Urban Growth Research Articles

AN INTEGRATED APPROACH TO IDENTIFY SUITABLE AREAS FOR THE LOCATION OF PUBLIC FACILITIES USING MULTI-CRITERIA ANALYSIS BASED ON GIS AND AHP IN THE CITY OF EL KHROUB, ALGERIA

Random and spontaneous urban growth is the result of massive natural population growth, as it is in all developing countries. As for our study air, it also results from the unloading of the mother city of Constantine to the satellite city of El-Khroub, which gave urbanization the power to take over its vast environment, An uneven distribution of public facilities in the city’s major districts, as well as traffic jams. This work attempted to determine the suitability of urban land for the location of public facilities in the city. It should be noted that land suitability assessment is a major factor in urban planning and management. Our land adequacy assessment is subject to the AHP model, calculating the weighting of various criteria including physical, socio-economic, environmental and urban. The final adequacy analysis revealed the proportion of land most suitable, estimated at 3.52% of the total area, covering mainly fallow land. The results of this study provide a detailed mapping of urban development potential, integrating both existing data and future projections.

Deep learning for automated encrustation detection in sewer inspection

Rapid urbanization and population growth in recent decades have placed significant pressure on urban cities to rely heavily on underground infrastructure, such as sewers and tunnels, to maintain the provision of essential services. These sewers, typically having a limited lifespan of 50 to 100 years, are prone to various forms of defects. While prior research has primarily addressed common sewer defect like crack, root intrusion, and infiltration among others, the challenge of encrustation—the formation of hard deposits within sewer systems—has received less attention. This study presents a pioneering deep-learning approach to detect encrustation in sewers by leveraging survey videos from 14 different sewers in the United Kingdom. Our work marks the first effort to develop models specifically for detecting encrustation using deep learning techniques, as previous studies have focused on other types of deposits such as settled and attached deposits. By converting the videos into sequential image frames, we subjected them to thorough analysis and several image pre-processing techniques. Our contributions include the development and comparison of different classification models using backbone CNN networks such as AlexNet, VGG16, EfficientNet, and VGG19 to classify encrustation. Notably, this study provides the first metric-based comparison of these backbone networks to identify the most effective model for encrustation detection. The results demonstrate an impressive 96 % accuracy using the deep architecture of VGG19. Beyond accuracy, this research explores the impact of data augmentation and network dropout on reducing overfitting and enhancing model performance. Additionally, we analyze the time complexities associated with training models with and without data augmentation, providing valuable insights into the efficiency of our approach.

Evaluation of cement-treated recycled concrete aggregates for sustainable pavement base/subbase construction

Rapid urbanization and population growth have caused a substantial rise in the generation of all kinds of waste globally. The use of recycled waste not only can replace the enormous volume of virgin materials used in construction but also alleviate environmental concerns by lowering landfilling loads. This study aims to evaluate the feasibility of using non-treated and cement-treated recycled concrete aggregates (RCA) in pavement base and subbase layers. A detailed study focused on the strength, durability and microstructural aspects of treated RCA. To fulfill this, experimental test program and analysis covered particle-size distribution, Los Angeles abrasion, aggregate impact value, modified Proctor compaction, unconfined compressive strength (UCS), weight loss under wet-dry cycles, and scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis. The recycled aggregates are found to show excellent physical and mechanical characteristics in terms of abrasion and aggregate impact values. Cement treatment has shown to significantly enhance the strength and durability characteristics of RCA, rendering it suitable for pavement base/subbase layer application. RCA samples treated with a cement content of 3 % and above (by weight) are found to satisfy the minimum specified unconfined compressive strength (UCS) values of 2 MPa at 7 days of curing, according to the Texas Department of Transportation (TxDOT) and Austroads guidelines for pavement base and subbase layer applications. However, a relatively higher cement contents (5 % and 7 %) is required to meet the minimum 7-days UCS criterion of 3 and 4.5 MPa for base layer applications of low- and high- volume roads, respectively, according to Indian road standards (IRC SP 72 (2015) and IRC 37(2018)). Cement-treated samples with 2 % cement or above showed minimal weight loss after 12 alternate wet-dry cycles, which was well within the maximum permissible limit (14 %) specified in various standards for stabilized materials. Additionally, microstructural investigations have clearly showed formation of hydration products corroborating the mechanism behind strength gain with time. Findings from this study provide references to promote the use of RCA in construction of pavement base and subbase layer, contributing towards the goal of net zero set by the United Nations.

Sustainable development goals, governance and assessment of the impact of urban growth on vegetation cover in Benin City, Nigeria, using land-use–land-cover change trajectories

Land-use/cover (LULC) and governance are key elements in the attainment of the Sustainable Development Goals. This study focused primarily on LULC changes in Benin City, Nigeria, from 1992 to 2022; to examine how urban growth affected vegetation cover across four time points: 1992, 2002, 2015 and 2022. Variable LULC classifications considered included: built-up areas, open spaces/bare lands, vegetations, waterbodies and wetlands. In three decades (1992–2022), increases in the built-up, open space/bare land and wetland LULC were observed and attributed to population increases and higher infrastructural demands whereas evident reductions in the sizes of vegetation and waterbody categories were ascribed to anthropogenic activities and climate events. The average annual rates of change in the built-up and vegetation LULC increased (7.28%) and decreased (−3.02%), respectively, between 1992 and 2022; with the built-up area experiencing a 218% increase from 6493 to 20,672 (km2) whereas vegetation decreased by 90% from 23,445 to 2239 (km2). The corollary is that urban growth, exemplified by the built-up LULC, was progressive while vegetation cover was depleted, in the 30-year period. Changes in five other periods were also interrogated. Government and stakeholders-promoted afforestation and agroforestry programs are recommended as plausible solutions to check vegetation-cover depletion. Other solutions proffered include the support of relevant farmers’ trainings in climate-smart and hydroponic agriculture, and the application of sustainable farming techniques. Policymakers and estate developers/managers should encourage sustainable land governance and cities with resilience and coping capacities; to tackle the problem of climate change, with high emphasis on green area developments.

Urban growth and spatial segregation increase disaster risk: lessons learned from the 2023 disaster on the North Coast of São Paulo, Brazil

Urban growth and spatial segregation increase disaster risk: lessons learned from the 2023 disaster on the North Coast of São Paulo, Brazil

Empirical Analysis on the Mechanism of Industrial Park Driving Urban Expansion: A Case Study of Xining City

Taking Xining City as an example, this article analyzes the mechanism by which industrial park construction drives the expansion of urban population size and built-up area, based on a review of the process of industrial park development and urban population growth. It also discusses future urban governance models in light of urban development trends. The research finds: (1) In the process of urban development, industrial park construction is often the initial factor in the cumulative and cyclical development of a city; (2) As the level of development improves and the mode of economic growth changes, the government should timely adjust its strategies, shifting from the expansion of industrial park construction towards structural optimization and quality improvement. The most significant difference from previous research is that this paper emphasizes the importance of government planning. This study can not only demonstrate the general process of industrial parks promoting urban expansion, but more importantly, it explains the fundamental reasons for the transition of urban expansion to adjustment from a mechanism perspective, thereby eliminating the drawbacks of simply predicting urban scale evolution through data models.

Green Infrastructure as a Sustainability Strategy for Biodiversity Preservation: The Case Study of Pantanos de Villa, Lima, Peru

Currently, the lack of adequate spaces for raising awareness among the population, coupled with disorderly urban growth, has led to an increase in water pollution from solid waste and the disruption of natural habitats in Villa Marshes. Therefore, this research focuses on implementing green corridors for the study of birdlife and environmental education, aiming to raise awareness about the importance of preserving this ecosystem. Various methodologies were employed, including climate analysis, characterization of flora and fauna, and bioclimatic design strategies supported by specialized software. The feasibility of this proposal was compared with other similar projects, emphasizing community importance. As a result, a network of green corridors was designed, including environmental education and visitor centers, along with the implementation of renewable energies to enhance energy efficiency. The main conclusion is that integrating renewable energies into the conservation of Villa Marshes offers a unique opportunity to promote a balance between human development and environmental protection.

Tasks of visual crowd analysis in intelligent video surveillance systems

Modern urban population growth creates challenges for public safety, in particular due to crowds. This stimulates the development of new crowd management methods that require automated analysis. Visual crowd analysis based on computer vision technologies is a key tool for solving these problems. The development of deep learning has significantly improved the monitoring systems used for urban surveillance, social distancing control, transportation and event management. However, crowd analysis remains challenging due to occlusions, scale variations, unpredictable movement patterns, and complex behavior. To overcome these challenges, new algorithms, models, and large-scale datasets are needed to enable real-time analysis. The main tasks include people counting, object detection, motion analysis, behavior recognition, and anomaly detection. Deep neural networks and transfer learning significantly increase the accuracy and adaptability of such systems, which helps to improve public safety and manage the flow of people.

The Practice of Urban Planning In Managing Urban Expansion: The Case of Level-I Towns in Southern Ethiopia

The world’s urbanization continues to grow rapidly occurring in developing regions. The rapid pace of urbanization without equivalent economic growth causes uneven spatial dispersion, land speculation, urban sprawl, ecological damage, and socio-cultural chaos. Urban planning is a key tool in managing such urbanization and particularly urban expansion challenges through several strategies. The objective of this study is to evaluate the practice of urban planning in managing urban expansion by applying both quantitative and qualitative research approaches. The first-hand data was collected by a structured questionnaire survey, interview, and physical observation, whereas secondary data was analyzed from spatial and non-spatial data of the study towns, national urban policy and strategy documents, and the national urban development spatial plan. Descriptive analysis, principal factor analysis, spatial trend analysis, and content analysis techniques were applied with the help of the SPSS and GIS analysis tools to reach the findings. The practices of urban planning in managing the urban expansion of the study town were evaluated on the basis of factors including urban spatial growth management, community engagement, economic change, and peri-urban communities’ understanding of urban planning. The major findings indicated that these variables are poorly practical, and their failure has been collectively posing significant obstacles to the effectiveness of urban planning. This implies that the urban planning practice in managing urban expansion was insignificant in the study towns. Therefore, it is best to use the alternative expansion area planning strategy, that promotes planned spatial growth, community inclusivity, mixed economic activity, environmental sustainability, and the community’s awareness of expansion areas.

A U-Net Model for Urban Land Cover Classification Using VHR Satellite Images

Urban settings are dynamic, constantly changing, and presenting a wide range of surface materials with high diversity in both spatial and spectral variation. As a result, mapping urban growth, evaluating infrastructure, managing water resources, and monitoring natural land cover become more complex tasks. Urban applications have made considerable progress thanks to the abundance of VHR orbital data and the recent development of artificial intelligence strategies especially neural networks. Convolutional neural networks have the potential to significantly enhance the analysis of urban land cover by addressing the limitations of traditional techniques. U-Net is a popular neural network for land cover analysis in remote sensing images. The current research presents a CNN model employing U-Net for image semantic segmentation in urban study area using both spectral and spatial context of VHR satellite data. The proposed model is trained, validated, and tested for VHR satellite image classification into five urban classes: water, vegetation, bare soil, road, and building. The CNN semantic segmentation results are compared to maximum likelihood image classification outcomes for validation and stability evaluation. A confusion matrix is applied to the classified scenes to determine the overall accuracy, producer's and user's accuracy, and Kappa coefficient using 400 random points with their corresponding ground truth. The U-Net image semantic segmentation technique achieved an overall accuracy of 87.50% and Kappa coefficient of 0.8395 which outperforms the maximum likelihood classification method with an overall accuracy of 83.25% and Kappa coefficient of 0.7812.

Urban growth and waste services: exploring scenarios in an inter-municipal cooperative framework in Sogamoso city, Colombia

ABSTRACT The spatial dimensions of city expansion in Latin America reveal the emergence of new urban agglomeration and metropolization phenomena. In this context, the goal is to implement a predictive model of land use change between 1976 and 2047 in the city of Sogamoso and neighboring municipalities in Colombia and to apply its results to a proposal for inter-municipal cooperation in the collection of solid household waste. The methodology used is based on a spatially explicit models using the CA_Markov model in Idrisi Selva software that incorporates Markov chains, multi-criteria evaluation, and cellular automata to identify future areas of urban expansion. The model forecasts urban growth from 2,420 ha in 2021 to 5,278 ha in 2047. The spatial distribution of the new urban areas implies collection routes that are ever farther away from the main urban centers. There is thus a vital need for new regional planning practices (such as inter-municipal cooperation).

Horizontal ecological compensation and urban inclusive green growth: evidence from China.

Horizontal ecological compensation (HEC) has the potential to incentivize inclusive green growth in cities. Using the multi-stage difference-in-differences (DID) method, this study examines the impact of HEC policies as a quasi-natural experiment. Panel data are analyzed; the data pertain to 87 cities in the Yangtze River Basin, from 2007 to 2020. The findings indicate that HEC policies significantly contribute to inclusive green growth, with consistent effects across different estimators. The moderating effect test reveals that urban industrial pollution levels and green innovation are key pathways through which HEC policies influence inclusive green growth. Further analysis shows that the positive impact of HEC is more pronounced in watersheds with high marketization and in downstream regions, suggesting that HEC may exacerbate regional disparities in inclusive green growth. This study offers insights for China and also for other developing countries seeking to promote urban inclusive green growth and achieve sustainable development goals.

Spatially Explicit Analysis of Landscape Structures, Urban Growth, and Economic Dynamics in Metropolitan Regions

Assuming that settlement morphologies and landscape structures are the result of economic transformations, the present study illustrates a statistical framework investigating metropolitan growth due to the inherent changes in landscape configurations vis à vis socio-demographic functions. Focusing on the evolution of their spatial drivers over time, metropolitan development was studied by adopting land parcels (or ‘patches’, as they are referred to in the ecological literature) as the elementary analysis unit—with the individual surface area and a specific shape indicator as the dependent variables and background socioeconomic attributes as predictors of landscape change over time. We specifically ran a Multiscale Geographically Weighted Regression (MGWR) testing the spatial dependence of the size and shape of landscape parcels on a vast ensemble of socioeconomic factors in a dense region (metropolitan Athens, Greece) with natural landscapes exposed to increasing human pressure. To investigate the spatial direction and intensity of the settlement expansion and landscape change, local regressions using the parcel area and fractal index (perimeter-to-area ratio) as the dependent variables and the elevation, distance from selected economic nodes, transport infrastructures, and natural amenities as the predictors were run separately for 1990 and 2018, representative of, respectively, a mono-centric configuration and a moderately polycentric organization of economic spaces. In a strictly mono-centric setting (1990), the parcel size showed a linear dependence on the distance from business districts, elevation, and wealth. Changes in the relationship between the parcel size and spatial (economic and non-economic) drivers may suggest a latent process of settlement de-concentration, and a possible shift toward polycentric development (2018), as documented in earlier studies. By integrating socioeconomic and ecological dimensions of landscape analysis and land evaluation, the empirical results of this study outline the increased complexity of dispersed landscape structures within dense metropolitan regions and along urban–rural gradients in Europe.

Navigating Urban Sustainability: Urban Planning and the Predictive Analysis of Busan’s Green Area Dynamics Using the CA-ANN Model

While numerous studies have employed deep learning and high-resolution remote sensing to predict future land use and land cover (LULC) changes, no study has integrated these predictive tools with the current urban planning context to find a potential issues for sustainability. This study addresses this gap by examining the planning context of Busan Metropolitan City (BMC) and analyzing the paradoxical objectives within the city’s 2040 Master Plan and the subordinate 2030 Busan Master Plan for Parks and Greenbelts. Although the plans advocate for increased green areas to enhance urban sustainability and social wellbeing, they simultaneously support policies that may lead to a reduction in these areas due to urban development. Using the CA-ANN model in the MOLUSCE plugin, a deep learning-based LULC change analysis, we forecast further urban expansion and continued shrinkage of natural green areas. During 1980–2010, Busan Metropolitan City (BMC) underwent high-speed urban expansion, wherein the urbanized areas almost doubled and agricultural lands and green areas, including forests and grassland, reduced considerably. Forecasts for the years 2010–2040 show continued further expansion of urban areas at the expense of areas for agriculture and green areas, including forest and grasslands. Given the master plans, these highlight a critical tension between urban growth and sustainability. Despite the push for more green spaces, the replacement of natural landscapes with artificial parks and green areas may threaten long-term sustainability. In view of these apparently conflicting goals, the urban planning framework for BMC would have to take up increasingly stronger conservation policies and adaptive planning practices that consider environmental preservation on a par with economic development in the light of the planning context and trajectory of urbanization.

Development of an Urban Growth Model Using Geographical Information System in Malaysia: A Review

Urbanization is one of the major problems faced by various countries over time. The process by which rural regions transform into cities and people move from rural to urban areas is known as urbanization. Urban land use development is influenced by a variety of factors, including physical, socioeconomic, and environmental issues. While urbanization benefits many stakeholders by enhancing social, economic, and infrastructure aspects, it also poses risks to people's safety and harms the physical, social, and cultural landscape as more buildings are constructed. Consequently, spatial models for urban growth are often used in planning to develop strategies for controlling land use actions, such as GIS, GIS-based remote sensing, CA-Markov, AHP, and MCE. GIS and CA-Markov are among the models widely employed by researchers to simulate land use change. Malaysia also tends to utilize urban growth models as part of its efforts to plan for sustainable cities in the future. Therefore, this study was conducted to assess and review the use of GIS in developing an urban growth model in the Malaysian context. The results indicate that GIS and other models or techniques can serve as a strategic framework for urban development policy.

Practices and determinants of urban land governance in Sheger City, Ethiopia

While there have been numerous global discussions on urban land governance, a lot remains to be done and serious urban land related obstacles remain to be overcome. This article identifies the most important governance principles for improving land governance for urban development and growth. The governance principles assessed in this study include participation, responsiveness, efficiency, openness, rule of law, rule of ethics, completeness, innovation, sustainability, sound financial management, sound human rights and accountability. Source of primary data is 458 respondents selected using a multi-stage cluster sampling method from the six sub cities and secondary data was collected from policy documents and regional government reports. The governance level is measured by using seven point likert scale and the results reveal that the status of land governance in Sheger City is lower (3.445) than the average level which is 3.5 (50%). Out of the twelve independent variables, the mean score of only four, meaning innovation and openness to change (3.74), openness and transparency (3.68), competence and capacity (3.51), and rule of law (3.52), is more than 50%. The remaining eight variables are below the average, indicating poor land governance in Sheger City. Regarding the determinants, 76.21% of the variation in land governance in Sheger city is explained by the model applied. The highest beta value is registered for responsiveness, and the next highest is for innovation and openness to change. These findings have important implications for policymakers and urban planners in Ethiopia, highlighting the need for continued efforts to improve urban good governance and land management practices to ensure sustainable and equitable urban development.

When market access gains do not spur urban growth

Abstract We revisit the natural experiments of division and unification of Germany. The negative shock to local market access following the division of Germany led to a fast and strong downward adjustment of the size of West German cities near the new border. In contrast, the positive shock of reunification did not lead to any change in their relative size. Even three decades after reunification, no convergence can be observed. We show that local subsidies to East Germany could have contributed to this asymmetry in time.

Assessment of Land Subsidence Pattern in Pokhara Valley Using Sentinel-1 InSAR Processing

This research examines the use of Sentinel-1's enhanced remote method and Interferometric Synthetic Aperture Radar (InSAR) processing to monitor ground subsidence in Pokhara Valley City, Nepal. It aims to comprehend the reciprocal effects of land sinking on environmental sustainability, infrastructure stability, and urban growth. The methodology encompasses the acquisition and processing of Sentinel-1 SAR data, along with rigorous interferometric analysis to detect and quantify ground deformation. Spanning from 2019 to 2022 AD and, -analyzing annual displacement trends, initially, a subsiding trend was observed in 2019-20 AD with an average rate of 0.037 m/year followed by 0.072 m/year in 2020-21 AD, and then escalating to 0.165 m/year in 2021-22 AD. These fluctuations in rates illustrate the intricate interplay of urbanization and geological dynamics affecting land stability in the region. The implications of this study extend to urban planning and infrastructure management, emphasizing the necessity of integrating land subsidence monitoring into the developmental policies and strategies of Pokhara Valley. Additionally, the potential of Sentinel-1 InSAR as a valuable tool for geotechnical investigations offers a non-invasive, cost-effective means to assess and monitor ground deformation risks. By leveraging the capabilities of Sentinel-1 InSAR, the study contributes to the body of knowledge in geotechnical and civil engineering fields, particularly within the context of sustainable urban planning and disaster risk reduction.

The Impacts of Urban Population Growth and Shrinkage on the Urban Land Use Efficiency: A Case Study of the Northeastern Region of China

In the context of rapid urbanization, urban population differentiation has become increasingly pronounced. Regional development strategies based on growth scenarios often lead to continuous expansion, regardless of urban population status. Such “one-size-fits-all” models exacerbate resource waste and negatively impact urban land use efficiency (ULUE). This study aims to explore the mechanisms by which urban population growth and shrinkage (UPGS) affect ULUE, with the goal of enhancing ULUE and promoting sustainable urban development. We analyzed 34 prefecture-level cities in China’s three northeastern provinces. First, we identified UPGS using population data. We then employed a three-stage SBM-DEA model to measure ULUE from 2000 to 2020. Spatial analysis methods were used to examine the spatiotemporal characteristics and correlations between UPGS and ULUE. Additionally, mediating effect models and spatial Durbin models were utilized to empirically test the impact processes, mechanisms, and spatial heterogeneity. Our findings reveal that: (1) Over the past 20 years, urban population shrinkage in northeastern China has intensified, and significant regional disparities in urban development are evident. (2) Population growth positively influences ULUE, while population shrinkage inhibits its improvement. (3) Economic development, technological innovation, and industrial structure upgrading are key factors in enhancing ULUE in this region, while the impact of public services on ULUE varies significantly at different stages of urban development. (4) Economic development, technological innovation, and industrial structure upgrading exhibit spatial spillover effects, whereas public services are constrained by regional limitations, resulting in minimal spatial spillover effects. To foster coordinated regional development, this study proposes policy recommendations, including strengthening support for resource-dependent cities, optimizing the allocation of public resources, and promoting technological innovation and industrial diversification.

Sustainable development and environmental protection in the Absheron peninsula: a geo-ecological perspective

The research focuses on the ecological and geographical aspects of the Absheron region in Azerbaijan, highlighting the significant environmental challenges and the need for sustainable resource management. Given the region’s rapid economic development and urbanization, there is a crucial need to balance economic growth with environmental conservation to ensure long-term ecological stability. The Absheron region faces numerous environmental issues due to intensive industrial activities, particularly in the oil and gas sectors, and increasing urbanization. These activities have led to significant anthropogenic impacts, necessitating comprehensive studies to assess and mitigate their effects on the natural environment. The article’s primary aim is to analyze the current dynamics of economic progress in the Absheron peninsula, assess the anthropogenic impacts, and identify efficient strategies for environmental management. The study also aims to provide a comprehensive ecological survey of the region, focusing on sustainable green economic practices. There has been significant urban growth in cities like Baku, Sumgayit, and Khyrdalan, contributing to increased environmental pressure. Modern settlements and infrastructure development have played a crucial role in organizing advanced systems for economic purposes. The economic activities, particularly in the oil sector, have significantly impacted the region’s natural complexes, necessitating the implementation of green economy principles. Effective management practices are essential to prevent pollution, maintain ecological balance, and protect natural resources. The study highlights the importance of greening initiatives and emergency response plans to manage environmental risks. The author emphasizes the need for a balanced approach to economic development and environmental conservation in the Absheron region. The study provides valuable insights into the ecological and geographical challenges of the Absheron region and offers practical solutions for achieving sustainable development. The article outlines the potential of geographic information systems and remote sensing technologies in monitoring and managing environmental change, in particular, in assessing the impact of industrial activity and urban expansion. The results of the study indicate the need for a comprehensive policy that combines economic development goals with environmental protection measures to ensure long-term environmental sustainability and economic prosperity in the Absheron Peninsula.