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An Analysis of High Urbanization via Clustering in Central East Africa for Regional Integration

Authors

Asst. Prof. Mehmet Çağrı Kızıltaş1*, Asst.Prof. Ömer Faruk Kültür2 
1Department of Civil Engineering, Faculty of Engineering and Architecture, Istanbul Beykent University.
2Department of Civil Engineering, Faculty of Engineering, Istanbul University Cerrahpaşa.

Article Information

*Corresponding Author: Asst. Prof. Mehmet Çağrı Kızıltaş, Department of Civil Engineering, Faculty of Engineering and Architecture, Istanbul Beykent University.

Received: September 30, 2026         |        Accepted: October 05, 2026           |            Published: October 09, 2026

Citation: Mehmet Ç Kızıltaş, Ömer F Kültür., (2026). “An Analysis of Metropolization and High-Capacity Transportation of Brazil Via Clustering Methods”. International Journal of Business Research and Management 5(3); DOI: 10.61148/3065-6753/IJBRM/105.

Copyright:  © 2026. Mehmet Çağrı Kızıltaş. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

High capacity and advanced technology mobility is one of the most vital parameter of transportation on today’s case. It is a transport choice that produces mobility among cities and settlement clusters within high speed, high capacity, and high volume. This transport way has a crucial role for tourism centers and settlements too. It is an effective way of sustainable mobility engineering that enhances intercity and inter regional scale tourism systematics. It is also an important dynamic for advancement of nationalities. In this paper, a cluster-based analysis was made for Central East Africa by usage of population and related parameters via clustering mathematical connections. Recommendations were given by considering the competitive operation intervals of high capacity transportation between specified clustering cities and lastly results were given on this context.

Keywords:

Clustering analysis, urban, high speed, tourism, economy

Introduction:

1. Introduction

Transportation is at the heart of development, attracting tourism, social activity, economic growth, and cultural relations. Transportation services increase the emphasis on tourism travel at city, regional, national, and international levels. Today, tourism is one of the main pillars of economic development for countries. Multi-sectoral improvement is a challenging issue, especially for developing countries. And the mentioned countries strengthen their core sectors such as construction, healthcare, tourism, heavy industry, infrastructure, energy, military, or light industry. The driving force behind tourism is a well-developed transportation system. High-speed systerms and well planned urban clusterings are important asset, capacity, and opportunity for national based tourism.

Cental East Afirca is a very large region. They have a vaat naturel integration between them in terms of their culture and same/similar ethnolenguistic base. Swahili language is same for a very large Population on Congo, Republic of Congo, Kenya, Somalia, Tanzania, Uganda, Ethiopia, Burundi and Zambia. Also this region has the highest fertility rates and population increase rates all over the World. Besides all of these, young population is very high and the region has very big, important and high populated urban clusters like Mombasa, Kinshasa, Mogadishu, Timbuktu, Dar es Salaam, Zanzibar, Nairobi, Kampala and Entebbe.

These are also Worldwide important cities too. So, because of all of these reasons and conditions the integration and unity of the region has a strategic point of view. And also it is strongly related to infrastructural balanced development. And all of these have closer connections with energy and geography. Finally urbanization and mobilization trends measuring and analysis will be determinant for all of these conditions. These two parameters has a strong, robust, reliable and rational bound with high speed, high capacity and high comfort mobility. High-speed system network proposal developed in this way will integrate East Africa more quickly with each other and neighbouring countries too. Within the scope of this study, the provinces of Central East Africa were listed according to parameters such as population, gross domestic product, and level of development, and were subjected to cluster analysis using statistical methods in the R Studio program. In this context, priority cities were determined by considering the number of clusters and cluster lists that emerged based on the most suitable clustering method. The aforementioned priority cities were evaluated based on distance, ultimately leading to a high-speed network system proposal for region.

Fig. 1. Big Urbans of Central East Africa (Deposit Photo, 2025)

In Figure 2 region’s state map is presented (Arthipo, 2025). Figure 3 shows region’s Geographical Map (Milliyet Eğitim, 2025). Table 1 shows region’s cities’ populations and livabilities (OECD, 2020).

Fig. 2. Central East Africa State Map (Arthipo, 2025)

Fig. 3. Central East Africa Geographical Map (Milliyet Eğitim, 2025)

Table 1: Central East Africa Cities Populations And Liveavilities (Oecd, 2020)

 

City

Liveability

Population

Kinshasa

32

11900000

Bukavu

22

871000

Lubumbashi

22

1790000

Mbuji-Mayi

21

1560000

Kananga

20

1970000

Kisangani

20

936000

Uvira

19

590000

Kolwezi

19

573000

Mbandaka

19

1190000

Tshikapa

18

732000

Likasi

18

423000

Matadi

18

306000

Mbanza-Ngungu

18

100000

Bunia

18

328000

Boma

17

163000

Mwene-Ditu

17

196000

Gandajika

17

146000

Isiro

17

183000

Kikwit

17

187000

Kalemie

17

147000

Kindu

17

172000

Beni

17

232000

Butembo

16

218000

Gemena

15

139000

Bumba

15

103000

Brazzaville

25

1830000

Pointe-Noire

20

829000

Kinkala

16

16100

Kayes

15

62500

Madingou

14

27500

Gamboma

13

19700

Nairobi

60

5550000

Thika

42

279000

Machakos

36

114000

Meru

34

1830000

Mombasa

33

1200000

Kisumu

32

410000

Nakuru

32

308000

Eldoret

32

194000

Mumias

29

100000

Malindi

25

120000

Luanda

41

2490000

Benguela

40

562000

Ambriz

40

17000

Huembo

39

844000

Lobito

39

393000

Cabinda

38

739000

Luena

37

357000

N'zeto

35

47800

Kampala

47

1680000

Entebbe

28

70000

Kira Town

28

317000

Jinja

22

72900

Gulu

19

152000

Mbale

19

96200

Tororo

18

41900

Arua

16

62000

Kasese

14

115000

Dar es Salaam

56

4720000

Zanzibar

34

206000

Stone Town

31

18000

Morogoro

29

207000

Arusha

27

416000

Dodoma

27

214000

Moshi

26

145000

Tanga

25

244000

Mbeya

25

292000

Mwanza

23

386000

Mogadishu

17

2120000

Baidoa

11

950000

Hargeisa

11

760000

Borama

8

68100

Lusaka

37

2470000

Kitwe

26

504000

Ndola

26

528000

Chingola

24

147000

Kapiri Mposhi

24

241000

Mufulira

23

122000

Kasama

22

168000

Choma

22

122000

Mansa

22

129000

Bangui

9

889000

Berberati

5

76900

Bria

3

35200

2. Literature Review

In the 21st century, in addition to urbanization, digitalization and sustainability also seem to be at the forefront. What strengthens the trend of digitalization is a continuous and uninterrupted process of technological development and innovation. This has created a constant dynamic of change in our lives. Transportation and urbanization have been and will continue to be affected by this dynamic.
Sustainability trends have strengthened even further today. Western countries and developed countries have a role to play in this regard. In this context, sustainability, digitalization, and urbanization indicate that more investment should be made in high-speed train lines, metro lines, and high-capacity high-speed bus lines. These three systems could be the initial driving force for autonomous transportation systems in developing countries. As a developed country in this context, the spread of well-planned metropolization and high standard transportation in Italy is an important saving. At the center of all of this, there are well planning, detailed analysis and true approaches (Givoni, 2006).

3. Methodology

Clustering Analysis

Clustering statistical analysis have been conducted via K means method, PAM and Clara method.

  1. K Means Method

Here are results for number of clusters and cluster visulation in terms of K means method in Figure 4 and Figure 5.

Fig. 4. Number of Clusters in Terms of K Means Method

Cluster Visulation

Fig. 5. Cluster Visulation in Terms of K Means Method

  1. PAM

Here are results for number of clusters and cluster visulation in terms of PAM in Figure 6 and Figure 7.

Fig. 6. Number of Clusters in Terms of PAM

Cluster Visulation

Fig. 7. Cluster Visulation in Terms of PAM

  1. Clara Method

Here are results for number of clusters and cluster visulation in terms of Clara method in Figure 8 and Figure 9.

Fig. 8. Number of Clusters in Terms of Clara Method

Cluster Visulation

Fig. 9. Cluster Visulation in Terms of Clara Method

As a result of all methods and agglomerations, the biggest cities has been emerged into two clusters, 4 main clusters has emerged for these dataset. On Table 2, clustering list of the cities has been given.

Table 2: Cluster List Of Central East African Cities

City

Liveability

Cluster

Kinshasa

32

6

Bukavu

22

4

Lubumbashi

22

4

Mbuji-Mayi

21

4

Kananga

20

4

Kisangani

20

4

Uvira

19

1

Kolwezi

19

1

Mbandaka

19

1

Tshikapa

18

1

Likasi

18

1

Matadi

18

1

Mbanza-Ngungu

18

1

Bunia

18

1

Boma

17

1

Mwene-Ditu

17

1

Gandajika

17

1

Isiro

17

1

Kikwit

17

1

Kalemie

17

1

Kindu

17

1

Beni

17

1

Butembo

16

1

Gemena

15

1

Bumba

15

1

Brazzaville

25

4

Pointe-Noire

20

4

Kinkala

16

1

Kayes

15

1

Madingou

14

1

Gamboma

13

1

Nairobi

60

3

Thika

42

5

Machakos

36

5

Meru

34

5

Mombasa

33

5

Kisumu

32

2

Nakuru

32

2

Eldoret

32

2

Mumias

29

2

Malindi

25

2

Luanda

41

5

Benguela

40

5

Ambriz

40

5

Huembo

39

5

Lobito

39

5

Cabinda

38

5

Luena

37

5

N'zeto

35

5

Kampala

47

5

Entebbe

28

2

Kira Town

28

2

Jinja

22

2

Gulu

19

1

Mbale

19

1

Tororo

18

1

Arua

16

1

Kasese

14

1

Dar es Salaam

56

3

Zanzibar

34

5

Stone Town

31

2

Morogoro

29

2

Arusha

27

2

Dodoma

27

2

Moshi

26

2

Tanga

25

2

Mbeya

25

2

Mwanza

23

2

Mogadishu

17

4

Baidoa

11

1

Hargeisa

11

1

Borama

8

1

Lusaka

37

5

Kitwe

26

2

Ndola

26

2

Chingola

24

2

Kapiri Mposhi

24

2

Mufulira

23

2

Kasama

22

2

Choma

22

2

Mansa

22

2

Bangui

9

1

Berberati

5

1

Bria

3

1

4. Results

After statistical analysis, prior urbans were gathered on 6, 3 and 5 no clusters’ urbans.  On Table 3 selected cities are listed below.

Table 3. Selected cities via clustering analyse

City

Liveability

Cluster

Country

Kinshasa

32

6

Dem. Rep. Congo

Nairobi

60

3

Kenya

Thika

42

5

Kenya

Machakos

36

5

Kenya

Meru

34

5

Kenya

Mombasa

33

5

Kenya

Luanda

41

5

Angola

Benguela

40

5

Angola

Ambriz

40

5

Angola

Huembo

39

5

Angola

Lobito

39

5

Angola

Cabinda

38

5

Angola

Luena

37

5

Angola

N'zeto

35

5

Angola

Kampala

47

5

Uganda

Dar es Salaam

56

3

Tanzania

Zanzibar

34

5

Tanzania

Lusaka

37

5

Zambia

The cities and urban areas selected above are regions that exhibit region’s highest level of metropolitanization and have the trend of producing the most life expectancy and motion. Rely on to the important role, these urbans are going to play a significant role on region’s economic, cultural, technic, national safety and wealth and Social aspects in mid term future period. Also a high speed and high capacity mobility network occurance is crucial and a priority for this region’s countries to be unit, integrated and advanced.

Sustainability, urbanization, and digitalization are among the mobility phenomena of the 21st century. These phenomena can best take place in developed countries. Central Africa must take significant steps regarding these mobility phenomena. Central Africa still constitutes one of the most important centers in the world. Sustainable transportation, reducing traffic congestion, increasing traffic safety, decreasing noise and air pollution, expanding railway investments, advancing autonomous vehicle technologies, equipping infrastructure facilities with current advanced technologies, and the integrated renewal of cities are the most important aspects of modern transportation and urbanization (Kiziltas, 2020).

Along with emerging technology, there are many alternative modes of transportation that provide high-quality service at high inter-city speeds. These can be classified as magnetically driven trains (Maglev), high-speed trains, airlines, high-comfort road transport. These modes of transport are highly competitive in cross-city travel, but their interconnections are combined or isolated accordingly.

  • Competitiveness
  • Integration
  • Residence instead of each other
  • Transformative transportation

These modes of transportation involve the priority, integration or substitution of cities according to their size, human characteristics, demand for transportation, urban features, interconnected spatial and technical locations, requirements, distances between cities and a number of fundamental parameters. Among the various cities in Western Europe, this is the case with high-speed trains and airlines (Marta et al, 2010).

5. Discussion And Conclusions

In this context, Figure 10 shows metropolization map of Central East Africa.  

Fig. 10. Central East Africa Metropolization Map (Dark Legend: The highest metropolization)

As shown in the map, the cities proposed as a result of deep analysis on this paper are cumulated mainly on south west and mid-south part of the region which are also include most central and densely populated areas of Central East Africa. When these areas are equipped a reliable regional planning perspective and high standard mobility services according to national principles, a regional metropolization unique map will emerge that trigger international integration of east Africa, central Africa and west Africa. On the other hand, with the completion of all the proposed planning and execution, a big integration will occur on south of continent, center of continent and north of continent too. Due to the region’s wide geography, the extension of the proposal clusters will accelerate a variety of various strategic dynamics.

References

  1. https://depositphotos.com/tr/vector/east-africa-map-with-flags-125033368.html
  2. https://www.arthipo.com/tr-tr/dogu-afrika-haritasi-posteri.html
  3. https://www.milliyet.com.tr/egitim/haritalar/afrika-haritasi-fiziki-siyasi-afrika-kitasinda-olan-ulkeler-akarsular-goller-akarsular-goller-nelerdir-6305774
  4. OECD Africa Population, 2020
  5. https://pixers.com.tr/duvar-resimleri/afrika-39-nin-siyasi-haritasi-45814900
  6. OECD Africa City Populations and GDP’s, 2020
  7. https://www.orangesmile.com/gezirehberi/afrika/ulke-kabartma-haritalari.htm
  8. Givoni, Moshe. Development and impact of the modern high‐speed train: A review. Transport reviews, 2006, 26.5: 593-611.
  9. Kiziltas, M.C., High-speed Railways, Study of Impact on Production and Economic Development, BEU Journal of Scientific Sciences, 9 (4), 1844-1853, 2020
  10. Sanchez-Borras, Marta, et al. Rail access charges and the competitiveness of high speed trains. Transport policy, 2010, 17.2: 102-109.