Spatial distribution of Urban land-use in Addis Ababa, Ethiopia

ABSTRACT

This study underlines the critical function of efficient urban land use planning, recommending mixed land use for improved city sustainability. The research, which is rooted in the historical context of urban renewal, attempts to harmonize theoretical frameworks with actual implementation, giving critical insights for policymakers and urban planners in constructing sustainable urban areas. The study identifies a deficit in empirical research on the spatial distribution of urban mixed land use, as well as a gap between theory and real application. Using a mixed-methods approach, it explores mixed land use planning concerns by including stakeholder input and temporal dynamics. Using theoretical frameworks, the study explores land use trends in four Addis Ababa sub-cities. When the null hypothesis of Complete Spatial Randomness is rejected, there is a significant relationship between location and land use functions (statistical chi-square value of 47.763). Finally, the study makes crucial recommendations for purposeful land use distribution in a dynamic urban setting, shedding light on the constraints of mixed land use planning in African urban growth.

KEYWORDS:

• Urban land use planning
• mixed land use
• sustainability
• empirical studies

1. Introduction

This study looks at the spatial distribution of urban land use as well as the practical implementation of mixed land use planning. It evaluates the implementation of mixed land use planning in specific locations, matching with theoretical frameworks and assessing the efficacy of planning and development standards. Efficient land use planning is critical for creating sustainable, resilient, and thriving cities by encouraging diversity, minimizing dependency on automobiles (Debrah et al., 2023), and stimulating social connections. The project aims to assist policymakers and urban planners with insights into constructing more livable and sustainable cities.

The 1950s and 60s urban renewal projects and single zoning codes of American cities raised critical questions on urban planning that led the famous Jane Jacobs to coin the concept of mixed land use as important for maintaining lively neighborhoods and streets (Fan et al., 2019). This idea and concept later propagated in international programs such as the SMART growth (Gren et al., 2019; Marshet et al., 2019; Song, 2022), the New Urbanism movement (Alice Nilsson, 2017; Kong et al., 2015), and the new urban agenda (Alice Nilsson, 2017; Rudd et al., 2018). Mixed land use promoted with the intention to achieve walkable streets (Babic, 2021; Evans et al., 2016) and inclusive development (Turok et al., 2018), reducing motorized transport use (Huang et al., 2018; Tiwari et al., 2016), increasing proximity to services, public health and local economic benefits (Artmann et al., 2019).

Despite the obvious benefits of mixed land use, some argue that it has resulted in unexpected effects. As a result of mixed land use, problems such as noise, traffic congestion, stressed infrastructure, and overall disorder have been noted. Furthermore, the phenomena has been related to a rise in land surface temperature, which contributes to the formation of urban heat islands (Mondal et al., 2021; Pandey et al., 2022) Furthermore, several studies, notably (Abdullahi et al., 2015) question whether mixed land use has produced the expected favorable consequences.

Mixed land use planning necessitates a comprehensive approach to implementation, led by regulatory mechanisms. Principles such as walkability (Fonseca et al., 2021), mixed-use development, and polycentric urban architectures (Fan et al., 2019) are founded on theoretical frameworks. The Processes of empirical validation investigate how these concepts manifest in urban settings and social interactions. A dynamic feedback loop examines how Smart expansion ideas are translated into sustainable urban expansion strategies. The study recognizes contextual diversity in different locations and examines how the distinctive characteristics of selected locales influence the practical implementation of mixed land use planning. A thorough examination of zoning rules (Y. Li et al., 2022), form-based codes (Kloosterboer, 2019; Singh, 2010), Transit-Oriented Development (TOD) guidelines (Huang et al., 2018), and Public-Private Partnerships guarantees a thorough examination of regulatory tools and their alignment with theoretical frameworks (Fleta-Asín et al., 2020; Wang & Ma, 2021). This integrated approach seeks to bridge the theoretical and practical gaps by providing nuanced insights into the challenges of mixed land use planning and development (Afzalan & Muller, 2018; W. Li et al., 2020; Rahnama et al., 2012).

This research fills important gaps in the existing literature on the spatial distribution of urban mixed land use and functions in urban community block (Oikonomou, 2015).Block is the space within the street pattern of a city that is subdivided into land lots for the construction of buildings (Vialard, 2014; Ye & Dong, 2018). It emphasizes the scarcity of empirical research and the gap between theoretical debates and practical application. The study tries to bridge these gaps by emphasizing the need of extensive theoretical framework investigation in urban development and the requirement for context-specific planning. Furthermore, it actively solicits stakeholder feedback and focuses a special emphasis on comprehending the temporal dynamics inherent in mixed land use planning. The major goal of methodically addressing these critical gaps is to contribute to the progress of urban planning methods.

This study investigates the spatial distribution of urban function, with a focus on mixed-use planning and its emergence from theoretical frameworks. It investigates modern paradigms, such as Carlos Moreno’s (Antônio et al., 2016) 15-minute city concept (Allam et al., 2022), which envisions metropolitan landscapes with everyday essentials within a short commute. The research also looks at notions such as ‘complete streets’ (McAslan, 2017) and ‘transit-oriented development’ (Huang et al., 2018), which promote inclusive streetscapes and development near transportation hubs. The study is especially pertinent to African cities, given their distinct socioeconomic dynamics and historical legacies. The research intends to provide nuanced insights by evaluating the practical implications of mixed land use planning principles and modern concepts in selected African metropolitan environments. The study will make a theoretical and practical contribution to the debate.

The dynamic alteration of Africa’s urban landscape, driven by population increase, urbanization, and economic development, emphasizes the importance of diversified land use for sustainable urban environments (Cobbinah et al., 2015; Garfias; Royo et al., 2022; Slavova & Okwechime, 2016). However, the implementation of this method is inextricably linked to historical legacies and existing policy frameworks. Theoretical frameworks highlight the importance of mixed land use in generating diverse and lively urban environments that support social interaction, economic vigor, and environmental sustainability (Pandey et al., 2022). This study investigates the application of mixed land use planning in selected urban area in Addis Ababa city, specifically how planners integrate theoretical frameworks into decision-making processes.

This research actively contributes to the discourse on African urban development by leveraging insights from existing literature, global urbanization trends, and distinctive case studies. Acknowledging formidable challenges such as informality, poverty, and deficient infrastructure, the study puts forth recommendations aimed at enhancing the effectiveness and contextual relevance of mixed land use regulations. The overarching objective is to promote sustainable and inclusive urban growth in Africa. Through a meticulous analysis of perspectives held by Sub-Saharan African city planners and a comprehensive evaluation of existing regulatory frameworks (Caprotti et al., 2017; UN-Habitat, 2011), this study seeks to illuminate the positioning of planners concerning the concept of mixed land use. By doing so, it endeavors to provide valuable insights that can significantly enrich urban planning strategies in the region.

The literature on mixed land use planning represents both successful and bad implementations, offering crucial insights into best and worst practices. The Best practices can be found in cities such as Copenhagen (Prato et al., 2018) and Vancouver (Shulman, 2021; Wideman et al., 2020), where careful planning has resulted in vibrant and harmonious urban environments (Parhizgar, 2013). However, the literature also identifies problematic practices, most notably in certain American cities where poorly implemented mixed-use zones have resulted in problems and dissonance (Lin et al., 2020; Zhang et al., 2019). Understanding these disparate outcomes highlights the need of context-sensitive design (Rauws, 2017) and community engagement (Dyer et al., 2014; Tavares et al., 2022). This study draws on this literature to inform an in-depth review of planning guidelines, regulatory instruments, and case studies as it digs into the assessment of practical applications. This approach intends to bring useful insights to the area by providing a comprehensive knowledge of the complexity surrounding the success or failure of mixed land use planning initiatives.

Even though urban planning has evolved from rigid master planning and land use zoning to more flexible structure and strategic planning, the mode of operation of zoning the top-down bureaucratic procedures of controlling land use remains to face similar challenges (Chitrakar et al., 2017). While there are fundamental arguments and critics raising questions on the relevance of imported models and the possibility of meaningful influence of the land use zones on the actual development course in the context of rapid urbanization (Echendu & Claver Chiedozie Okafor, 2021), complex interaction of legal and illegal governance system, and power interplay (Alemie et al., 2015). Acknowledging these challenges, on the other hand others ascertain that the reality does not show an entirely impotence of the planning tools across the board, while there are wide variations as to the level of influence in actual implementation through some sort of negotiation (Berrisford et al., 2018; Goodfellow, 2013).

While with that being said about the overall international experiences and reflections of previous studies, this paper tries to understand what is the situation in Addis Ababa the specific urban planning and development guideline, the regulatory controlling tools employed and their level of influence in the implementation taking a specific local case and draw lessons in light of the above arguments. It aims to contribute to the body of knowledge developed (the above mentioned studies) and compare and contrast with the finding of the previous studies (Table 1).

Table 1. A chronological table documenting Addis Abeba’s planned milestones, activities taken, and related references from 1986 to the present. This information is derived via 2020 fieldwork and map analysis.

Year Range	Planning Approach	Purpose of Change	Key Initiative and Concerns	References
1986	Master plan Zoning	Dictate the development of the city for consecutive 20 years	Introduce distinct zoning codes outlining permissible activities in specific zones. Criticized later for lack of flexibility and alignment with changing economic policy.	(Kloosterboer, 2019; ORAAMP, 2002)
2002–2014	Mixed Land Use Development	Address concerns about settlement pattern and decline in quality of life. Encourage Mixed Land Use Development (MLD) to promote urban development.	Introduce MLD as a zoning strategy to induce flexibility and facilitate private investment. Structure plan outlines green infrastructure, main road networks, markets, and services.	(Kloosterboer, 2019; ORAAMP, 2002)
		Establish regulatory mechanisms for urban development, including local Development Plans (LDPs), compatibility matrix,	Potential of LDPs largely untapped due to lack of systematic approach and consistent regulations. Challenges in execution lead to inadequate implementation of LDPs.	(Benti et al., 2022)
	Structured Plan	Shift from a ‘strict’ masterplan to one allowing on-the-ground flexibility and negotiation for better urban expansion control.	Utilize goal-setting with structured plan and local development plans. Signify a shift in planning strategy.	(Monclús, 2003; ORAAMP, 2002)
2017	Transformation towards MLD	Respond to challenges posed by transformation towards mixed land use.	Note erosion of functional specialization, escalating conflicts among land uses, and blending of diverse activities.	(AACPPO, 2017)
Present	Goal-Setting Approach	Adoption of structured plan and local development plans by Addis Ababa City Government plan commission office.	Control urban expansion and increase inner city redevelopment and infill in main, secondary corridor redevelopment.	from author site survey 2020

In many parts of Addis Ababa, mixed land use zoning planned as the basis for sustainable development (Colding et al., 2020) and smart growth in urban areas (Saaty & De Paola, 2017). These zones believed to attract more populations, which in turn is able to increase economic activity and, as a result, enhance daily commercial activities in the area. Therefore, this was thought to be an excellent way of activating and motivating those areas that were suffering from deterioration in economic status and promoting pedestrian movement. On the contrary, mixed land use has had negative consequences for the community (Bahadure & Kotharkar, 2012; Delisle et al., 2021; Zahnow, 2018) Such as creating noise pollution inside the urban blocks and overcrowding of industrial, commercial, and residential zones that ultimately lead to disturbance of the living as well as the working environment if not managed.

In the process of urban settlement, since the establishment of Addis Ababa from traditional or local (i.e. it refers to the process of urban or rural development and land use management that is rooted in the customs, practices, and values of a particular community, culture, or region) to pure zoning, then modern mixed land use. There were shifting of functional specialization and mixing of different uses in specific area; i.e. changing of planning from zoning to mixing, challenges of Addis Ababa city. Mixed Land-use is defined in functional mix conceptual level point of view. The application of mixed land use planning and development has an impact on urban areas (Cheng & Van Ameijde, 2023; Ewing & Cervero, 2010) Whether, the traditional or planned mixed land use settlements that have been created through traditional or modern mixed land use development affect urban areas. The mixing of uses at a specific site affects the dweller’s life positively or negatively. Individuals and communities generate different types of functions that change the built environment; those functions harmonize or create conflicts between competing uses. Thus, how they are planned? What are those development principles, clear guide line and controlling regulation tool? Are major problems that needs a solution at its outgrowth level. There for this study hypothesizes the distribution of land use in selected locations, either randomly or as associated each other?

2. Methods

The study adopts a mixed-methods methodology to analyze the dynamics of land use planning in Addis Ababa’s four sub-cities in depth. The research design complies to Creswell’s suggestions by utilizing both quantitative and qualitative research methods (Creswell, 2017), allowing for a nuanced examination of urban land use trends. Data is collected from a variety of sources, including maps, surveys, and on-site data, resulting in a strong dataset for analysis. To improve understanding of horizontal land use mix, statistical approaches such as SPSS and ArcGIS are used. The project, which spans 160.29 hectares and spans the years 2002 to 2017, focuses a significant emphasis on ethical issues and transparent reporting, favoring trustworthiness despite potential limits.

The thorough crafting of the methodology is obvious in the deliberate selection of several sub-cities and the incorporation of spatial analysis techniques such as point pattern and quadrant analysis. This not only adds to the study’s overall validity by providing insights regarding land use spread. The systematic use of random and stratified sampling methods, together with a carefully determined sample size, further enhances the study’s findings’ dependability. Ethical considerations and transparency in addressing shortcomings highlight the dedication to rigorous research. The Chi-square test in SPSS is an important component, highlighting the precision used in investigating correlations between geographical locations and functional categories. In final analysis, this well-designed mixed-methods methodology allows for a deep and robust research into the complex dynamics of land use planning in Addis Ababa (Figure 1).

Figure 1. Location map of the study areas in Kir-kos and Bole Sub-cities. Source: from structural plan manual (revised version) May 2012, Addis Ababa.

The figure (Figure 2) illustrates different study areas in Addis Ababa, Sourced: from the revised version of the structural plan manual dated May 2012, provided by the Addis Ababa authorities and updated in air Map obtained from EMA, over lay current google earth Map 2023.

Figure 2. a) each corresponding to a sub-city. The main city center (MCC) map focuses on the legehare study area, encompassing Woreda 6, 7, 9, and 10. b) the main corridor (MC) map pertains to Woredas 1, 2, and 9, commonly known as Africa Street, extending from the Dembel area to the wollo-sefer roundabout. c) the secondary corridor (SC) map features the sub-Arterial Street (SAS) in Woreda 4, known as the ‘22 roundabout’, extending up to the cross junction near the new stadium. d) around goru junction (AGJ), the map covers Woreda 11, locally referred to as ‘goru’.

It is important to note that when we refer to distance from the center, we specifically denote the straight-line distance from Minilik Square outward to the periphery, providing a precise framework for understanding the spatial relationships of these selected sites.

This flowchart (Figure 3) outlines the key steps and components of the research methodology, from the research design to the presentation of findings. It shows the logical flow of the processes involved in the study.

Figure 3. Comprehensive flowchart of the research method.

The research design of this study encompasses a mixed-methods approach, drawing on both quantitative and qualitative research methodologies, as elucidated by (Creswell, 2017). Quantitative methods were instrumental in conducting data analysis, while qualitative methods played a crucial role in unraveling the practical applications of mixed land use planning. The study focused on four specific inner and peripheral sub-cities of Addis Ababa, deliberately chosen for their unique characteristics. Residential properties were randomly assigned for investigation across distinct areas, including the Main City Center (MCC), Main Corridor (MC), Secondary Corridor (SC), and Periphery (AGJ). Data collection involved a meticulous combination of maps and on-site surveys, utilizing information from diverse sources such as the Addis Ababa Plan Commission, Ethiopian Mapping Agency (EMA) 2016 Air Map, 2020 physical survey data, and 2023 Google Maps. The integration of these datasets facilitated the creation of a comprehensive map for analysis. To unravel the intricacies of land use patterns, the study employed descriptive statistics through SPSS and utilized ArcGIS for quadrat point pattern analysis and Poisson distribution, providing a nuanced understanding of horizontal land use mix. The examination of study areas delved into diverse factors, including proximity to the city center, socioeconomic characteristics, public services, accessibility, land value, street attributes, settlement type, and development time, thereby enriching the analysis with a multifaceted perspective.

The determination of the household sample size involved applying the formula n = (z² pq)/d² : n = (1.96)²(0.5) (0.5)/(0.05)², n = 384. The confidence level (z) was established at 95%, with estimated population characteristics (p) assumed to be 0.5, and the margin of error (d) set at 0.05. This method ensures a reliable and statistically sound sample size for the subsequent data collection and analysis, aligning with established standards in survey research. In the sampling process, a systematic random sampling method was utilized. The sampling interval (K) was determined through the formula K=nN, where N represents the population size, and n is the sample size. This approach involved selecting every ‘K’ element within the population, commencing from a randomly chosen starting point. The systematic nature of the sampling ensures a representative and structured approach to data collection, enhancing the validity of the study’s findings. In implementing stratified sampling, the aim was to guarantee comprehensive representation across sub-cities and different areas (Table 2). The stratification formula used for calculating the sample size within each stratum was expressed as ni = (n/N) Ni. This method facilitated a meticulous survey population and sample allocation strategy, ensuring a balanced and well-represented distribution of samples across distinct sub-city categories and areas. The utilization of stratified sampling enhances the precision and reliability of the study’s findings by considering the diversity within the larger population.

Table 2. Sample size allocation for sub-Cities.

Name of Sub-City	Targeted Population (houses)	Share of one sub city from targeted population	Study Site	Sample Size (n) (No of houses)
Kir-kos	59,589.80	160.22	MCC	81
			MC	81
Bole	83,225.40	223.77	SC	126
			AGJ	96
Total	142,815.20	384		384

The temporal scope of this study spans from 2002 to 2017, capturing a comprehensive view of urban land use dynamics. The expansive study area encompasses 160.29 hectares, providing a robust foundation for spatial analysis. To ensure data accuracy and relevance, an updated map meeting specified criteria was generated on 2 February 2020, validating the integrity of the information used in the study. Ethical considerations were paramount throughout the research process, with a commitment to adhering to established standards in conducting surveys and gathering data from households. Recognizing potential limitations, such as biases in random sampling and dependence on existing data sources, the study employs transparency in acknowledging these constraints. Findings are meticulously presented through a combination of maps, tables, and graphical representations, offering a comprehensive framework for assessing both the spatial distribution of urban land use and the practical implementation of mixed land use planning in the selected study areas.

2.1. Assumption and hypothesis

The analysis of events within defined study areas, representing the distribution of commercial, residential, and mixed functions, is grounded in two critical assumptions. Firstly, events (uses) are assumed to occur independently, meaning the occurrence of one event provides no information about the timing of another. Secondly, the probability of an event occurring within a given period remains constant over time. To analyze this, the relationship between the number of observations and the count of events per quadrant is presented for each study site.

2.2. Spatial analysis technique

A multifaceted approach is employed for a comprehensive understanding of the dispersal of applications within a specific region (Table 3). This involves point pattern analysis, spatial arrangement exploration, and rigorous statistical examinations. Quadrant analysis, based on the works of (Antônio et al., 2016; Heyne & Fhoteringham, 2020; Neel et al., 2004). is utilized to scrutinize the degree of clustering or the geographical pattern within the study area.

Table 3. Houses surveyed and quadrat calculation for GIS Analysis.

Study Site	Area of the Study Site (in hectares)	Number of Houses (Events) (n)	Area of Quadrant in Sq m	Number of Quadrants
MCC	70.3	81	121	80
MC	25.72	81	126	80
SC	27.55	126	160	80
AGJ	36.72	96	99	80
Total	160.29	384	506	320

Source: study site survey data, 2020.

This table provides details on the study areas, their respective sizes, the number of surveyed houses, and the parameters for quadrant analysis. Quadrat size calculations, utilizing square quadrats, ensure a balanced approach in spatial analysis, taking into account crucial factors like quadrant size, cell size selection, and grid placement. The quadrant analysis, based on spatial arrangement and statistical examinations, categorizes point distributions as clustered, uniform, or random. The study employs a Chi-square test to determine the significance of associations, focusing on the distribution of land use types (mixed, residence, commerce) within four areas: MCC, MC, SC, and AGJ. This research utilizes SPSS software to investigate the relationship between geographical locations and functional categories, classifying functions into three primary groups: Mixed, Residential, and Commercial. Commercial functions include entities such as banks and retail stores, residential functions consist of apartments and standalone homes, while mixed functions encompass that blends multiple uses into one space where those functions are to some degree physically and functionally integrated.

3. Result

Urban areas have unique land uses and development paradigms. In the study area, Addis Ababa, the land use type is usually a mixed of residential with commercial-type. The general scenario of land use planning is adapted as the mixed development. However, such land use development is taking place with shallow legal and policy background that frame the plan. Hence, under this sub section, the results concerning challenges of the mixed land use development, distribution of functions mainly residential, commercial and mixed which are not consistent and mutually supportive each other, resulting disturbances in the land use planning.

In Figure 4, we illustrate the distribution of functions across four study sites (MCC, MC, SC, and AGJ) during a 2020 site survey in Bole and Kirkos sub-city. We measured these functions in terms of households. SC had a higher residential use compared to the other study areas, with residential functions being the most prevalent across all study sites. On the contrary, commercial use was the least common function when compared to mixed-use (Table 4). Specifically, SC had approximately 79% residential use, whereas AGJ had precisely 62%. AGJ also had a higher residential usage than MC, with percentages of about 62% and 56%, respectively. In the context of mixed use, MCC accounted for approximately 46%, while SC had roughly 36%. SC had a greater proportion of mixed use compared to AGJ, with percentages of around 36% and 20%, respectively.

Figure 4. The distribution of commerce, residence and mixed functions on the four study site (MCC, MC, SC and AGJ) Source: Author, Site survey, 2020.

Table 4. Chi-square statistical test result of location and functional distribution.

Study site	Count	Commerce	Residence	Mixed	Total
MCC	Observed	9	26	46	81
	Expected	10	47	24	81
	${\chi }^2$	0.2	9.4	21.2	30.8
MC	Observed	15	56	10	81
	Expected	10	47	24	81
	${\chi }^2$	2.1	1.7	7.9	11.7
SC	Observed	11	79	36	126
	Expected	16	73	37	126
	${\chi }^2$	1.6	0.5	0.0	2.1
ATJ	Observed	14	62	20	96
	Expected	12	56	28	96
	${\chi }^2$	0.3	0.7	2.3	3.2
Statistical Chi square				X^2	47.763
Degree of freedom (df) = (r-1) *(c-1)				df	6.000
Statistical tables Chi square value				X^2	12.592

Source: study site survey data, 2020.

Chi-square statistics were employed to explore the relationship between location and the distribution of functions (Mixed, Commerce, and Residence). At the 5% significance level, our analysis reveals a noteworthy connection between location and the current function at the specified site (χ² = 47.763, df = 6, p = 0.001). Notably, the statistical chi-square value greatly exceeds the tabulated critical value (i.e. 47.763 > 12.592), providing substantial evidence to reject the null hypothesis (Ho). Consequently, we cannot accept the null hypothesis, affirming a significant link between location and function. Hence, we find support for H1.

Given that our p-value is less than 0.05, we can confidently conclude that the observed pattern of selected sites does not significantly differ from the expected distribution under the null hypothesis of Complete Spatial Randomness (CSR). To further assess the magnitude of these differences, we conducted an effect size analysis, which revealed a small to medium effect size (0.353). This outcome suggests that location does indeed have a discernible impact on the distribution of functions.

The paper compares propose that, in a specific metropolitan region in Addis Ababa, location has more weight over functional distribution than the Mixed land use theoretical planning and development framework, as well as its related clear standards and laws. The study aims to test and appraise the practical use of mixed land use planning in accordance with theoretical frameworks. Furthermore, the study examines the chosen area’s planning and development rules, as well as regulatory mechanisms. In contrast to the null hypothesis suggesting a negative correlation between location and functional distribution, the results reveal that pure residential functions exhibit a more scattered distribution when compared to mixed and commercial types of use, as depicted in Figure 4. The analysis, employing Pearson’s correlation coefficient, shows a weak negative correlation between location and functional distribution (r = 0.123). Moreover, there is no significant association between function and location (r = −0.516). These findings imply that functions are distributed in a seemingly arbitrary and unrelated manner. Conversely, functional distribution appears to be relatively unaffected by the specific location.

The Figure 4–7 displayed below are the results of Quadrat Analysis generated using ARC-GIS software. These outputs include point pattern density (considered houses as points), the distribution of houses observed within the designated quadrats, and the Poisson distribution.

Figure 5. Main City center analysis Source: study site survey data, 2020.

Figure 6. Main Corridor Quadrat analysis Source: study site survey data, 2020.

Figure 7. Secondary corridor Quadrat analysis Source: study site survey data, 2020.

In Table 3 above, we present the house density data for the study area, including MCC, MC, SC, and AGJ, gathered during the 2020 site survey in Bole and Kirkos sub-cities. The units of measurement are houses per hectare. Overall, the secondary corridor exhibited the highest house density compared to the main corridor, while the Main City Center had a higher density than the peripheral areas. Specifically, SC boasted a density of approximately 41 houses per hectare, in contrast to MC’s 16 houses per hectare. Furthermore, MCC showed a higher density than AGJ, with figures of approximately 27.2 and 19.2 houses per hectare, respectively.

4. Discussion

The study of the spatial distribution of urban land use in Addis Ababa, notably in the sub-cities of Bole and Kirkos, gives light on the actual application of mixed land use planning. This research departs from theoretical frameworks that argue for strong legal and policy foundations in mixed land use planning (Butler, 2006; Rudolf et al., 2018), revealing a scenario in which mixed land use development occurs with inadequate support in these areas. The quantitative findings highlight the difficulties in achieving a consistent and mutually beneficial distribution of functions, particularly in the prevalence of residential land use across all study sites, with the Secondary Corridor (SC) exhibiting the highest residential use at approximately 79 % (see Figure 4).

The results of chi-square analysis show a substantial relationship between location and land use distribution, which is consistent with previous studies stressing spatial dependency in land use patterns (Briassoulis, 2020; Credit, 2019; Jun, 2017).The rejection of the null hypothesis of Complete Spatial Randomness (CSR) and the modest to medium impact size add to the evidence that spatial determinants influence observed land use distribution. Furthermore, Pearson’s correlation coefficient indicates a modest negative association between location and functional distribution, highlighting the subtle and complicated nature of spatial correlations in urban land use (Duncan et al., 2012; Ganguly et al., 2017; Generalova et al., 2018).

The use of GIS-based Quadrat Analysis provides a geographical viewpoint, revealing different home densities across research sites. The higher density in the Secondary Corridor (SC) highlights the spatial variability of land use patterns within the city, providing useful insights for urban planners and policymakers while underlining the importance of context-specific land use planning techniques.

The study’s goal was to assess the practical implementation of mixed land use planning while taking both theoretical frameworks and planning principles into account. The findings indicated significant geographical distribution elements that support the goals of mixed-use planning and refute the CSR hypothesis. Pearson’s correlation coefficient revealed a somewhat negative relationship between location and functional distribution. Furthermore, the Quadrat Analysis graphically verified these findings, providing subtle insights into the complex interaction between location and land use distribution in the context of urban planning (see Figure 5–8).

Figure 8. Around Goru Junction Quadrat Analysis Source: study site survey data, 2020.

The analysis reveals crucial links in the geographical distribution of urban land use in the sub-cities of Bole and Kirkos, highlights the non-random nature of urban land use distribution, which is corroborated by chi-square analysis, which shows a significant association between location and land use distribution. The correlation research, on the other hand, reveals a minor negative association between location and functional distribution, implying the influence of factors other than geography. The Quadrat Analysis graphically highlights non-random spatial patterns, allowing for a more complete comprehension of the subtle processes affecting land use in the selected sub-cities (Mix & Pafka, 2017; Summary, 1996).

Statistical calculations show that the study has dual relevance. The Chi-square analysis shows a strong relationship between location and distribution of land use, however the correlation study finds only minor correlations, showing that factors other than location have a larger influence. These modest insights add to a full understanding of the intricate mechanisms that determine the spatial distribution of the study area of urban land use, both confirming and deviating from previously predicted hypothesis.

The study’s significance is defined by theoretical frameworks and prior research, which examine the spatial distribution of urban land use in the sub-cities of Bole and Kirkos. Chi-square analysis backs up well-known urban planning theories (Carpio-Pinedo et al., 2021; Shen & Sun, 2020), arguing for the effectiveness of mixed-use design and rejecting the null hypothesis. The correlation analysis, which found weak links between location and functional distribution, supports the theoretical premise that factors other than geographical location has a considerable influence on land use patterns. This intricacy, inherent in urban planning theories, highlights the multifarious nature of the identified linkages in the selected sub-cities.

The study on the practical application of mixed land use planning in the sub-cities of Bole and Kirkos concludes by highlighting a substantial relationship between location and land use distribution, hence validating the efficacy of mixed Land use planning as advocated in urban planning theories. The sophisticated theoretical argument that local contextual factors greatly determine land use patterns is supported by the nuanced findings of the correlation analysis, which show the influence factors other than geographical location. These findings highlight the complicated interplay between theoretical frameworks and observable realities in urban planning, revealing important insights into the complexity of achieving balanced and purposeful land use in dynamic urban environments.

The exploratory study admits limitations that limit the breadth and usefulness of its findings. The scarcity of empirical studies on civic mixed land use geographical distribution may limit the depth and generalizability of the analysis. Capturing variances across diverse civic environments is difficult, and this has an impact on the soundness of given solutions. The depth of stakeholder engagement may vary, influencing the findings’ significance. The study’s concentration on specific Addis Ababa sub-cities may limit its applicability to other places. Long-term trends may not have been fully captured throughout the study period of 2002 to 2017. Implementation challenges in mixed land use planning may limit insights into the real effectiveness of these programs. In geographical analysis, hypotheses may oversimplify complex civic dynamics. The single-megacity emphasis and limited legal and policy backdrop may limit the broader applicability of recommended strategies. Future research could broaden understanding by looking beyond regional boundaries, doing a more nuanced examination of socioeconomic, creative, and literal effects, and applying qualitative methodologies for a more complete picture.

Future study could expand our understanding of urban land use trends by looking beyond geographical concerns. A more comprehensive assessment of socioeconomic, cultural, and historical impacts could provide deeper insights into the intricacies of the urban landscape. Longitudinal research documenting changes over time would add to a more dynamic understanding of how urban landscapes evolve. In terms of suggestions, comparative evaluations across cities or regions with varying planning policies and socioeconomic conditions could give information on the influence of different planning approaches on land use distribution. Furthermore, future research might apply qualitative approaches to investigate residents’ and companies’ perspectives and preferences, providing a more comprehensive understanding of the acceptance and success of mixed-use design concepts. In order to further this research, the use of qualitative approaches could provide deeper insights into the decision-making processes that influence land usage. Collaborative research involving urban planners, politicians, and community stakeholders could improve practical applications in urban planning and policy, creating a more complete perspective. Furthermore, the inclusion of variables linked to community participation, infrastructure development, and accessibility in future studies may provide a more holistic understanding of the complex dynamics forming urban environments.

Extending the conceptual scope to include a broader range of land use types or investigating the impact of land use patterns on environmental sustainability could be considered, resulting in a more comprehensive understanding of the interconnectedness of land use planning, social dynamics, and environmental considerations. Finally, future research might look into advanced spatial analysis approaches like geospatial modeling or machine learning algorithms to improve the precision and depth of analyses about the geographical linkages between land use and numerous influencing factors. These guidelines are intended to guide future research efforts, ensuring a more thorough examination of the intricacies inherent in urban land use processes.

The findings of this study have important consequences for individuals, management, and organizations working in urban areas. Individually, households and enterprises stand to benefit from a better awareness of the geographical distribution of functions, allowing them to make better decisions.

Author contribution statement

Girmachew Tariku: Conceived, designed and performed the research; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Dr Liku Workalemahu: Conceived, developed the research; Examined and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Dr Dagnachew Adugna: Conceived and designed the research; Analyzed and interpreted the data; Wrote the paper.

Ethical approval and informed consent

This study paper was ethically approved by the Addis Ababa University, Ethiopia Institute of Architecture, Building Construction and City Development. The Ethical Review Board with a member of five committees named as Dr. Mintesnot Woldeamanuel (Chair), Dr. Fisseha Wegayehu (Member), Dr. Dipl-Ing Berhanu Woldetensae (Member), Dr Dagnachew Adugna (Member), Dr Liku Workalemahu (Member). For this study, a written informed consent was obtained from Thesis Proposal Evaluation Committee before collecting a primary data (Survey Questionnaire). The Ethical Approval Letter include conclusion, recommendation and evaluation result of the Ph.D. Thesis proposal.

After that the university write cooperation letter for Bole, Kir-Kos sub city, and for other institutions that relevant for study. Accordingly, confidential letter was written and communicated with cellphone and email with each individual respondents and offices. After Informed and obtained consent for all subject, individuals and institutions involved in this study then, I started to collect every relevant data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The collected data was filled in hard and soft copy, included, referenced in article. And also the data presented in this study are available in corresponding author and can provide if, the publisher required any time.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Appendix A

Table A1. Demographic characteristics of the household sample.

	MCC		MC		SC			AGJ
Gender
	Frequency	Percentage	Frequency	Percentage	Frequency	Percentage	Frequency	Percentage
Male	43	53.1	43	53.1	63	49.2	51	52.1
Female	38	46.9	38	46.9	65	50.8	45	46.9
Total	81	100	81	100	128	100	96	100
Age of respondents
18–27	21	25.9	43	53.1	39	30.5	30	31.3
28–37	33	40.7	25	30.9	45	35.2	40	41.7
38–47	14	17.3	6	7.4	22	17.2	16	16.7
48–57	8	9.9	1	1.2	16	12.5	6	6.3
58–67	3	3.7	1	1.2	3	2.3	2	2.1
68–77	2	2.5	0	93.8	1	0.8	2	2.1
Missing System	0	0	5	6.2	2	1.6	0	0
Total	81	100	81	100	128	100	96	100
Education
Illiterate	1	1.2	2	2.5	4	3.1	2	2.1
Read and write	2	2.5	4	4.9	6	4.7	1	1
Grade 1 up to 8	9	11.1	9	11.1	11	8.6	9	9.4
Grade 9 up to 12	13	16	7	8.6	12	9.4	14	14.6
Diploma	32	39.5	32	39.5	54	42.2	37	38.5
Degree and above	24	29.6	26	32.1	41	32	33	34.4
Missing System	0	0	1	12	0	0	0	0
Total	81	100	81	100	128	100	96	100
Job Status
Business	5	6.2	16	19.8	20	15.6	29	30.2
Engineering (graphics, Artiest)	5	6.2	1	1.2	6	4.7	3	4.1
Social Science (economist, accountant,)	3	3.7	3	3.7	12	9.4	12	12.4
Secretarial, Social Work	6	7.4	3	3.7	7	5.5	18	18.8
Others (Driver, teachers)	12	14.7	2	2.5	7	5.4	13	13.6
Nursing, public health, Doctor, Pharmacists, Public/Health Admin	0	0	1	1.2	9	7	0	0
Students	12	14.8	8	9.9	5	3.9	4	4.2
No job	0	0	4	4.9	13	10.2	0	0
No response	38	46.9	43	53.1	44	34.4	16	16.7
Total	81	100	81	100	128	100	96	100
House hold size
Single	4	4.9	7	8.6	6	4.7	12	12.5
Paired	16	19.8	8	9.9	13	10.2	7	7.3
Three	16	19.8	18	22.2	21	16.4	23	24
Four	10	12.3	19	23.5	24	18.8	15	15.6
Five	6	7.4	21	25.9	27	21.1	13	13.5
Six	5	6.2	6	7.4	21	16.4	15	15.6
Seven	4	4.9	1	1.2	8	6.3	7	7.3
Eight and above	4	4.9	1	1.2	8	6.3	4	4.2
No response	16	19.8	0	0	0	0	0	0
Total	81	100	81	100	128	100	96	100
House ownership
Government	26	32.1	4	4.9	10	7.8	0	0
Private	16	19.8	16	19.8	42	32.8	8	8.3
Kebele/Public	24	29.6	25	30.9	39	30.5	52	54.2
Rental House	14	17.3	36	44.4	36	28.1	33	34.4
Others	1	1.2	0	0	1	0.8	3	3.1
Total	81	100	81	100	127	100	96	100