International Journal of Human Capital in Urban Management

Abstract BACKGROUND AND OBJECTIVES: Urbanization and rapid population growth are significant global challenges, especially in cities with outdated planning systems. Effective urban growth models, which utilize historical data, land use patterns, and population dynamics, are essential for predicting future expansion. In Kirkuk, Iraq, urban growth has occurred unregulated due to an outdated master plan, and a new plan has been introduced. However, no local studies have assessed the effectiveness of urban growth models against this plan. This study aims to fill this gap by evaluating urban development in Kirkuk from 1993 to 2023 and forecasting growth to 2037 using remote sensing and Geo-spatial Information System-based models.
METHODS: This research applied two urban growth models: Cellular Automata Markov chain modeling (CA-MARCOV) and SLEUTH, to analyze urban expansion in Kirkuk. Satellite imagery from 1993, 2003, 2013, and 2023 was used for land use classification. The Cellular Automata Markov chain model used transition probability matrices derived from land use data, while the SLEUTH model incorporated urban density, road networks, and slope data for simulations. Both models were tested for accuracy by comparing predicted urban growth for 2023 with actual land use data. The study also used these models to forecast urban expansion for 2037, comparing their predictions with the city’s new master plan.
FINDINGS: The land use classification indicated significant urban growth in Kirkuk, from 41.57 km² in 1993 to 155.5 km² in 2023. The accuracy of the predictions for 202F3 showed that the SLEUTH model achieved 87% accuracy, outperforming the Cellular Automata Markov chain model, which had 76% accuracy. For 2037, the Cellular Automata Markov chain model projected urban growth to 201.43 km², while the SLEUTH model predicted a larger expansion of 219.78 km². The SLEUTH model also excluded water bodies and restricted zones (such as oil fields and airports), which were manually identified, while the Cellular Automata Markov chain model did not account for these exclusions.
CONCLUSION: The SLEUTH model provided more accurate urban growth predictions and was selected for comparison with the new master plan. The results indicated discrepancies between the SLEUTH model’s predictions and the master plan, particularly in areas experiencing rapid growth, suggesting the need for adjustments. The southeastern and southwestern regions showed alignment with the plan. These findings highlight the importance of using accurate urban growth models for sustainable planning in Kirkuk, offering valuable insights for urban development through 2037

Abstract BACKGROUND AND OBJECTIVES: Currently, 56% of the global population, reside in cities, and this urbanization trend is predicted to result in a more than doubling of the urban population by 2050. Similarly, mid-sized Indian cities have exhibited rapid urban growth in recent decades. However, a holistic study focusing on the temporal dynamics of urban growth in all the mid-sized Indian cities is lacking. Therefore, this study aims to investigate the urban growth pattern across eighty-eight mid-sized Indian cities with the help of Census data from 1971-2011.
METHODS: This research, utilizing a quantitative approach, investigates the relationship between economic growth and urban expansion in selected cities. The cities are categorized based on the Gross State Domestic Product of respective states, and the study evaluates changes in municipal areas and demographic growth patterns through the decadal urban expansion rate and decadal population growth rate. The urban growth character is further analyzed by dividing the population growth rate by the decadal urban expansion rate, with a value less than 1 indicating inefficient land utilization. This comprehensive methodology aims to provide insights into the dynamics of urban growth and its correlation with economic development.
FINDINGS: The results revealed that inefficient land utilization for urban growth during 1971-2011 had occurred in thirteen cities from the states with higher Gross State Domestic Product and three cities among the states with lower Gross State Domestic Product. Overall, the mid-sized Indian cities, such as Ajmer (0.65), Solapur (0.67), Asansol (0.79), Mangalore (0.83), Jhansi (0.84), Nellore (0.85), Belgaum (0.86), Thrissur (0.86), and Bareilly (0.89) exhibited the lowest PU values during 1971-2011.The major drivers for urban growth in mid-sized Indian cities are government policies and schemes, industrial growth, rise in Gross State Domestic Product, climatic conditions and terrains, social profile, transportation, and infrastructure.
CONCLUSION: Overall, there has been inefficient land utilization in several cities, particularly those from states with varying levels of Gross State Domestic Product. Noteworthy cities like Ajmer, Solapur, and Belgaum consistently demonstrated efficient land utilization, reflected in their lower Population-to-Urban Expansion (PU) values. The study emphasizes the intricate influences shaping urban growth, encompassing government policies, industrial development, economic factors, climate, social dynamics, and infrastructure. Future research endeavors could further delve into the specific impact of these factors on urban expansion, employing longitudinal analyses, and explore the socio-economic ramifications of efficient or inefficient land utilization, contributing to more informed urban planning and policy formulation.

Abstract BACKGROUND AND OBJECTIVES: Recently, Jos Metropolis, Nigeria is witnessing a strong trend toward urban growth and expansion. This phenomenon has impacted Land Use/Land Cover and efficient management of land. This paper evaluated urban growth and changes in Land Use /Land Cover and examined the land use efficiency of the metropolis. Land Use and Land Cover changes were established from 1999 to 2022; Land consumption rate and population growth rate were determined, and computation of the SDG 11.3.1 framework was done to examine the efficiency of land use.
METHODS: Data were collected through official documents, the use of remote sensing, and, geographic information systems. Satellite imageries used to determine the classes and changes in Land Use/Land Cover changes were Landsat 5 TM (1999), Landsat 7 ETM+ (2004, 2009, and 2014), and Landsat 8 ETM+ (2018 and 2022). Global positioning system was used for ground-truthing, IDRISI Taiga software was used for image classification, and ArcGIS was used for map visualization. Four classes of Land Use and Land Cover were identified: Built-up, Meadows, Mountain/Vegetation, and Water bodies.
FINDINGS: Results revealed that built-up area increased consistently from 3494.007 hectares in 1999 to 16995.360 ha in 2022 leading to a substantial reduction in other land use and land cover. The study confirmed a burgeoning population growth from 780,000 in 1999 to 1,563,193 in 2022. This growth had a significant impact on urban land use management, consuming a large proportion of land from 3494.007 hectares to 16995.36 hectares in 1999 and 2022 respectively. Results revealed a high land consumption rate of 0.0962 and 0.0884 during 2018-2022 and 1999-2004. A high population growth rate (0.0414) was recorded during 2018-2022. These dynamics intensified the rate of land acquisition for urban development. The average value of the SDG 11.3.1 framework was 2.3 which is higher than 1, indicating that urban expansion is moving away from land use efficiency.
CONCLUSION: The paper recommended the establishment of a Growth Management Monitoring system by the state government for effective and efficient management of land resources through a spatial plan for the metropolis. This study has provided insight into the dynamics of Jos metropolitan LULC and land use efficiency management which could be useful to policymakers, urban planners, and researchers in initiating sustainable urban development strategies and inclusive structure for its planning and management.