire service, 2012).
The response period is divided into 4 categories according to the Oklahoma City Fire
Department Fire Station.
Call Processing and Dispatch –This time starts when the caller responds to the call and ends
on sending the first unit.
Turnout – This is the time from dispatch to departure from the station (or other location)
Travel - This period begins with the departure of the station and ends when the unit arrives.
Vertical – This is the amount of time from arrival at the scene to arrival at the side of the patient
or the site of the fire

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2.1.4 Service Area
The area where the fire fighter can reach to an incident location within standard response time
is regarded as service area. The station's specified coverage area must not be greater than the
station's standard service area.
2.2 Bangladesh Fire Service & Civil Defense (BFSCD)
In Bangladesh, Fire Service and Civil Defense (BFSCD) Directorate is the first respondent in
all natural and manmade calamities and remains alert round the clock to fight fire and surface
rescue operations.
Activities of BFSCD
The most important part of national protection is firefighting and emergency management. The
only authorized department in Bangladesh is the Fire and Civil Defense Service (BFSCD) to
act as first answer and to operate during a disaster. They organize different training courses for
departmental staff both domestically and internationally in order to perform their functions
efficiently. Simultaneously, trainings for community volunteers and other nation - building
organizations, schools and colleges are organized.
Rules, Regulations & code
According to “Fire Protection and Extinguishing Act, 2003” act the BFSCD is empowered to
use water from any source to extinguish fire. Beside this act, in Bangladesh National Building
Code, 2014, some development rules for building construction and road lay out design have
been set. The final draft of the code is prepared and is planned to convert it into a law for
ensuring public safety including fire safety. In this code, some standards have been
recommended to facilitate fire service as well as to make ease the fire-fighting activities of the
fire fighters. According to this rule (section 1.7):
a) The access facilities of building shall meet the requirements of fire service vehicles and
engines movement for rescue and fire extinguishment operation.
b) For fire apparatus, access roads shall have an unobstructed width of 4.8m and the minimum
vertical clearance of 5m. The width and vertical clearance for the access of fire apparatus may
be increased according to the opinion of the fire extinguishing authority.

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c) For large Assembly Occupancy of I1 (large scale assembly with fixed seat of 1000), I3(large
scale assembly without fixed seat of more than 300 people) and I5 (assembly for watching
sports), width of the approach road shall not be less than 15 m.
d) Access roads longer than 30 m having a dead end shall be provided with appropriate
provisions for turning around of the fire apparatus at the dead end
2.2.1 Standards and Codes of Fire Service
Different countries have different standard response time. But in our country, there is no written
standards. National NFPA (National Fire Protection Association), a non - profit, global fire,
electric and related hazard reduction organization founded in 1896. NFPA is the world's leading
fire prevention activist and a leading public security source. The aim of this international not -
for - profit organization, which offers and promotes scientific - based consensual codes and
standards, research, education and training (About NFPA,2014), is to reduce the global burden
of fire and other life hazards. In the event of any fire incident, the NFPA specifically developed
response time standards. There are also standards on number of fire fighter according to
population demand and number of fire fighters to operate firefighting equipment and vehicles.
In Bangladesh, there is no standard on coverage area, serving population size and staff level in
accordance with population demand (About NFPA,2014). In addition, there are no guidelines
on specific types and capacity of vehicles in the field.
2.3 Different Research on Fire
Fire stations have the greatest role to play in the event of an emergency and inadequate service
leads to huge loss of property and human life. Many research projects deal with the distribution
of fire events, placement and Vulnerability mapping, Existing Response coverage, Site
suitability analysis of future fire stations.
2.3.1 Incident Pattern
Incident pattern analysis refers to spatial statistical analysis. For decision makers, it is very
much important to know the pattern of the incident. Nearest neighborhood index analysis in
ArcGIS tells us the pattern of the incident either it is concentrated or random Travel-This period
begins with the station's departure and ends when the unit reaches the scene. They also applied
NNI (Nearest Neighborhood Index) and found that crimes in Beijing are not randomly
distributed and hotspots of fire incidents also identified by performing kernel density.

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2.3.2 Incident Density Mapping
The intensity, frequency, and the season of burn of fire determine the fire regime or zone
(Williams et al. 2001). In GIS environment there are 3 types of density under spatial analyst
tool. They are line density, point density, and kernel density. The kernel density tool calculates
the magnitude of the point or polyline functions per unit area using a kernel function to fit each
point or polyline with a smoothly tapered surface. Kernel density has been used by many
researchers to determine the densest area of occurrences and incidents (Parajuli et.al.,2017). In
view of the forest fires in Nepal. The Kernel Density model was used to determine the high,
medium and low fire risk zone. The quartic density estimate was made by Wing & Long(2015)
to create a continuous surface, representing the large scale observation of fire in Oregon and
Washington (Wing & Long, 2015).
2.3.3 Fire Vulnerability Mapping
Naima Rahman Conducted a study on physical and social fire hazard vulnerability assessment
in Dhaka City. Physical vulnerability factors were selected on the basis of literature reviews
and opinions of local fire experts. The methodology which used here was developed by World
Bank (2014) for social vulnerability. Using ArcGIS, the result of vulnerable zone mapping was
obtained. Rahamawati(2016) developed social, physical and economic vulnerability index of
urban fire risk in Kampung Nyamplungan city.There are many methods for vulnerability
mapping. Analytical Hierarchy Process is one of them. Many researches have used this method
for risk mapping.
Analytical Hierarchy Process
The analytical hierarchy (AHP) process could also be used for determining the level of
significance of the risks in risk assessment as an efficient method (Ali Kokangül et el.,2017).
Xin-Ming Dong (2018) Used AHP model for urban fire risk assessment and represented it as
a fire demand point map.To generate the fire potential zoning map of Kathmandu metropolitan
City AHP method was conducted (Chhetri & Kayastha, 2015). Criteria which are selected for
fire potential zoning map are land use, distance from the fire station and population density.
Alam and Baroi (2014) have assessed the fire hazards risk in Dhaka City using GIS and
developed a framework for categorizing fire hazard and risk mapping. Srivanit obtained the
technique of the Analytical Hierarchy Process (AHP) to create a Chiang Mai municipality fire
risk map. In the study, the author used six vulnerability factors: (i) building material types, (ii)
building height, (iii) building density, (iv) population density, (v) occupancy of building
hazards, and (vi)distance from available fire sources.M.M Yagoub applied AHP model for

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weighting the criteria that have been selected for suitable location plan for the future fire
station. Weighted overlay analysis was utilized to propose a new station location.
2.3.4 Response Time modelling
ArcGIS is one of the common platforms of response time modelling. Using network analysis
response time modelling have been performed.
Network Analysis
It’s an extension of ArcGIS which is based on Dijkstra’s algorithm. ArcGIS Network Analyst
enables you to overcome problems of the common network including selecting the best route,
finding the nearest emergency vehicle or facility, selecting the best facilities for opening or
closing(Dabhade et al.,2015).In Solapur city, a study was performed which used network
analysis to find out the optimal path and service area of emergency services like the fire station,
hospital, blood bank, ATM with respect to the road of the city (Mali & Mane, 2013). Remote
sensing & GIS technology have been used to calculate the accurate distance & time from
incident to the facility(Dabhade et al.,2015). .They used network analysis to identify the
shortest route to the closest health center from their location. dynamically and existing service
area of health facilities have been drawn out here. Which is helpful for reducing their travel
time and finding the nearest hospital.
2.4 Case studies:
Case Study 1:
Eric K. Forkuo and Jonathan A. Quaye-Ballard conducted a study on GIS-based fire
Emergency response System in 2013 in Ghana. Their objective was to establish a GIS
(Geographic Information System) based fire emergency response services which will be very
effective to identify the optimal route from its location to any fire incident. They used Network
Analyst extension for the optimal path and geospatial analysis was performed to suggest new
locations for fire hydrants. The Authors provides a visual representation in GIS interface and
showed the optimal path between fire incident and fire station and also showed the path from
incident spot to the nearest hospital. Here the optimal path is the lowest impedance or lower
cost. Higher impedance is more resistant in mobility. Various impedance factors such as traffic
volume, road condition road width number of junctions and turns, one-way restriction are
considered in determining the optimal route. The impedance factor of each road segment is
updated in the road network dataset. Using Dijkstra’s algorithm in a network analysis optimal
path have been calculated.

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Case Study 2:
A study on the fire potential zoning map of Kathmandu Metropolitan Nepal in 2015 was carried
out by Sachin Kumar Chhetri and Prabin Kayastha.. Digital land cover map of Katmandu,
population density data and location of fire station were collected. They used AHP method for
scoring the weight of the criteria. Expert’s opinion survey was conducted for the AHP model.
Then the linear weighted combination was used for different causative factor maps to produce
fire potential index map as given in the following equation.
FPI = Weight map of (distance from fuel stations + land use + population density)
FPI value varies between 0.05-1.03. The higher value represents a higher potential zone and
the lower value represent lower fire potential zone. It has been found that 58.04% area is low
potential zone. About 32.92 % area is moderate and Rests belongs to the high-risk fire potential
zone.
Case Study 3:
M.M Yagoub and Ahmed conducted a study in Sharjah city (UAE) in 2014. Their objective
was to find any distinct pattern of fire incidents and used GIS analytical tool for siting new fire
station location. Here different data layers were digitized and prepared. Transport layer from
IKONOS, fire station, police station, hospital location were digitized. Fire incident location
was collected from different sources like newspaper, report, blogs, and journals of period 2002-
2012 were geocoded and using GIS analytical tools spatial pattern of fire incident were
determined. After that, they used the AHP model for a suitable location for the new fire station.
Criteria they have selected includes the distance from roads, hospital with emergency rooms,
police station and quick intervention, existing fire station and household density and incident
density. After selecting the criteria, the weights of the criteria were given by using the AHP
model. Finally, weighted overlay analysis was performed to find out the suitable location of
the newly proposed fire station. They also performed network analysis and show that the
Sharjah was not well served by existing fire stations which actually covered 36 % area within
6 minutes. They proposed 6 new stations fire station which will cover 75% area of Sharjah city
within 6 minutes

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Chapter 3
STUDY AREA PROFILE

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Chapter 3: Study Area Profile
3.1 Study Area
Khulna is the third largest city of Bangladesh and it is situated between 22°12′ and 23°59′ north
latitudes and between 89°14′ and 89°45′ east longitudes. (BBS, 2013) It covers a total area of
59.57 km² and It is 12 ft. above mean sea level. In the northern part of the district, Khulna City
is mainly a business expansion near the Rupsha and Bhairab Rivers. It is bounded by the Jessore
and Narail districts on the north, by the Bagerhat district on the east, Bengal Bay on the south,
and Satkhira District on the west. (Kashem et el., 2017). Around 46 percent of the area being
built is occupied by residential housing of Khulna, according to the land use survey undertaken
for Khulna's Master plan (2010). Approximately 15% of the land is for industrial use, while a
little proportion (approximately 5%) of land is for commercial use (Md.Esraz-ul-Zannat &
Islam, 2015).For this study we have selected our study area as Khulna city corporation. It is
45.4km2
and consists of 31 wards.
3.2 Land Use Profile of the Study Area
Majority of the land in Khulna city is used for residential (34.04%) and agriculture (27.58%)
purposes. Transport, communication and health services cover 15.25%, 4.23%, and 0.22%
respectively. In the Khulna city commercial areas are found beside the roads In the Khulna city
commercial areas are found beside the road, as a result, there is a lack of parking space for
vehicles parking. Because of inadequate space, people park their vehicle in the street which
results in congestion and increases delay time which results in more travel time. The following
table represents the land use profile of Khulna City Corporation.
Table 3.1: Existing land use classification of KCC
Categories Area in Acres Percentage (%)
Residential 7121.39 34.04
Agriculture 5769.17 27.58
Water body 3189.20 15.25
Industrial 1090.96 5.22
Transportation and
Communication
885.26 4.23
Education and Research 621.54 2.97
Categories Area in Acres Percentage (%)

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Administrative 411.44 1.97
Commercial 365.21 1.75
Mixed Use 252.95 1.21
Vacant Land 249.98 1.20
Community Facilities 84.37 0.40
Open Space 74.31 0.36
Recreational Area 65.27 0.31
Health Care Service 45.79 0.22
Graveyard 7.88 0.04
Miscellaneous 3.06 0.01
(Source: KCC, 2012)
3.3 Khulna Fire Stations
In the boundary of Khulna city, there are four fire stations. Their name and location are given
in the following Table 3.2 Fire station location is represented in Figure 3.1
Table 3.2: Khulna Fire stations names and locations
Source: KCC & Google Earth,2019
Name X- Coordinate Y-Coordinate
Daulatpur fire station 22°52'20.90"N 89°31'8.93"E
Khalispur fire station 22°51'28.26"N 89°32'50.47"E
Boyra fire station 22°49'52.04"N 89°32'44.76"E
Tootpara fire station 22°48'19.03"N 89°34'14.42"E

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Figure 3.1: Fire station location Source: Prepared by Author,2019

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Chapter 4
METHODOLOGY

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Chapter 4: Methodology
4.1 Desk Review
A desk review was done by gathering information from Online ArcGIS help website and online
newspaper, source, and journal which help to understand the issues regarding this study.
4.2 Study Area Selection
Khulna is the third largest city in Bangladesh. Geographically it locates in southern-western
part of Bangladesh between 1°41' and 23°00' north latitudes and in between 89°14' and 89°45'
east longitudes(BBS,2013).Our study area is khulna city corporation.It has 31 wards. It covers
a total area of 45.4 km2 while the district itself is about 4394.46 km2
.In the process of the
urbanization, Khulna city has increased its’ population, structures, transport services, industries
etc. As the population is rapidly growing, the number of the vehicle is also expanding. After
the construction of the Padma Bridge traffic volume will evidently increase. Consequently, it
will generate more difficulties for the fire vehicle to reach the fire incident in time if proper
management and route choice are not taken.
4.3 Data Collection
This study was mainly based on both primary and secondary data. Secondary data was obtained
from different relevant sources and they are given below. Primary data was collected by
surveying Experts. Sources of Secondary data is given in the table 4.1
Table 4.1: Sources of Secondary data
SL Name of data Source
1 Road network data KCC (2012) and Open Street Map (2018)
2. Average vehicle speed of fire vehicle Fire service and civil defense Khulna (2018)
3. Population data, population density BBS 2011
4 Fire station and police station location Google Earth,2019
5. Waterbody KDA (2012)
6. Fire incident location Fire service and civil defense Khulna,
(2016-17))

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4.4 Data Preparation
This phase includes the preparation of the base map from Khulna city corporation. Fire station
location was collected from google earth. The road network shapefile was obtained from
Khulna city corporation.
Attributes had been added to the road network data. Travel time for each road segment
was calculated and added as an attribute. For calculating the travel time, the average speed of
the vehicle had been used. Using the average vehicle for different road category the travel time
had been calculated by the following formula.
V=s/t
Different road category has different speed. The average speed of various road
classification was collected from the primary survey. Those data were collected from fire
service and civil defense Khulna and given in the following table.
Table 4.2: Speed according to the classification of road
Road class Average speed (Km/h)
Primary 45
Secondary 35
Tertiary 30
Access 20
4.4.1 Creation of Geodatabase
Geo-database is the native data structure and is a fundamental data format which can be used
for both editing and management of the data (ESRI, 2019). A Geodatabase can be personal,
file, or enterprise. A personal Geo-database is a database which can be used for storage,
consultation, and management of both spatial and non-spatial data. (Ahmed, Ibrahim, & Hefny,
2017) It will contain the data of fire services location, road network. Using ArcGIS, a personal
Geo-database was created for analysis.
4.4.2 Building Network Topology
To identify the errors in the data and correcting them network topology was built. It was done
by applying some topology rules. One thing that needs to be assured that there should have no
dangles in the road network and the roads do not intersect or overlap with themselves. (Ahmed,
Ibrahim, & Hefny, 2017)

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4.4.3 Building Network Dataset
While the errors have been corrected, the network data is prepared for network analysis. The
network data set is suitable for modeling the transport network. It consists of a set of edges
representing links and a set of links connecting edges and facilitating navigation from one edge
to another. In ArcGIS for Desktop, the Network Analyst extension was used to create the
network dataset. It is a strong extension which provides network-based spatial analysis, along
with route analysis, travel direction, closest facilities analysis and service area analysis
(Dabhade et al.,2015).It permits users to modelle realistic network factors dynamically at
different times of day, for instance restrictions on turning, speed limits and traffic conditions.
4.5 Incident Pattern Distribution
Spatial pattern means the distribution pattern of fire incident is Uniform, random or aggregated.
Firstly, the fire incident location was collected from the fire stations of Khulna fire service.
With the help of google earth and ArcGIS, the location of the incidents was geocoded. Under
the spatial statistics tool, the average nearest neighborhood in ArcGIS 10.3 was used to
generate the spatial pattern of the incident. To determine the distribution pattern of fire incident
Nearest Neighborhood Method has been applied.
4.5.1 Nearest Neighborhood Method
To investigate the pattern of fire incident here ‘Nearest Neighbor Index Analysis’ (O’Sullivan
and Unwin, 2003; Suwan, 1998) which is a method of exploring patterns graphically was used
here.
The equation for the nearest neighborhood is given below:
R = Dob / Dex……………………………………….. (Equation 1)
Where,
R=Nearest Neighbor Index (NNI)
Dob= Actual average nearest neighbor distance,
Expected average neighborhood distance Dex = 0.5*(n / A)1/2 [ n =The number of events in
A, A = subset of study area]
The values of index R ranges between 0 and 2.15. The pattern represents Absolute
Aggregated Distribution While all the points in a pattern fall at the same location, in that case,
R = 0. When R is closer to 0 it is more likely aggregate or clustered pattern. When it is between

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.81 to 1.31 it represents a random distribution pattern. Ranges between 1.31-2.15 represent the
uniform pattern. But when the value of R exceeds 2.15 it is scattered pattern
Table 4.3: Value of R and its Pattern
Values of R Types of Pattern
0.00 to 0.80 Aggregated Distribution Pattern
0.81 to 1.30 Random Distribution Pattern
1.31 to 2.15 Uniform Distribution Pattern
Figure 4.1: Types of pattern
4.6 Vulnerability Mapping
Vulnerability mapping of fire vehicle accessibility is done in this section. First of all, the criteria
have been selected for this vulnerability mapping. Then Adopting Analytical Hierarchy
procedure (AHP) method for the preparation of vulnerability mapping.
4.6.1 Analytical Hierarchy procedure
AHP is mainly used for Multi-criteria evaluation techniques. It was developed by Saaty(1977).
AHP can be used for incorporating, economic, socio-political issues. It is a systemic analysis
assessment process for quantitatively treating a complex and multi-index system. In the
construction of a comparative matrix, each factor is rated against the other by allocating a
relative dominant value from 1 to 9 (Pourghasemi, 2012). Pairwise ranking and scaling (1-9)
had been done by an expert opinion survey. The intensity of relative importance scale
developed by Satty given in table 4.4.
Table 4.4. The intensity of relative importance scale developed by Satty.
Intensity of
Importance
Definition

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The consistency index (CR) in AHP is used to show the possibility that matrix judgments were
arbitrarily generated (Saaty, 1977).
CR = CI / RI
Where RI= Average consistency index and CI =consistency index. RI can be expressed by the
following formula
RI = (λmax –n) / (n–1)
Here λmax=The largest eigenvalue of the matrix and n =The order of the matrix
The vulnerability map in terms of accessibility map was prepared by using the AHP OS
calculator and ArcGIS 10.3. AHP OS is online based software for calculating the eigenvalue
of selected criteria and which also gives the CR value. If CR<0.1 then the weight of the factors
will be accepted and if CR>0 then the factors are not consistent.
Vulnerability map of Khulna city in terms of accessibility is prepared by using the
weights derived from AHP. The relative weights are assigned directly to each map layer
attribute. The weights are based on the opinion survey of the experts. Here the weight of sub-
criteria and sub-criteria used as the same weight of sub criteria derived from AHP. Finally,
Vulnerability map of Khulna city in terms of accessibility was generated.
Criteria for determining Vulnerable area in terms of accessibility:
1. Distance from roads (<12 feet width)
2. Distance from water bodies
3. Distance to fire stations
1 Equal importance
3 Moderate prevalence of one over another
5 Strong or essential prevalence
7 Very strong or demonstrated prevalence
9 Extremely high prevalence
2,4,6,8 Intermediate values
Reciprocals For inverse comparison

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4. Fire incident density
1.Distance from Roads
Distance from the road for each cell of a raster is calculated in GIS environment via the
Euclidean distant tool in ArcGIS 10.3 using the shapefile of the road network which is
collected from Khulna city corporation. Roads are selected which has an equal or greater
width than 12 feet. Distance map was classified according to the objectives of the study.
2.Distance from Fire Stations
Distance from the fire station for each cell of a raster is calculated in GIS environment using
the shapefile of the fire station location which is collected from Google earth. Here Euclidean
distant tool in ArcGIS 10.3 has been used for distance map. Distance map was classified
according to the objectives of the study.
3.Distance from water body
Distance from waterbody for each cell of a raster is calculated in GIS environment using the
Euclidean distant tool in ArcGIS 10.3. The shapefile of the water body has been collected
from Khulna city corporation. Distance map was classified according to the objectives of the
study.
4.Fire Incident Density
Kernel density function under spatial analyst tools in ArcGIS 10.3 has been used to determine
the densely fire occurring area of Khulna area. Fire incidents of 2016-2017 were used as
input points. Default search radius has been used and the grid cell size is 41.48 X 41.48 m.
Finally, the incident density map was generated and classified according to the objectives of
the study.
Steps of AHP
To determine the CR value from a pairwise comparison matrix using online AHP OS webpage.
CR calculation of “Distance from road” criteria is given below.
Step 1: Select the number of sub-criteria for the criteria in AHP online webpage.

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Figure 4.2: Selection of the number of sub-criteria
Step 2: Write the name of the criteria and sub-criteria. As an example, “Distance from the
road” is the criteria and subcriteria 1)0-50 meter 2)50-100 meter 3)>100 meter
Figure 4.3: Writing the name of the criteria and sub-criteria.
Step 3: The third step is the AHP calculation process. Firstly select the importance level using
the AHP scale. The level of importance was collected from the Experts. Later consistency was
checked by “Check consistency” button.

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Figure 4.4: Assigning the level of importance
Step 4: Finally, the priorities of each sub-criteria are generated in percentage.
Figure 4.5: Priorities of sub-criteria
After generating the eigenvalues from AHP calculator the eigenvalues of sub-criteria were
multiplied with the eigenvalues of criteria. Later weighted sum tool in ArcGIS 10.3 finally
the vulnerability map had been prepared.
4.7 Existing Response Coverage
Response coverage can be defined that which streets can be reached within the standard time
from the service stations. service area is an imaginary polygon which exhibits all accessible
areas with selected impedance. For instance, the 6 minutes service area for the station displays
which streets can be reached from the station within 6 minutes.
Service area also shows how accessibility fluctuates with impedance to assess
accessibility. Here the fire stations selected as facilities and time was selected as impedance
Here service area layer under Network analyst extension was used to determine the
existing coverage of fire station service. Impedance settings for this analysis are 4,6,8 minutes

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response time respectively. The roads which are above 12 feet are considered for evaluating
the service area coverage because the roads which are below 12 feet fire vehicle cannot enter.
4.8 Site Suitibility Analysis for Fire Station
Site suitability analysis was performed here for locating future fire stations to improve the
response coverage. Criteria were selected for locating future fire station were taken from
different papers, journals etc. The suitable location map was prepared by using the AHP OS
calculator and ArcGIS 10.3. AHP OS is online based software for calculating the eigenvalue
of selected criteria. The weights of criteria are mainly based on expert opinion survey. Weights
were derived from in AHP. Finally, using the weighted sum tool in ArcGIS 10.3 the suitable
location map for future fire stations were created.Criteria which were selected for locating
future station location is given I table 4.5.
Table 4.5: Criteria for locating future fire station
No. Factor Criteria Source
1 Roads • Within 500 meters
from arterial road
(Begnell,2002)
2 Police Stations •Within 3 kilometers
Suggested by local experts of
BFSCD Khulna
3
Existing Fire
Stations
• Away from
fire station & should be
within 1-9 Km
(Liu, 2006)
4
Households
Density
(Population)
•High population is
recommended
(Al Gharib,2011)
5 Incidents
•Near areas with high fire
occurrences
(Yagoub & Jalil, 2014)

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4.9 Origin-Destination Cost Matrix
From the Vulnerability map, the Highly vulnerable area was identified. Later those areas were
converted to polygons. Then using the polygon to point tools in ArcGIS 10.3 polygons were
converted to points.
For the origin-destination cost matrix, those points are taken as destinations and origins
were selected as existing fire stations location. Finally, Origin-destination cost matrix was
generated using the origin-destination cost layer in network analyst extensions.
4.10 Optimal Path
Optimal path or route is between two locations which is actually based on travel time. The
shortest path is not always the optimal path because of its condition.
Closet facilities analysis can find the closest facilities that can be reached in a specific
period from an incident location based on travel time and traffic information available. It is
very necessary for an emergency situation to know the closest facilities that can be reached
from the incident location. It reduces time and thus saves peoples life and resources
To generate the optimal path from the closest facility to incident spot, closest facility
layer under Network Analyst extension in ArcGIS 10.3 was used. Here open street road
network has been used for this analysis. For impedance settings, Fire stations as facilities and
path should be from facility to incident and optimal path is based on travel time along with
directions. Network dataset was prepared using the Open street map shapefile. Preparation of
network dataset is mentioned in section 4.3.1

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Chapter 5
ANALYSIS

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Chapter 5: Analysis
5.1 Existing Scenario of Roads
Khulna City Corporation consists of 634.8 kilometers of roads (HCL-SPL Physical Survey,
2010). Among them, 444.7-kilometers roads are pucca, which consists of 68% of total roads.
About 146.4-kilometers roads are semi-pucca. 57.7-kilometers roads are regarded as katcha.
The fire vehicles of BFSCD is close around 12-meters-long and 2.5 meters in width (Islam, et
al.,2017). Fire apparatus access roads in Bangladesh should be a minimum of 4.5 meters in
width (BNBC). So, a minimum of 12 feet (Suggested by BFSCD) road width is required for
the fire vehicle to access easily any roads. In Khulna, about 69% of roads are greater than or
equal to 12 feet. Rest of the roads are below than 12 feet and are considered as inaccessible
roads for fire vehicle.
Figure 5.1: Fire vehicle road accessibility percentage Source: Prepared by author
5.2 Incident Pattern Distribution
Incidents locations are geocoded with the help of ArcGIS 10.3 and represented as a map in the
(Figure 5.2). From the map, it is found that most of the incidents from ward no 16,17,19,21.
Spatial statistical analysis has been done to know the spatial pattern of the incident. The result
of Average nearest neighborhood analysis provides values of Nearest Neighborhood Ratio (R),
z-scores and p-value. The distribution of fire incidents in the Khulna city for 2016-2017 was
spatially clustered. The R-value was found between 0 to 0.88. Values of R, z-score and the p-
value are illustrated in Figure 4.3 (R = 0.73; z-scores = - 5.52; p < 0.00) (Figure 5.3). The
acceptance and rejection of the null hypothesis depend on z-score. In this study, the null
hypothesis is that there is no spatial pattern among the fire incident location within Khulna city.
With small z-scores, there is a small probability which is less than 1% likelihood that this
69%
31%
Accessible
Inccessible

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clustered pattern could be a result of random chance, so, the null hypothesis is rejected.Fire
incidents of khulna city is not random incidents. It has found that most of the incidents are from
residential area including mujgunni residential area,sonadanaga residential
Figure 5.2: Incident location Source: Prepared by Author,2019

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Figure 5.3: Average Nearest Neighbourhood Analysis Report
5.3 Vulnerability Mapping
After generating the criteria maps and classification of criteria into sub-criteria a pairwise
comparison conducted for sub-criteria also and finally one pairwise comparison also
constructed among the main factors. In all comparison, CR value is found less than 0.1 Which
means that the pairwise comparison matrix is consistent. Eigenvalues for all sub-criteria and
criteria are calculated and are given in the appendix A &appendix Criteria maps for
vulnerability mapping is provided in Appendix-E
Distance from Roads
Maximum distance from the road is found 2627.8 meters .Accessible road density is found
lower in the surrounding area of ward no 4,9,22 and 31. Those wards are more vulnerable
because of narrow and inaccessible roads. The area near roads is less vulnerable because it is
easier for firefighters to rescue. That's why the distance from the road has been considered for
preparing the vulnerable map.. 58.66% of the total area is considered as the low vulnerable
area. The percentage of highly vulnerable area is 28.89%.

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Distance from Waterbody
Presence of water body is a very useful source for extinguishing the fire. The area nearer to
waterbody is less vulnerable. Maximum distance from waterbody is found 988.305 meters.Up
to 100 meters from the waterbody is considered as low vulnerable area, 100-200 meters is
regarded as moderate and above 200 meters is recognized as a highly vulnerable area. About
14.96% area is in the high vulnerable area for this factor. Percentage of the high vulnerable
area is less because the number of water bodies is sufficient.
Distance from Fire Station
Distance from the fire station is considered as another important factor in vulnerability analysis.
The area which is Proximity to fire station is less vulnerable. The closest area near the fire
station can be early responded. The maximum distance is found here 4456.18 meters. Up to
1400 meters from the fire station is regarded as a low vulnerable area. (1400-2000) meters is
moderate vulnerable and above 2000 meter is Highly vulnerable and it is 38.77 % of the total
area. Ward no (7 -12) and 2 is the highly vulnerable area. Ward no (7 -12) and 2 is the highly
vulnerable area. About 24.8% area is moderate for this factor.
Incident Density
Kernel density tool has been used to prepare a map with a raster cell size of 41.48 m X 41.48
m was created in this research. On the basis of this density value of fire incidents, the areas
with fire incidents were classified into three categories through the classification process of
Jenks classification, which can be called:
1. Low Vulnerable
2. Medium Vulnerable
3. High Vulnerable
The areas of having the density greater than 5 incidents are classified as “High Vulnerable
area” and the areas with a density of 3 to 5 are classified as "Moderate Vulnerable Area”. Ward
no 9,14,16,17, (19-26) have higher incident density. Sonadanga residential area, Mujgunni
residential.goalkhali area have higher fire accidents than other locations. Figure (5.3.4)shows
the Incident Density map(KDE) of fire incidents of 2016-2017(Appendix-D)

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After generating the criteria maps and classification of criteria into sub-criteria a pairwise
comparison conducted for sub-criteria also and finally one pairwise comparison also
constructed among the main factors. In all comparison, CR value is found less than 0.1 Which
means that the pairwise comparison matrix is consistent. Eigenvalues for all sub-criteria and
criteria are calculated and are given in the appendix A &appendix D.
Finally, the vulnerability map using AHP has been prepared. About 30.70% area is
highly vulnerable. Low vulnerable area is 37%. Table (5.1) represents the area and percentage
according to different vulnerability level. (Figure 5.4) represents the vulnerability map in terms
of accessibility. Most of the area of Ward no 23,22,29,30,31 area highly vulnerable. Khulna
shipyard area, Notun Bazar, Rupsha area, south-central road etc are situated in the vulnerable
zone.). Iimportant structures including 8 schools,5 colleges, bazar, clinic, church etc are
situated in the high vulnerable zone.
Table 5.1: Area percentage of the vulnerability map
Category Area(acres) Percentage
Low vulnerable 4222 37.84%
Moderate vulnerable 3498 31.35%
High vulnerable 3425 30.70%

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Figure 5.4: Vulnerability map using AHP Source: Prepared by Author,2019

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5.4 Existing Service Area
GIS-based network analysis has been performed to determine the service area of existing fire
stations. Service areas of Daulatpur,khalishpur, Boyra & Tootpara fire stations are generated
to identify the existing coverage of fire stations. To identify the service area of fire stations,
travel time zones are selected 4,6, and 8 minutes’ drive time.
The area which can be covered by the existing fire stations within 4,6- and 8-minutes
response time is represented in the map (Figure:5.5). The green area in the map shows that that
area can be reached within 4 minutes. It means that those green area can be covered or accessed
in 4 minutes if any fire incident occurred in the green zone. Up to yellow area can be accessed
by fire vehicle in 6 minutes response time and the pink area are within 8 minutes. The white
area inside the boundary recognized as the unserved area. From the map, we can see that the
area which is so close to fire station cannot be served because the roads in those areas are below
12 feet and those areas cannot be accessed by the fire vehicles. As a result, those area remains
unserved though it is proximity to fire stations.
The existing response coverage by the fire station of Khulna city is quite disappointed.
Maximum portion of land remains as unserved. The speed of fire vehicle ranges between 20-
45km/h which is very low compared to other developed countries along with the number of
fire stations to serve the Khulna city is inadequate.

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Figure 5.5: Service area of fire stations Source: Prepared by Author,2019
.

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5.4.1 Percentage of the Served Area:
Fire service needs to respond as early as possible. Reduction in response time can save lives
and minimize the portion of the loss. Response time can be minimized if there is a diminution
in travel time. The following chart shows the Percentage of the unserved area is in 4,6 and 8
minutes. Only 25.23 % area covered by the fire stations of Khulna city in 4 minutes. Ward 1,2,
and 31 are not properly served in 8 minutes response.
Figure 5.6: Percentage of area coverage Source: Percentage calculated by Author,2019
5.4.2 Land Use Wise of Area Coverage :
The following figure shows that land uses wise area coverage by the fire stations in 4, 6 and 8
minutes.
Table 5.2: Land Use wise of area coverage
Source: Land Use wise area coverage calculated by Author,2019
Land Use
In 4
minutes(%)
In 6
minutes(%)
In 8
minutes(%)
Commercial 66.91 86.72 89.65
Community Service 24.35 73.13 76.21
Education and Research 45.25 66.03 79.69
Government Services 44.63 77.55 68.38
Manufacturing and Processing Activity 4.62 16.16 41.57
Miscellaneous 37.03 76.55 85.11
Mixed Use 31.93 90.01 88.38
Non-Government Services 9.39 64.70 50.20
Recreation Facilities 27.41 83.56 93.46
Residential 32.14 65.27 77.69
Restricted Area 39.49 59.55 66.52
Service Activity 37.87 77.43 88.15
Transport and Communication 59.89 92.30 98.72
25.23
47.17
64.85
0
20
40
60
80
4 minutes 6 minutes 8 minutes
PERCENTAGE OF SERVED AREA

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In most of the cases of fire incidents, it is from the residential area. In the residential area,
there is more risk of life rather than other locations because children and women remain most
of their time in their residents. From the table, it is showed that the existing fire stations can
cover 32.14% area of the total residential area in 4 minutes which is not appreciable. Poor road
condition and congestion are the two of the main reasons lagging behind it.
5.5 Suitable Site for Future Fire Stations
Euclidean distance maps and density have been prepared for site suitability analysis for location
future fire stations is provided in Appendix -F. From AHP comparison matrix the CR value
has been found less than 0.1 Which means that the pairwise comparison matrix is consistent.
After consistency check, Eigenvalues for all criteria calculated and are given in the Appendix
C &Appendix D. Figure (5.7) represents the site suitability map for future location of fire
stations. The dark green area is the best location for locating future fire stations. The red area
is a poor choice for locating a fire station. From this suitability analysis it is found that the most
suitable area is near sher-e bangla road, Uttar para road, mujgunni area, B.I.D.C road. Old
Jessore road, MA Bari sharok

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Figure 5.7: Site suitability map Source: Prepared by Author,2019

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5.6 Origin-Destination Cost Matrix
Origin-cost destination matrix was obtained using the origin-cost destination layer under
network analyst extension in ArcGIS 10.3. Among 143 destinations, 96 destinations can be
reached by the existing fire stations in 8 minutes by the four fire stations. The figure 5.8 shows
that which destination can be covered within 8 minutes.
Figure 5.8: Origin destination map Source: Prepared by Author,2019

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Figure 5.9: Origin-Destination cost matrix
Above Figure 5.9 represents the origin-destination cost matrix. It represents the travel
time required to reach the destination from the existing fire stations within the 8 minutes. To
cover all the destination in 8 minutes more fire stations are required. To cover the
destinations with the existing fire stations maximum time required from the closest fire
stations is 17.4014 minutes.

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5.7 Optimal Path
Selection of the path to reach the incident is very important. In our country, the path is selected
based on the experience of the driver. Gis based analysis can help in this regard to find the best
route in providing emergency services. In this study, a GIS-based analysis is done to find the
optimal route. Here the optimal path is least cost path and cost attribute is selected as time. The
following figure illustrates the optimal path from the closest fire station to the incident location.
Here incident location is khalispur retrolling agency and the closest fire station is selected as
Khalispure fire station. Figure (5.10) represents the optimal path which is based on the travel
time. It requires 5 minutes to reach the incident location and 1.7 miles away from the fire
station. It selects the port colony road towards jetty ghat road and BIDC road to reach the
incident spot. Direction, Total travel time, distance have been created while the path is
generated (Figure 5.11).
Figure 5.10: Optimal path based on travel time Source: Prepared by Author,2019

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Figure 5.11: Direction of Optimal path based on travel time
Again, for the same incident location, the optimal path is selected based on the length
of the road instead of travel time. This time the optimal path is the shortest route in respect of
geographical length. The figure (5.12) shows the shortest route in respect of the length of the
road. The route is via port colony road. The route is 1.4 miles long which is less than the optimal
route which is based on time. But this route will cost more travel time to reach the incident
location. It requires 7 minutes to reach the incident spot which is 2 minutes more than the
optimal route. When vehicles move through a narrower road, they have lesser speed. This may
cause higher travel time. It can be said that the geographical shortest route is not the suitable
path. In rescuing or providing emergency services selection of an optimal path is very essential.
Even one minute earlier arrival can save lives and lessen the loss of property. Direction, Total
travel time, the distance for this path is given in the figure (5.13)

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Figure 5.12: Optimal path based on length Source: Prepared by Author,2019
Figure 5.13: Direction of Optimal path based on length

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Chapter 6
FINDINGS & CONCLUSION

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Chapter 6 :Findings & Conclusion
In this study firstly the incident pattern of previous fire incidents of the year between 2016-
2017 was geocoded and applying the ANN method in ArcGIS found that the incident pattern
of fire incidents is clustered. Then adaptation of AHP model and ArcGIS has been used to
identify the vulnerability map. Criteria for AHP analysis were selected from the desk review
of the different journal, paper etc. Expert opinion survey was done for AHP analysis.
Secondly the service area coverage of the existing fire stations done by performing network
analysis. From the study, it has been found that response time in recusing fire incident is higher
than in developed and developing countries. This study helps to identify the area which can be
covered or not be covered in different response time. It also determines the area where the fire
vehicle cannot access. A site suitability analysis also performed to identify the suitable site for
future fire stations. Origin-destination cost matrix was obtained from Origin-destination cost
matrix layer under network analyst in ArcGIS
Finally, A geodatabase of the road network was created for routing of fire vehicle direction.
It will show the minimum cost path(travel time) from the closest facility to the incident spot
along with direction map. This geodatabase can be used further in making a routing application.
After the construction of Padma Bridge and the introduction of CNG vehicle in Khulna, the
traffic scenario will change dramatically which results in increasing response time. From the
study, it can be said the existing condition of the road is not good. There is still some area
where fire vehicle cannot enter. This road needs to be boarded. The number of the fire station
is not enough to respond in standard response time. The fire department should use GIS
technology to identify the optimal route from the closest fire station to the fire incident spot.

47 | P a g e
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Appendix A: (Table: pairwise comparison of sub-criteria (vulnerability mapping))
2.Distance from waterbody
Criteria 0-100 100-200 >200
0-100 1 3 8
100-200 .33 1 5
>200 .12 .20 1
Eigen values 0.661189 0.271785 0.067025
Consistency ratio 4.6%
Principal Eigenvalue 3.044
3.Distance from the fire station
Criteria 0-1400 1400-2000 >2000
0-1400 1 3 7
1400-2000 .33 1 4
>2000 .14 .25 1
Eigen values 0.658626 0.262757 0.078617
1.Distance from roads
Criteria 0-50 50-100 >100
0-50 1 3 9
50-100 .33 1 6
>100 .11 .17 1
Eigen values 0.663043 0.278484 0.058473

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Appendix B:(Table: pairwise comparison of Criteria)
4.Incident Density
Criteria 0-3 3-5 >5
0-3 1 3 7
3-5 .33 1 5
>5 .14 .20 1
Eigen values 0.649097 0.278978 0.071925
Criteria Accessibility
by roads
Distance
from the
fire station
Distance
from
waterbody
Fire history
Accessibility by roads 1 3 4 5
Distance from fire station 0.33 1 4 3
Distance from waterbody .25 .25 1 2
Fire history .20 .33 .50 1
Eigen values 0.530376 0.275299 0.114036 0.080288

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. Appendix C
Pairwise comparison matrix for site suitability
Criteria Distance
from
roads
Distance
from fire
station
Distance
from police
station
Population
density
Incident
density
Distance from
roads
1 2 8 7 6
Distance from
fire station
0.5 1 7 6 3
Distance from
police station
0.12 0.14 1 .50 .20
Population
density
.14 .17 2 1 .33
Incident
density
.17 .33 5 3 1
Eigen values 0.487043 0.29214 0.037283 0.05617
0.127364
Consistency
ratio
4.2%
Principal
Eigenvalue
5.188

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Appendix-D
Appendix-E (Criteria maps for Vulnerability map)
Figure 1: Distance from Road Source: Prepared by Author,2019
Category Priority Rank
Distance from roads 48.7% 1
Distance from fire station 29.2% 2
Distance from police
station
3.7% 5
Population density 5.6% 4
Incident density 12.7% 3

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Figure 2: Distance from Waterbody Source: Prepared by Author,2019

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Figure 3: Distance from Fire station Source: Prepared by Author,2019

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Figure 4: Incident Density Source: Prepared by Author,2019

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Appendix-E (Criteria maps for Site Suitability map)
Figure 5: Distance from Road Source: Prepared by Author,2019

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Figure 6: Distance from Firere Station Source:Prepared by Author,2019

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Figure 7: Population Density Source:Prepared by Author,2019

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Figure 8: Distance from Police Stations Source:Prepared by Author,2019

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Figure 9: Incident Density Source:Prepared by Author,2019

Assessing the Accessibility of Fire Vehicles in Khulna City

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