Derivation of Critical Infrastructure Accessibility Index Using

GIS-MCDA and Network Analysis: Case Study of Sarajevo

Ivan Marić

, Aida Avdić

and Boris Avdić

University of Zadar, Department of Geography, Center for Geospatial Technologies, Zadar, Croatia

University of Sarajevo, Faculty of Science, Department of Geography, Sarajevo, Bosnia and Herzegovina

Keywords: Critical Infrastructure, GIS, City OD Sarajevo, Accessibility Analysis.

Abstract: This study explores the accessibility of critical infrastructures (CRITIS) in urban planning, focusing on the City

of Sarajevo. CRITIS, essential for societal functioning, encompasses diverse services vital to social,

economic, political, health, educational, and administrative systems. The authors leverage geographic

information system (GIS) tools to construct an accessibility model for Sarajevo, analysing the spatial

availability of critical functions. Six groups of CRITIS indicators, composed of 29 CRITIS elements, were

used in the derivation of critical infrastructure accessibility index. The methodological framework was based

on implementation of network GIS analysis, interpolation method (IDW) and GIS multi-criteria analysis,

which could be applicable to similar research studies. Local communities concentrated in the strict urban core

(Ferhadija, Baščaršija) have the best accessibility of CRITIS, while peripheral local communities with a large

area, such as Mošćanica and Reljevo, have the lowest. Results suggest a zonal categorization of the urban area,

providing valuable insights for spatial planning and future urban development management. The study reveals

that the highest value of CRITIS accessibility doesn't necessarily align with the most densely populated areas

at local community level.

1 INTRODUCTION AND

BACKGROUND

Though lacking a singular and universally accepted

definition, critical infrastructures (CRITIS) (Luiijf et

al., 2009) can be elucidated through a fundamental

set of services that constitute the lifeblood of

seamless economic and societal functioning.

According to Murray (2012) it encompasses a diverse

array of means facilitating the operation of social,

economic, political, health, educational, and cultural

systems. Numerous studies and scholarly works delve

into the capacity of a state or society to enhance the

functionality of essential infrastructural systems,

often with the primary objective of formulating

measures to protect and fortify specific infrastructural

components crucial to national security (Croope and

McNeil, 2011). The formulation of strategies for this

purpose proved highly beneficial during crises such as

the COVID-19 pandemic

and

various

environmental

natural disasters, including floods

and earthquakes. Consequently, the past decade has

witnessed a proliferation of research on the

vulnerability and resilience of critical infrastructure,

exemplified by works from Huff et al. (2019),

Milanović et al. (2017), Svegrup et al. (2019) and Niu

et al. (2022). Although Bosnia and Herzegovina

lacks an advanced critical infrastructure protection

system, there has been a growing recognition in both

public and academic spheres of the necessity to

establish such a platform (Smajić and Bajramović,

2024). Given that urban areas remain focal points for

human settlement, critical infrastructure assumes

paramount importance within cities due to its

multifaceted nature and the substantial user base

reliant on its services. Urban planning, in this context,

places particular emphasis on investigations into the

accessibility of specific functions (Neuman, 2012,

Šiljeg et al., 2018), with accessibility being a

determinant of equal access and opportunity, where

transport infrastructure assumes a pivotal role. The

vulnerability of these systems emerges as a

significant planning challenge, as highlighted by

Tsenkova (2012), particularly in the cities of

Southeastern Europe, where susceptibility is

compounded by limited access to education and

healthcare. Such a situation result from the rapid

Mari

c, I., Avdi

c, A. and Avdi

c, B.

Derivation of Critical Infrastructure Accessibility Index Using GIS-MCDA and Network Analysis: Case Study of Sarajevo.

DOI: 10.5220/0012548100003696

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 10th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2024), pages 15-25

ISBN: 978-989-758-694-1; ISSN: 2184-500X

urban development of the formal city and strong

centralization, relegating smaller settlements to the

periphery. Sarajevo, the capital of Bosnia and

Herzegovina and the most administrative, political,

cultural and financial centre of the country, is no

exception. The city has undergone substantial spatial

transformations in urban content and significant

alterations in urban morphology, owing to its turbulent

historical and social development, as well as the

impacts of economic and induced demographic

transitions (Pobrić, 2002; Gül and Dee, 2015; Čakarić

and Idrizbegović Zgonić, 2020). The dynamic nature

of these alterations underscores the necessity to

investigate the availability of infrastructural facilities

considered vital for urban functioning. Given the

absence of a universally applicable set of criteria for

ascertaining infrastructure criticality, such criteria are

tailored to the socio-economic characteristics of the

observed area. Cikotić et al. (2018) assert that energy

plants, information technology, finance, healthcare,

food services, water, transport, and government are

among the most prevalent critical infrastructure

components, subject to national, regional, and local

spatial scales vulnerability assessments. Contemplat-

ing the essential services requisite for seamless daily

operations and drawing insights from recent pandemic

conditions, the authors of this study have incorporated

elements from the transport, administrative, health,

educational, and communal sectors in their analysis of

the spatial availability of critical infrastructure.

Leveraging Geographic Information System

(GIS) tools for the spatial delineation of essential,

critical functions, the principal objective of this study

is to construct an accessibility model of critical

infrastructure (CRITIS) for the City of Sarajevo. The

aim is to comprehend the extent to which residents

and all service users can effortlessly access goods,

services, and activities. Ford et al. (2015) posited that

accessibility to services constitutes a crucial

component in developing a sustainable transport

system, functioning as a highly important

intermediary between services and the population.

Consequently, spatial accessibility encompasses both

service availability and travel impedance, with travel

distance and suitable transportation emerging as

common indicators of accessibility (Yin, 2010; Šiljeg

et al., 2018; So, 2016).

GIS provides an expansive array of tools for

analysing availability, vulnerability, resilience, and

control, particularly in CRITIS (Wolthusen, 2005;

Milanović et al., 2018). This underscores the

applicability of geographic solutions in addressing

contemporary urban challenges. The novelty of this

study lies in its innovative utilization of the GIS

multi-criteria model to construct a comprehensive

accessibility model of critical infrastructure in a case

study of a transitional city with atypical urban

development, thereby offering valuable insights for

informed decision-making in urban planning.

2 STUDY AREA

The territorial scope of this research is limited by the

administrative boundaries of Sarajevo (141 km²),

which has a population of 275,524 people, according

to the last 2013 census (BHAS, 2016). It comprises

four urban municipalities (from east to west): Stari

Grad, Centar, Novo Sarajevo and Novi Grad. The

historical centre of Sarajevo is located in the eastern

part of the urban area, in the municipality of Stari

Grad (Old City), while newer neighbourhoods line up

to the west. The terrain morphology primarily

determines the urban development and sprawl of

Sarajevo, so the majority of the city population is

concentrated in the Miljacka River valley and on the

nearby hills. On the other hand, the surrounding

mountains, such as Trebević and Ozren, are virtually

uninhabited.

Sarajevo is a typical example of a transitional city.

It experienced most of its spatial and population

growth in the socialist period, during the second half

of the 20th century. The event of the 1984 Winter

Olympics was a particularly significant stimulation

for urban growth and infrastructure modernisation.

However, the process of further development of

critical infrastructure was interrupted by the 1992-95

war and post-war economic underdevelopment.

Hereby, this study is the first attempt at

methodologically based research on disparities of

urban development of critical infrastructure in the

capital city of Bosnia and Herzegovina.

Figure 1: Geographical location of City of Sarajevo and its

administrative division.

GISTAM 2024 - 10th International Conference on Geographical Information Systems Theory, Applications and Management

3 MATERIALS AND METHODS

The methodology is based on an integrated

application of network GIS analysis (closest facility),

interpolation method of time cost attribute and GIS

multi-criteria analyses (GIS-MCDA).

The methodological framework can be divided

into seven steps (Fig. 2): (1) determine the main GIS-

MCDA objective (2) selection of appropriate groups

and elements of CRITIS; (3) acquisition of GIS and

non GIS data; (4) application of closest facility tool

within Network analyst; (5) interpolation of travel

time cost attribute using inverse distance weighted

(IDW) method; (6) aggregation of the accessibility

raster models using weighted sum tool; and (7)

delineation of hot-spots and deprivation zones of

CRITIS using Zonal statistics tool.

Figure 2: Methodology workflow.

3.1 Selection of CRITIS

CRITIS encompasses components of the urban system

that constitute essential foundations for the operational

integrity and safety of urban environments, particularly

during periods of imminent peril (Yang et al. 2023).

These infrastructural systems assume a pivotal role in

facilitating the fulfilment of imperative social,

economic, organisational, and other functions crucial

for the routine activities of the urban populace

(Petrović et al, 2018). The absence of a uniform

system for selecting indicators for critical

infrastructure allows the authors arbitrariness to the

extent that follows the logic and nature of urban

functions and the socio-economic status of the city.

In selecting infrastructure systems as critical, the

authors primarily decided on educational and health

infrastructure due to their fundamental roles in

ensuring societies' well-being, resilience, and

functionality. Educational institutions are primary

contributors to human development in a sphere of

workforce preparation, innovation and social

development (Grigore, 2021), while health

infrastructure, including hospitals, clinics and public

health systems, provides medical services and plays a

critical role in safeguarding public health (Sänger, et

al-, 2021, Scholz et al-, 2022). In many works, the

transport network is undeniably treated as a vital part

of critical infrastructure (Theoharidou, 2012;

Borghetti and Marchionni, 2023), enabling basic

services for the movement of people, goods and

information, and in the context of the availability of

all other functions, it plays an intermediary role.

Administrative functions involve critical decision-

making processes at various levels of government.

These decisions impact the overall well-being of a

nation, its citizens, and its infrastructure, which is

reason why many authors (Żaboklicka, 2020) find it

critical. Due to their essential role in providing

services such as water supply, gas and

telecommunication, utilities are considered as

CRITIS (URL 1, URL 2).

Although it certainly belongs to the critical

domain, the connection of households to electricity,

water, sewerage and similar networks was not taken

into consideration within this research, since it is

considered that almost all the city's population has

access to this type of infrastructure. Instead, the work

is focused on the discovery of spatial disparities in the

accessibility of those functions, which are

characterised by a certain degree of physical distance,

but are also necessary for the daily life of people, as

well as the sustainability of the social system. In the

context of the accessibility of communal services,

treated facilities where fees for the aforementioned

services are regulated, and which are considered

inevitable for their users. Finally, banks, malls,

supermarkets and hypermarkets as key chains for the

supply of commercial and banking services are

classified in the group of trade/financial indicators of

CRITIS. Table 1. shows all CRITIS groups and

elements for which accessibility analysis is done.

Derivation of Critical Infrastructure Accessibility Index Using GIS-MCDA and Network Analysis: Case Study of Sarajevo

Table 1: CRITIS thematic groups and elements.

Group CRITIS Source

Educational

Primary school

URL3, Google Earth

(GE)

Secondary school URL3, GE

Kindergartens Geofabrik, GE

Administrative

Offices for social help and

employmen

URL 4, GE

Ministries URL 5

Police stations GE

Courts GE

Local communities GE

Administrative authority GE

Healthcare

Hospital 1rank URL3, GE

Hospital 2rank URL3, GE

Hospital 3rank

+ health homes

URL 3, GE

Pharmacy Geofabrik, GE

District outpatient clinics URL 3, GE

Trade /

Finance

Large stores Geofabrik

Marketplace GE

Banks Geofabrik

Traffic

Bus terminal Ministry of Transport

Minibus stations Ministry of Transport

Tram stations Ministry of Transport

Trolleybus stations Ministry of Transport

Railway stations Ministry of Transport

Main roads Geofabrik

Post office Google Earth

Communal

Communal cash register URL4, GE

Firefighters URL4, GE

Electro distribution URL4, GE

Heating plants URL4, GE

Community and building

managers

URL4, GE

3.2 Data Acquisition

GIS and "non" spatial data were acquired to create the

CRITIS accessibility index for the city of Sarajevo.

GIS data was mostly acquired from OSM sources,

Geofabrik, and official state sources (layer of local

communities, and four urban municipalities). "Non-

GIS data (addresses of schools, hospitals, banks, etc.)

were geocoded using My Maps and Google Earth and

then with KML to layer tool converted into GIS data.

After harmonisation, all data were organised into a

unique GIS database in the projection coordinate

system WGS 1984 UTM Zone 33N. To improve the

interpolation model with the extrapolation method

(Marić and Šiljeg, 2017), the data were also acquired

for neighbouring zones outside the city boundaries.

Namely, a buffer zone of 400 m was created around

that polygon, which consists of four urban

municipalities (Stari Grad, Centar, Novo Sarajevo,

and Novi Grad). Within that expanded polygon, a

raster accessibility model of the CRITIS was created.

After aggregating all models, clipping of the extended

model was performed according to the borders of the

administrative territory of the city of Sarajevo.

Network analyses were made based on the

network dataset, which was created from the road

layer downloaded from Geofabrik. Before the

derivation of the network dataset, a topological check

was made using the Planarize lines tool. Then, for

each element, the attribute of the road that needs to be

covered (length) and the speed of movement, which

in this case is 5 km/h, or the average walking speed

of a person, is calculated. From the calculated length

and movement speed, the attribute of time (min) that

needs to be spent to overcome a certain element of the

path is calculated.

3.3 Closest Facility Analysis

Based on the derived network dataset, geocoded

locations of CRITIS, and the layer of residential

buildings that represent the location of the population

in the city of Sarajevo, the Closest facility analysis

was performed using the Network Analyst extension

within ArcMap 10.8.1. The closest facility solver

measures the cost of travelling between incidents and

facilities and determines which are closest to each

other. When finding the closest facilities, you can

specify how many to find and whether the direction

of travel is towards or away from them. It displays the

best routes between incidents and facilities, reports

their travel costs, and returns driving directions.

Residential buildings representing the locations

of residents were acquired from Geofarbrik (layer: gis

osm buildings a free 1) and then converted into

points. In the analysis, "facilities'' represented a

specific element of the CRITIS infrastructure (e.g.,

primary schools), while "incidents'' was a layer of

residential buildings (n=47,288). The cost attribute

was time of travel in min. For each residential

building, a time of travel attribute was calculated, i.e.

how many minutes should be spent walking to reach

the specific CRITIS element.

GISTAM 2024 - 10th International Conference on Geographical Information Systems Theory, Applications and Management

3.4 Interpolation Method

To perform raster continuous models of CRITIS

accessibility, it was necessary to implement a specific

interpolation method (IM). The input data were

elements of residential buildings (n= 47 288). For

each of them the cost attribute of travel time was

calculated. The IDW (Inverse Distance Weighted)

interpolation method was used, which explicitly

assumes that things that are close to one another are

more alike than those that are farther away. The

measured values closest to the prediction location

have more influence on the predicted value than those

farther away. It gives greater weights to points closest

to the prediction location, and the weights decrease as

a function of distance. When implementing

interpolation methods, the same user- defined

parameters (search distance, power setting, etc.) were

set for each element of a specific CRITIS group. For

all raster models, a spatial resolution value of 10 m

was set. After generating the continuous raster

models of CRITIS accessibility, it is possible to create

isochrones, i.e. lines connecting points (places) that

can be reached from a specific place in the same

average time.

3.5 Interpolation Method

In total, 26 accessibility CRITIS models were

derived. They were clustered into six groups. In the

first step, models were aggregated within each

thematic group (education, health, administration,

etc.) using the Weighted sum tool. Each model had an

equal weight coefficient. This resulted in six thematic

accessibility CRITIS models. This was followed by a

new aggregation where each thematic CRITIS model

had a weight coefficient of 0.16667. The final

CRITIS accessibility model was converted into a

range of values from 0 to 1, where a lower value

represents better accessibility, i.e. shorter travel time

to CRITIS. This was done using the tool Fuzzy

membership and linear function.

3.6 Delineation of Accessibility Zones

Delineation of CRITIS accessibility zones was done

following two approaches: (1) boundaries of local

districts and; (2) elements of residential buildings. In

the first approach, the final CRITIS model overlapped

with the polygonal layer of the local district (n=76)

within Sarajevo. For each district using the Zonal

statistics tool, the mean values of the pixels located

within the boundaries of that district were calculated.

This made a certain generalisation of the availability

CRITIS model according to the boundaries of the

local districts. The availability zones thus follow the

boundaries of local districts. They were classified into

five classes (extremely accessible, accessible, neither

accessible nor inaccessible, inaccessible, moderately

inaccessible) using the Jenks (natural breaks)

classification method (Fig. 2). In the second

approach, the final CRITIS model overlapped with

the residential buildings layer (points). Then, using

the Extract value to point tool, the CRITIS

accessibility attribute was derived for each object

(point). Then the objects were classified into five

classes using the Jenks classification method, similar

to the first approach. Descriptive statistics then were

derived for both approaches.

4 RESULTS AND DISCUSSION

4.1 CRITIS Models

Examining the spatial dynamics of Sarajevo reveals

disparities between the urban core and the semi-urban

periphery, particularly evident when scrutinizing the

accessibility of critical infrastructure. This analysis

delves into key sectors such as educational facilities,

public transport, commercial services, administrative

hubs, healthcare, and communal infrastructure. The

examination unveils distinct patterns that underscore

the challenges faced by residents of the outskirt parts

of the city compared to those in city center. The study

results are predominantly conveyed through

cartographic representations, encompassing 29 basic

thematic maps. Additionally, these are synthesized

into six aggregated maps based on distinct indicator

groups. Spatial inequalities between the urban core

and the semi-urban periphery of Sarajevo are very

evident when it comes to the analysis of the

availability of educational infrastructure (Figure 3).

The distribution of secondary schools particularly

contributes to this, since their deficit has been

established even in densely populated areas of the

municipality of Novi Grad, while there are none of

them in the outer parts of the city. The availability of

primary schools is somewhat more even, which is

especially visible in the northwestern city periphery.

Neighborhoods in this part of Sarajevo are once again

neglected regarding availability of kindergartens. A

very similar spatial pattern is observed when

analyzing the public transport infrastructure (Figure

3). In this regard, the flat part of the city is particularly

privileged, where all the tram, trolleybus and railway

stations are located, while the hilly neighbourhoods

primarily rely on bus and minibus lines.

Derivation of Critical Infrastructure Accessibility Index Using GIS-MCDA and Network Analysis: Case Study of Sarajevo

Figure 3: Accessibility model of 1a) secondary schools; 1b) primary schools; c) kindergartens and final educational acessibiliy

model; accessibility model of 2a) bus terminal; 2b) minibus station; 2c) tram stations; 2d) trolleybus stations; 2e) railway

stations; 2f) main roads; 2g) post office and final transport accessibility model; accessibility model of 3a) large stores; 3b)

marketplaces; 3c) banks and final trade/financial acessibility model.

The stretch of most of the main roads is also

determined by the morphological characteristics of

the terrain, and is highly correlated with the density

of other urban contents. Post offices are relatively

evenly distributed in highly urbanized parts of all four

city municipalities, but there are practically none on

the city's outskirts.

Access to basic commercial and financial services

also differs significantly in the peripheral compared

to the central parts of the city (Figure 3-3). While

supermarkets are somewhat more widely dispersed

across the city, banks are primarily concentrated

along the main axis of Sarajevo's urban development,

in the east-west direction.

Market locations are relatively few, which is why

the model of their availability shows spatial

fragmentation.

The administrative infrastructure (Figure 4) is

primarily located in the central part of the city, and

secondarily in highly urbanized parts of other city

municipalities (Stari Grad, Novo Sarajevo and Novi

Grad). The semi-urban periphery is particularly

marginalized in this regard. A significant exception is

the administrative functions at the level of local

communities, which were primarily formed so that

the inhabitants of individual urban neighbourhoods

could more easily articulate their infrastructure needs.

GISTAM 2024 - 10th International Conference on Geographical Information Systems Theory, Applications and Management

Figure 4: Accessibility model of 4a) social help and employment; 4b) ministries; 4c) police stations; 4d) courts; 4e) local

communities; 4f) administrative authority; and final administrative accessibility model and 5a) hospital 1_rank; 5b) hospital

2_rank; 5c) hospital 3_rank; 5d) pharamcy; 5e) district outpatient clinics; and final healthcare accessibility model and 6a)

communal cash register; 6b) firefighters; 6c) electro distribution; 6d) heating plans; 6e) community and building managers

and final communal accessibility model.

Healthcare, as an extremely important element of

critical infrastructure, is organized on four levels –

clinical center, other hospitals, health centers and

local clinics (Figure 4). Since the facilities of the two

highest levels of this organizational structure are

located exclusively on the territory of the

municipality of Centar, even the urbanized parts of

Novi Grad in the west are characterized by an

unsatisfactory degree of availability of these services

due to physical distance. The city's population is

served by five health centers, and the large spatial

imbalance is partially mitigated by the distribution of

a larger number of local clinics. The analysis also

took into account the availability of pharmacies,

which emphasized the very unfavourable position of

the northwestern outskirts of Sarajevo. Modeling of

communal infrastructure availability confirmed

similar spatial patterns as in the case of other elements

Derivation of Critical Infrastructure Accessibility Index Using GIS-MCDA and Network Analysis: Case Study of Sarajevo

of critical infrastructure (Figure 4). The only thing

more pronounced is the slightly better infrastructure

coverage of Dobrinja, as the city's largest district,

which is located on the far southwestern outskirts of

the city of Sarajevo.

4.2 Final CRITIS Accessibility Model

Figure 5 shows the final model of the CRITIS

accessibility and the derived zones of accessibility

following the two mentioned approaches. Descriptive

statistics are provided in Table 2 and 3, where it is

stated how many residents and residential buildings

can be found in the derived zones, depending on the

used approach.

The five local districts with the best accessibility

of CRITIS infrastructure are (1) Ferhadija; (2)

Baščaršija; (3) Center Trg Oslobođenja; (4)

Mjedenica and (5) Džidžikovac Koševo I. These five

local districts have a total of 9369 inhabitants with a

total area of 1,037 km², which gives 9,035 population

per km². These are the local communities of the

central business district where the main city functions

are concentrated. It is also the main traffic and

historical center of Sarajevo.

The five local districts with the lowest

accessibility of CRITIS infrastructure are (1) Naselje

Heroja Sokolje; (2) Pionirska Dolina Nahorevo; (3)

Reljevo; (4) Dobroševići and (5) Moščanica. These

five local districts have a total of 20428 inhabitants

with a total area of 80.02 km², which gives 255

population per km². These are peripheral hillside local

communities, with a relatively low population density

and a significant distance from the urban center. Low

CRITIS accessibility (CA) represents a significant

and long-recognized problem by the local population

with a negative effect on their quality of life (URL 6,

7, 8).

Table 2: Results of CRITIS accessibility (CA) for first

approach (local districs).

Population Area (km²) Local district

Total % Total % Count %

1 84359 30.6 7.85 5.7 26 34.2

2 123032 44.7 16.70 12.0 35 46.1

3 21382 7.8 8.40 6.1 5 6.6

4 33974 12.3 35.17 25.4 6 7.9

5 12778 4.6 70.53 50.9 4 5.3

Total 275525

138.66

1 - very high, 2 - high; 3 - medium; 4 - low; 5 - very low

Table 3: Results of CRITIS accessibility for the second

approach (residential buildings).

Residential buildings

Total %

1 15008 31.76

2 17429 36.88

3 7094 15.01

4 4052 8.57

5 3675 7.78

On the basis of the derived multicriteria index, it

was established that about 30% of the urban

population of Sarajevo falls into the most favourable

category of infrastructural availability. These are

residents of the city core in the municipalities of

Centar and Stari Grad, then the highly urbanized

neighbourhoods of Novo Sarajevo, and a smaller part

of Novi Grad. On the other hand, some 17% of the

population of Sarajevo has low or very low

availability of critical infrastructure. The largest

number of inhabitants from these categories inhabit

the northwestern periphery of the city territory (part

of the municipality of Novi Grad), that is, primarily

the local communities of Dobroševići, Naselje Heroja

Sokolje and Reljevo. The situation is similar in the

hilly northeastern parts of Sarajevo (e.g. the village of

Nahorevo), but the population concentration in these

areas is still significantly lower.

The findings for the City of Sarajevo unveil

interesting patterns, revealing that the highest

concentration of service supply does not necessarily

coincide with the most densely populated areas. It is

known that the largest population concentration

pertains to the southwest part of the urban area (the

southern part of the municipalities of Novo Sarajevo

and Novi Grad). However, the accessibility of critical

infrastructure in this part of the city only partially

fulfils the needs of its residents. This issue needs to

be further explored through future research, which

would treat population density as a key variable.

Simultaneously, there is a need to differentiate

weights for different types of infrastructure. In this

study, equal weights were utilized for methodological

transparency, eliminating subjective assessments of

the significance of individual infrastructure elements.

However, it is evident that there is a need for an

objective and methodologically grounded

differentiation in this field. Additionally, parallel

research of this type is necessary in other cities to

optimize the spatial CRITIS model through different

case studies, aiming for its universal validity.

GISTAM 2024 - 10th International Conference on Geographical Information Systems Theory, Applications and Management

Figure 5: (A) CRITIS accessibility index for local district; (B) CRITIS accessibility for residential buildings.

5 CONCLUSION

The CRITIS accessibility model applied in this case

study resulted in the creation of a composite index,

whereby equal weights were assigned to

administrative, communal, healthcare, transport,

trade/financial and educational infrastructure. In this

way, a specially designed methodological approach

for examining infrastructural disparities within the

urban zone of Sarajevo was tested, which can be used

in other examples of cities of similar size, status,

historical background and/or urban patterns. The

obtained results are promising, since they clearly

indicate the zonal categorization of the studied urban

area, which can be widely used in spatial planning,

that is, in the future management of urban

development. Recommendations for further

improvement of this model primarily include research

on the correlation of CRITIS availability with

population concentration, introduction of

Derivation of Critical Infrastructure Accessibility Index Using GIS-MCDA and Network Analysis: Case Study of Sarajevo

differentiated weights, more detailed analysis of

individual elements of critical infrastructure,

potential inclusion of additional and review of

existing criteria, comparative field research, as well

as comparative analyzes with other cities. While

Bosnia and Herzegovina is still in the initial phases of

developing its critical infrastructure protection

system, this model serves as a solid foundation for

further expansion and implementation across other

cities in the country.

ACKNOWLEDGEMENTS

This research was supported by the Center for

Geospatial Technologies (University of Zadar,

Croatia).

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