Urban Sustainability Research Articles

Spatiotemporal analysis of urban expansion and its impact on farmlands in the central Ethiopia metropolitan area

Urban growth in sub-Saharan Africa presents significant challenges to sustainable development, food security, and environmental conservation. The rapid urban expansion and impact on agricultural land reduction in central Ethiopian metropolitan areas (Addis Ababa and Sheger city) exemplify these issues while simultaneously offering opportunities for sustainable development. This study aims to quantify and characterize the spatiotemporal dynamics of urban expansion in Addis Ababa and the surrounding Sheger city, explicitly focusing on understanding the impact of urban expansion on farmlands. The supervised random forest (RF) classification in the Google Earth Engine platform was used to prepare land use and land cover (LULC) for 1990, 2000, 2010, and 2023. The study employed an analytical framework incorporating multiple methodologies: intensity analysis at interval, categorical, and transitional levels to quantify urban growth trajectories; gradient direction and distance analyses to examine spatial expansion patterns; and Land Expansion Index (LEI) and Landscape Dynamic Typology (LDT) metrics to characterize the urban morphology and spatial dynamics of the study area. The results revealed that edge expansion is the predominant mode of urban development, primarily affecting farmlands in the eastern section. Built-up areas quadrupled between 1990 and 2023, whereas arable land declined. Intensity analysis revealed significant changes, particularly affecting farmlands. Our LDT analysis showed reduction in stable areas and increased in LULC changes from 1990 to 2023. The findings highlight the need for revised urban development strategies in Ethiopia to focus on compact and efficient growth while safeguarding agricultural lands, aligning with SDGs 2, 11, and 15 to promote balanced development that ensures urban and agricultural sustainability.

Sustainable Development in Africa: A Comprehensive Analysis of GDP, CO2 Emissions, and Socio-Economic Factors

The fight against climate change is gaining momentum, with a growing focus on reducing carbon dioxide (CO2) emissions and mitigating environmental impacts. Africa, the continent most vulnerable to global warming, faces unique challenges in this context. This study examines the long-term association among CO2 emissions, economic growth, and different socio-economic factors in 36 African countries from 1990 to 2020. Employing the Pooled Mean Group (PMG) estimator with Autoregressive Distributed Lag (ARDL) model, along with U-test and Dumitrescu and Hurlin causality analyses, our study reveals substantial long-term connections amongst CO2 emissions and factors such as economic growth, trade openness, renewable energy consumption, urbanization, and population dynamics. The findings support the Environmental Kuznets Curve (EKC) hypothesis, indicating that CO2 emissions initially increase with GDP per capita growth but begin to decline after a turning point at approximately 10,614.75 USD. However, the evidence for this turning point remains weak, suggesting that most African countries have not yet achieved decoupling. Renewable energy consumption and urbanization are negatively associated with CO2 emissions, while trade openness and GDP per capita show positive correlations. Causality analysis reveals bidirectional relationships among most variables, except for population growth and CO2 emissions, which may involve other moderating factors. The findings highlight the urgent need for integrated policies that advance sustainable development by focusing on renewable energy adoption, sustainable urbanization, and green growth strategies. Policymakers should prioritize initiatives that harmonize economic growth with environmental sustainability, ensuring a lasting balance between development and ecological preservation across Africa.

Austerity and sustainability: ‘common-sense' neoliberalism in a Finnish city

ABSTRACT The 2008 financial crisis and the subsequent austerity measures were harsh on cities. Despite receiving little academic attention, in progressive Nordic countries, such as Finland, cities faced fiscal stress and implemented austerity. As a solution to cities’ budget deficits, austerity became a widely accepted ‘common-sense' policy. During this time, the seemingly contradictory sustainability policies increased support. This article analyses how austerity and sustainability, narrated as common-sense solutions, changed the urban development policy in Tampere. The narrative analysis identifies a significant change in urban policy that occurred during the recession. At first, an ‘austerity for efficiency' narrative argued that urban development and sustainability must meet the budget and service provision should be economically efficient. During the recession, a ‘green growth' narrative began to assert that growth investments in sustainable city development could be financed with debt, while service provision must meet fiscal austerity. The city’s political elite made narrative arguments to justify downsizing the public sector while at the same time using sustainability to justify debt investments in urban development, enabling private investments. Despite containing contradictory elements, the ‘common-sense' neoliberalism of the Finnish city is to boost sustainable city development and gradually shrink the welfare state.

Informing Risk Hotspots and Critical Mitigations for Rainstorms Using Machine Learning: Evidence from 268 Chinese Cities.

Climate change is exacerbating rainstorms, increasing the risk of flooding and threatening urban sustainability, which could undermine climate action. Here, we propose a machine learning-based framework to assess heterogeneous risks and identify critical mitigation measures for rainstorms across 268 Chinese cities. Nighttime light serves as a proxy for urban functionality, and meteorological, socio-economic, and infrastructural factors are incorporated to uncover underlying impact mechanisms. The Causal Forest (CF) model identifies 150 and 250 mm monthly rainstorm totals as critical thresholds, with significant negative impacts in the risk hotspots of eastern and north-central China. Additionally, Random Forest and SHAP (RF-SHAP) analysis highlight effective mitigation strategies, including well-developed drainage and bridges, expanded road networks, and sufficient dams. The Fixed Effects (FE) model reveals that the greatest negative impacts of rainstorms occur in spring, particularly in April, followed by autumn and winter for both the 50 and 150 mm thresholds. Our results demonstrate that the three models complement and validate each other, enhancing the reliability of the estimates. This novel framework leverages machine learning model to inform evidence-based mitigation, contributing to the achievement of Sustainable Development Goals 11 and 13─building resilient cities and combating climate change.

Multi-temporal analysis of land use change using GIS and satellite imagery: Implications for sustainable urban planning

Urbanization is a significant driver of land use change, particularly in rapidly growing metropolitan areas. This research investigates Greenfield City land use change in the 20-year period (2000-2020) using GIS and satellite data. The mapping shows where the greatest land-use changes occurred, ranging from increased residential and commercial developments to the loss of agricultural fields and the omission of green space. The work applies multi-temporal analyses of Landsat satellite images taken in 2000, 2010 and 2020 to estimate land cover change and its effects on urban planning and sustainability. They indicate that theres a clear rise in housing and business developments, but also a steep decline in farming and greenspace. These transformations affect the environment, with habitat loss, biodiversity destruction and encroachment on natural resources. The paper wraps up by focusing on the issues of sustainability in urban planning and how better land use planning is required to reduce the negative environmental effects of urban sprawl.

A smart incentive-based plastic recycling system for urban sustainability: global insights from sustainable service design

A smart incentive-based plastic recycling system for urban sustainability: global insights from sustainable service design

Securing Cyber Physical Systems: Lightweight Industrial Internet of Things Authentication (LI2A) for Critical Infrastructure and Manufacturing

The increasing incorporation of Industrial Internet of Things (IIoT) devices into critical industrial operations and critical infrastructures necessitates robust security measures to safeguard confidential information and ensure dependable connectivity. Particularly in Cyber Physical Systems (CPSs), IIoT system security becomes critical as systems become more interconnected and digital. This paper introduces a novel Lightweight Industrial IoT Authentication (LI2A) method as a solution to address security concerns in the industrial sector and smart city infrastructure. Mutual authentication, authenticated message integrity, key agreement, soundness, forward secrecy, resistance to a variety of assaults, and minimal resource consumption are all features offered by LI2A. Critical to CPS operations, the approach prevents impersonation, man-in-the-middle, replay, eavesdropping, and modification assaults, according to a security study. The method proposed herein ensures the integrity of CPS networks by verifying communication reliability, identifying unauthorized message modifications, establishing a shared session key between users and IIoT devices, and periodically updating keys to ensure sustained security. A comprehensive assessment of performance takes into account each aspect of storage, communication, and computation. The communication and computing capabilities of LI2A, which are critical for the operation of CPS infrastructure, are demonstrated through comparisons with state-of-the-art systems from the literature. LI2A can be implemented in resource-constrained IIoT devices found in CPS and industrial environments, according to the results. By integrating IIoT devices into critical processes in CPS, it is possible to enhance security while also promoting urban digitalization and sustainability.

Assessing the impact of greenery on urban heat using opportunistic drive-by sensing

The urban heat island (UHI) phenomenon is recognized as a main urban sustainability problem in the face of a changing climate, affecting human health, energy consumption, and other socio-economic considerations. The UHI can be mitigated by urban greenery, but it needs further investigation of detailed impacts across the urban landscape. The aim was to study UHI and model the relation to greenery in combination with urban grey structures, at a high spatiotemporal resolution across the urban landscape, in Stockholm. Temperature data was collected through opportunistic drive-by sensors on electric three-wheeled taxis. Data on greenview and skyview factors were used to inform on greenery and building density along the roads. During night and morning hours, the surface temperature was in general higher than air temperature, indicating that some densely built-up environments stored heat overnight. Hot zones were unevenly distributed throughout the city, while greenery had a cooling effect, especially when combined with skyview as an inverse measure of building density. Our results provide information on the spatiotemporal distribution of heat that can be used to inform efforts to use greenery for mitigating impacts of UHI on urban residents.

Assessing Urban Freight Tours: A Machine Learning and Life Cycle Sustainability Assessment Approach for Logistics Management

ABSTRACTThe main aim of this study is to assess urban freight tours through integrating machine learning with the Life Cycle Sustainability Assessment (LCSA). The research captures supply chain operations using the Gradient Boosting Regressor (GBR) model with real‐time data from surveys and Global Positioning System (GPS) tracking. These predictions were analysed using LCSA to assess the sustainability impacts of Hydrogen Fuel Light Commercial Vehicles (HFLCVs) and Electric Light Commercial Vehicles (ELCVs) compared to traditional fuel‐based vehicles. HFLCVs show remarkable reductions in ecosystem and health damage by 58% and 61%, indicating substantial environmental and health benefits. Findings suggest that strategic investment in hydrogen‐fuel and electric LCVs can significantly decrease operational costs and environmental impacts, making them crucial for advancing sustainable urban logistics. This research highlights the benefits and possibilities of using an integrated data‐driven approach to achieve urban sustainability, thus creating an urgency to shift policies favouring green urban freight systems.

Development and Application of Green Building Technologies

As the global population grows, people's demand for residential land has gradually increased. A large number of people have poured into cities, resulting in an increase in various needs for resources, making the original traditional city design extremely burdened. To address this, engineers introduced the concept of smart cities, leveraging technological advancements to enhance urban sustainability and livability. This paper explores the integration of green building technologies into smart city development, aiming to optimize resource use and reduce environmental impact. The research methodology involves literature review and drawing inspiration from various scientific inventions, promoting the use of green technology in the construction of smart cities. This paper finds that green building technologies play a big role in the construction of smart cities.

Nighttime light extent and intensity explain the dynamics of human activity in coastal zones

Studying human activity in coastal areas is crucial for urban planning, sustainability, and economic development. However, there is limited evidence of ongoing monitoring of human activities in these areas. Thus, a quantitative analysis of the spatio-temporal changes, trends, and variability of Nighttime light (NTL) in the Italian Coastal Zone over the past decade (2014–2023) was conducted to assess human activity dynamics. The findings of our study indicate the following: (1) NTL increases over the years in both extent and intensity along the coastal zone; (2) NTL extent and intensity vary by season, with the coastal zone being brighter in summer; and (3) a highly heterogeneous NTL pattern was found where some locations became hot spots (significant upward trend) or cold spots (significant downward trend) while others remain unchanged. By explaining the intensification of human activity, this study can provide insight into identifying the patterns of economic development and environmental conditions contributing to more effective planning in coastal zones.

Exploring the impact of land use on bird diversity in high-density urban areas using explainable machine learning models.

Amid rapid urbanization, land use shifts in cities globally have profound effects on ecosystems and biodiversity. Birds, as a crucial component of urban biodiversity, are highly sensitive to environmental changes and often serve as indicator species for biodiversity. This study, using Shenzhen as a case study, integrates machine learning techniques with spatial statistical methods. Firstly, a multi-layer perceptron (MLP) model was employed to globally simulate bird richness based on citizen science data. Subsequently, a geographic weighted random forest (GW-RF) model was used to construct the complex relationship between bird diversity and land use. Additionally, SHAP analysis evaluates the effects of urban factors and development patterns on bird diversity. The findings reveal that anthropogenic disturbances and habitat factors significantly influence bird diversity. Furthermore, the impact of land landscape patterns on bird diversity exhibits notable spatial heterogeneity, with landscape patterns within ecological spaces and developed land showing marked differences in their effects on bird diversity. The study's findings clarify the intricate effects of urbanization on bird diversity, pinpointing specific ecological conservation areas. It underscores the importance of ecological conservation in guiding urban development, advocating for strategic restoration to bolster urban sustainability and optimize land use for the protection of ecological diversity.

Assessing Urban Heat Islands Using GIS and Remote Sensing for Sustainable Urban Planning in the Philippines

Abstract- Growing urbanization and a tropical climate intensify the known environmental challenges of urban heat islands (UHIs) in the Philippines. UHIs are formed by human activity, infrastructure, and decreased vegetation, resulting in elevated temperatures in urban areas compared to their rural surroundings. This tendency exacerbates energy consumption, air pollution, and health concerns, posing significant issues for urban planners and policymakers. Geographic Information Systems (GIS) and remote sensing technologies provide efficient methods for evaluating and reducing UHIs. GIS enables the merging and examination of geographical data, providing a comprehensive understanding of urban settings. Remote sensing uses thermal data from satellites to provide a comprehensive understanding of land surface temperatures and heat distribution patterns. In the Philippines, these technologies are essential for detecting areas with high temperatures, assessing the elements that contribute to this, and creating specific policies for sustainable urban development. By utilizing GIS and remote sensing, urban planners can strategically create geographically accurate green spaces, optimize construction materials, and apply cooling measures, ultimately fostering a healthier and more resilient urban environment. This paper shows the significant utilization of these technologies to facilitate data-driven decision-making, which is crucial for mitigating the detrimental impacts of UHIs. This research can guide environmental planners on how to utilize GIS and remote sensing for a more scientific approach as urban areas continue to grow and science-based sustainable urban planning becomes more and more apparent. Evaluating UHIs using GIS and remote sensing is an essential step in the development of habitable, sustainable, and climate-resilient cities in the Philippines.

Parallel railways and urban sustainability: a comprehensive bayesian evaluation of infrastructure impacts and land use

Parallel railways and urban sustainability: a comprehensive bayesian evaluation of infrastructure impacts and land use

Smart City 4.0 as the concept of strategically managed sustainable urbanism

Background: Smart technologies serve as a bridge between strategic business goals and sustainable development, creating a synergy among the economic, environmental, and social dimensions of business and circular urbanism. Purpose: The objective of this paper is to analyse the impact of implementing smart technologies on the economic benefits for an urban centre in a Central European Union state. Study design/methodology/approach: The research employs an econometric model to predict financial savings (30%, 40%, and 55%) resulting from the implementation of smart technologies in waste management within a selected urban centre. Findings/conclusions: The predictions confirmed the existence of a positive and growing trend in financial savings across all analysed areas, highlighting the economic benefits of smart technology adoption. Limitations/future research: The limitations of the research consist of inconsistencies in the implementation of smart technologies in waste management across different municipalities within the analysed country. Future research could expand the research sample to multiple urban centres and countries after the introduction of legislation that incentivises the uniform adoption of current smart technologies and the publication of up-to-date implementation data. This would facilitate the development of sustainable strategic plans and decisions that are tailored to both national level and local needs of individual urban centres, offering effective and long-term solutions for sustainable urban development.

Assessing the Role of Green Spaces in Enhancing Pandemic Resilience a Case Study of Jos Metropolis

The COVID-19 pandemic underscored the necessity for resilient built environments, emphasizing the role of Green Spaces in mitigating the impacts of pandemics within urban settings. This study evaluates the effectiveness of Green Spaces in fostering pandemic resilience within Jos Metropolis, Nigeria, through the lens of architectural composition within urban design. The objectives include: examining the relationship between Green Spaces of architectural composition and sustainable urban design, investigating their role in pandemic resilience, and assessing the mediating effects of Green Spaces in this context. A positivist approach was adopted, using a quantitative methodology on a sample of 384 residents, calculated with Cochran’s formula (Cochran, 1977). Findings reveal significant interconnections between architectural composition in the built environment and pandemic resilience, mediated by Green Spaces. These results highlight the necessity for robust urban planning policies prioritizing green infrastructure and active community engagement. The study recommends targeted investment in green technologies and comprehensive education initiatives to enhance urban resilience and sustainability.

Does land use change decline the regional ecosystem health maintenance? Case study in subtropical coastal region, Fuzhou, China.

Regional environmental management aims to maintain or improve regional ecosystem health (REH) and prevent its degradation over time. In the context of rapid urbanization and global sustainability over the last two decades, has land use change resulted in a deterioration of REH? By using the improved REH framework model as Pressure-Vigor-Organization-Resilience-Service (P-VOR-S), this paper proposed Regional Ecosystem Health Maintenance (REHM) as a dynamic quantitative indicator of REH, and detected REHM as well as its response to land use change in the coastal city of Fuzhou, China during 2003-2018. The results showed that: (1) During 2003-2018, the average REH gradually decreased in spite of the 62.50-67.55% area coverage of the REH "well" level. The REHM "maintenance" level covered 9764.69km2 (83.74%), while the REHM "degradation" and "improvement" covered only 1485.17km2 (12.74%) and 410.99km2 (3.52%), respectively. (2) The REHM "degradation" in Fuzhou was predominantly caused by the conversion of forest to cultivated land and cultivated land to construction land, as well as the conversion of forest and water to construction land. (3) The REHM map highlighted the degraded areas as hotspots for environmental management concerns, and the area of REHM "degradation" or "improvement" could be served as key indicator for regional environmental management and spatial land planning.

Quantifying sustainable urbanization by predictive modeling for better agricultural management: A case study in the South Asiatic Region

Global population growth and uncontrolled are creating threats to agricultural land. To address urbanization, proactive planning is required. Land use and land cover (LULC) classification maps for 2002-2022 were analyzed using remote sensing (RS) and geographic information systems (GIS) in Sahiwal, Punjab, Pakistan. Idrisi's Cellular Automata (CA)–Markov model was used to predict future scenarios. The results showed that urbanization was rapidly accelerated in large LULC changes that were unpredictable. In particular, the urbanized area increased by 234.7 km2 (91%) from 22.83 km2 in 2002 to 257.53 km2 in 2022, with a reduction of 656.05 km2 (52%), from 1252.52 km2 in 2002 to 596.47 km2 in 2022, of agriculture land. About 17.05 km2 of land was lost to urbanization; however a large portion of CA 251.75 km2 was absorbed due to careless urban growth. The CA-Markov projection revealed that from 2022 to 2042, agriculture will experience the largest net change, losing about -226.09 km2 of land. However, the projected results showed that the urban class will be expanded up to 450.23 km2 and will gain approximately 192.7 km2 in 2042. The overall findings show that it is possible to manage outcomes in a quantitative way and control haphazard and unplanned urban sprawl by putting forward a comprehensive master plan.

Urban Agriculture and Local Food Systems: A Bibliometric Analysis of Research on Sustainable Cities

Urban agriculture and local food systems are pivotal in addressing the challenges of urbanization, food insecurity, and environmental sustainability in modern cities. This study employs a bibliometric analysis to explore the intellectual landscape of research on urban agriculture and its integration into sustainable city frameworks. Using the Scopus database, this study examines publication trends, co-authorship networks, and thematic clusters to identify core research themes, key contributors, and emerging trends. The findings reveal that urban agriculture significantly contributes to food security, climate change mitigation, and community resilience, while also facing challenges such as land scarcity, soil contamination, and economic viability. Policy integration and innovative technologies, including vertical farming and hydroponics, are identified as essential for scaling urban agriculture initiatives. Despite substantial progress, research gaps remain in economic impact analysis, policy frameworks, and digital technology adoption. This study provides valuable insights for researchers, policymakers, and urban planners, emphasizing the interdisciplinary and collaborative efforts required to enhance the role of urban agriculture in sustainable urban development.

Analysis of the concerted development plan to improve user satisfaction in a local government in Arequipa

The study examines the Joint Development Plan (PDC) of José Luis Bustamante y Rivero district (2011-2021), a strategic document designed to guide the community’s integral and sustainable growth. Based on a situational analysis, four strategic axes are identified: social development, economic productivity, urban-environmental management, and institutional governance. However, the PDC shows limitations in addressing global megatrends such as digital transformation, environmental sustainability, and climate resilience. This work suggests updating the PDC by incorporating digital technologies to optimize municipal management, climate adaptation strategies, and urban sustainability measures. It also recommends using SMART indicators and fostering multisectoral partnerships to enhance its impact. Aligning the PDC with the Sustainable Development Goals (SDGs) and trends like digitization and renewable energy would enable more effective and future-oriented planning. These changes would position the district as a model of inclusive, resilient, and sustainable development.