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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. Full article

Discovering the Representative places (RPs) of a city will benefit the understanding of local culture and help to improve life experiences. Previous studies have been limited in regard to the large-scale spatial identification of RPs due to the vagueness of boundaries and the lack of appropriate data sources and efficient tools. Furthermore, human perception of these places remains unclear. To address this gap, this research adopts a novel approach to identify and evaluate the RPs of a city from the perspective of human perception. Our methodology involves the utilization of deep learning systems, text semantic analysis, and other techniques to integrate multi-source data, including points of interest (POIs), street view images, and social media data. Taking Nanjing, China, as a case, we identified 192 RPs and their perceptual ranges (PRRPs). The results show the following: (1) Comparing RPs to non-RPs, RPs show higher average scores across four perceptual dimensions (positive indicators): Beautiful (7.11% higher), Lively (34.23% higher), Safety (28.42% higher), and Wealthy (28.26% higher). Conversely, RPs exhibit lower average scores in two perceptual dimensions (negative indicators): Boring (79.04% lower) and Depressing (20.35% lower). (2) Across various perceptual dimensions, RPs have utilized 15.13% of the land area to effectively cover approximately 50% of human perceptual hotspots and cold spots. (3) The RPs exhibit significant variations across different types, levels, and human preferences. These results demonstrate the positive perceived effects that RPs have, providing valuable insights to support urban management, the transformation of the built environment, and the promotion of sustainable urban development, and provide guidance for urban planners and designers to make improvements in urban design and planning to make these sites more attractive. Full article

With the rapid development of the world economy, pollution of urban and rural ecological environments and the decline in anti-risk capabilities are becoming more serious. In order to promote sustainable improvement of urban and rural ecological resilience, based on previous independent research on urban and rural resilience, this paper combines the two to carry out collaborative development research. The dynamic evolution and driving force heterogeneity in the coordinated development level of urban and rural ecological resilience in Yunnan Province in China from 2013 to 2022 were studied using the coordination degree model of composite system and geographical detector. The results show the following: (1) The urban and rural ecological resilience levels in Yunnan Province increased annually, but urban ecological resilience (0.178) lagged behind that of rural areas (0.376). Compared to rural areas, the overall spatial difference in urban ecological resilience level is significant. (2) The overall level of urban–rural ecological resilience synergy in Yunnan Province has been increasing annually, from “no synergy” to “primary synergy”. However, there are great differences between prefectures and cities. (3) The combination of urban and rural driving factors is more conducive to improving urban–rural ecological resilience. The interaction between the per capita water supply and fertilizer consumption is the primary and critical driving factor. In the future, we will continue to take the coordinated development of urban and rural ecological resilience as the theme, further expand the research field, and carry out future development trend prediction research. This study provides new ideas for the construction of ecological resilience in similar countries and regions worldwide. Full article

Vegetation exerts a significant cooling effect, particularly during the hot summer; however, the spatial scale effects and gender difference among occupants’ subjective thermal comfort remain elusive. Developing a comprehensive model to elucidate the multidimensional relationship between green spaces and thermal experience holds paramount importance. Taking Longzi River Park in Zhengzhou city as a case study, this research examined the influence of vegetation on thermal experience by using structural equation modeling (SEM) from perspectives of fitting scale and gender disparities. It was found that (1) The vegetation environment not only influences thermal sensation, comfort and demand independently, but also influences the pathway between them. These influence paths constitute a complex causal network, functioning as a framework of “sensation → comfort → demand” and its influencing factors. (2) There exists a scaling effect in the pathway framework, which conforms to a threshold of 10 m for the inner radius and 30 m for the outer radius. The goodness of SEM model fit declines with the increase in either the inner radius or the outer radius, or both. (3) Differences in genders are exhibited for the pathway framework, with the vegetation exerting a stronger influence on female sensation and comfort, as well as male demand. The pathway from sensation to comfort to demand is more pronounced in male populations. The research findings contribute to the development of improved and sustainable vegetation distribution in urban parks. Full article

The presented paper examines the integration of Artificial Intelligence (AI) in the management of smart cities, focusing on the Silesian and Lesser Poland Voivodships in Poland. This research addresses a notable gap in the analysis of regional AI strategies within urban management, providing a comparative analysis of AI implementation in these two distinct regions. The Silesian Voivodship, with its emphasis on traditional industries such as manufacturing and energy, contrasts with the broader approach of the Lesser Poland Voivodship, which includes applications in life sciences and ICT. The paper explores how AI technologies enhance urban efficiency, sustainability, and livability through practical applications in traffic management, healthcare, energy efficiency, and environmental management. It highlights the importance of a human-centric approach in smart city development, emphasizing inclusivity, transparency, and ethical considerations. The paper also delves into the socio-technical dynamics of AI deployment, illustrating how these technologies can transform urban environments while ensuring that the benefits are equitably distributed and that urban developments are sustainable and resilient. By analyzing specific case studies, the authors aim to provide empirical evidence and insights that contribute to the academic and practical understanding of AI’s role in smart cities, ultimately advocating for the design of AI applications that prioritize human well-being and environmental health. Full article

The 47.8 km long Line 9 of the Barcelona Metro is one of Europe’s longest urban metro lines. Its southern section connects the city to the airport, being entirely excavated through soft deltaic deposits, promoting more sustainable mobility by reducing significant road traffic. This study identifies the most accurate method for predicting surface settlements caused by tunnel excavation using ground movement monitoring data. Several methodologies were assessed, with the Mean Absolute Error (MAE) and Mean Relative Error (MRE) calculated to evaluate their performances. The methods considered were Peck’s Gaussian curve method, Sagaseta’s method, and Verruijt and Booker’s method, with MAE values of 0.66 mm, 0.50 mm, and 0.48 mm and MRE values of 49%, 45%, and 36%, respectively. Verruijt and Booker’s method proved the most effective for predicting settlement, minimising surface impacts, improving building sustainability, and reducing environmental contamination from chemical injections. A sensitivity analysis was also conducted by comparing the monitoring data from Line 9 with data from 45 other tunnels excavated worldwide in deltaic soils. This analysis aimed to develop rapid predictive models applicable to different locations. The methodologies proposed for estimating ground settlements relied on specific parameters, particularly the K value, which was consistent across all deltaic soil locations, with values ranging from 0.45 to 0.55. Full article

Oasis cities are central to the economic and social development as well as ecological sustainability in the arid region in Northwest China. This study aims to explore the balance between river health and human well-being of local residents in the Hexi River oasis, while also enhancing the effectiveness of water resource management within the basin. Utilizing the SMI-P method, we construct a ‘Happy River’ evaluation system that integrates goals, criteria, and indicators. We analyze the evaluation index system for ‘Happy River’ construction in the study area, specifically the Zhangye City section of the Heihe River Basin, and derive a comprehensive evaluation value for the ‘Happy River’ initiative. Additionally, we assess the fit attribute of the evaluation system using the coupled coordination degree model and harmony degree theory, thereby enhancing the rationality of the evaluation method and ensuring a more thorough examination process. The results indicate that from 2017 to 2021, the urban wastewater treatment rate and the degree of water quality excellence in the Zhangye City section of the Black River Basin represent the highest and lowest weights, respectively, within the evaluation system. This suggests that improving the quality of the urban water environment has emerged as the primary factor influencing the assessment of the Happy River during the construction of the Happy River and Happy Lake. Moreover, ecological health is identified as the most significant criterion in the evaluation system, serving as the main factor affecting residents’ perceptions of happiness related to rivers and lakes. Over the five-year period, the happiness level in the study area improved from “relatively happy” to “very happy”, while the coupling coordination degree increased from 0.605 to 0.687, indicating a gradual progression toward coordinated development. Simultaneously, the harmony degree rose from 0.527 to 0.601, suggesting a tendency towards a condition of basic harmony. Additionally, the happiness index increased from 76.71 to 81.97, transitioning from a state of happiness to one of very high happiness. The composite index also improved, rising from 0.459 to 0.526, which demonstrates the preliminary success of the ‘Happy River’ construction efforts in the study area. The evaluation system and model of the ‘Happy River’, along with the final results of this study, can serve as theoretical references for the development of similar initiatives in typical characteristic rivers within the arid region of Northwest China. Full article

Terrestrial ecosystems play a critical role in the global carbon cycle, and their carbon sequestration capacity is vital for mitigating the impacts of climate change. Changes in land use and land cover (LULC) dynamics significantly alter this capacity. This study scrutinizes the LULC evolution within the Beijing metropolitan region from 1992 to 2022, evaluating its implications for ecosystem carbon storage. It also employs the Patch-Generating Land Use Simulation (PLUS) model to simulate LULC patterns under four scenarios for 2035: an Uncontrolled Scenario (UCS), a Natural Evolution Scenario (NES), a Strict Control Scenario (SCS), and a Reforestation and Wetland Expansion Scenario (RWES). The InVEST model is concurrently used to assess and forecast ecosystem carbon storage under each scenario. Key insights from the study are as follows: (1) from 1992 to 2022, Beijing’s LULC exhibited a phased developmental trajectory, marked by an expansion of urban and forested areas at the expense of agricultural land; (2) concurrently, the region’s ecosystem carbon storage displayed a fluctuating trend, peaking initially before declining, with higher storage in the northwest and lower in the central urban zones; (3) by 2035, ecosystem carbon storage is projected to decrease by 1.41 Megatons under the UCS, decrease by 0.097 Megatons under the NES, increase by 1.70 Megatons under the SCS, and increase by 11.97 Megatons under the RWES; and (4) the study underscores the efficacy of policies curtailing construction land expansion in Beijing, advocating for sustained urban growth constraints and intensified afforestation initiatives. This research reveals significant changes in urban land use types and the mechanisms propelling these shifts, offering a scientific basis for comprehending LULC transformations in Beijing and their ramifications for ecosystem carbon storage. It further provides policymakers with substantial insights for the development of strategic environmental and urban planning initiatives. Full article

The contradiction between ecological resource protection and urban sprawl in urban agglomeration areas is becoming more and more prominent, facing a serious imbalance between the supply and demand of ecosystem services. To analyze the impact of urban agglomeration expansion on regional ecosystem services, based on multi-source data, an assessment model of supply and demand of ecosystem services for water conservation, carbon sequestration, soil conservation and crop production was constructed. With the help of value transformation model and spatial analysis method, this paper explores the risk of ecosystem service supply and demand imbalance faced by the Yangtze River Delta urban agglomeration in the process of expansion. This study found that the supply capacity of ecosystem services in the YRDUA has continued to decline at the spatial pixel scale; ecosystem service value deficits are a common problem in the YRDUA, with cities around Taihu Lake, such as Shanghai and Suzhou, being the most serious; the value surplus areas are concentrated in the southern cities, such as Xuancheng and Chizhou, but the balance between the supply of and demand for ecosystem services in these cities is also facing a challenge as the cities are expanding. This study analyzed the spatial pattern changes in the Yangtze River Delta region in the context of urban sprawl from the perspective of ecosystem service supply and demand, which helps to clarify the changing ecosystem service dynamics of the region and guide the formulation of urban planning policies and to achieve a balance between ecological supply and demand as well as sustainable development. Full article

Sustainable growth relies on common prosperity, which is reflected in increasing total income and equitable income distribution. This study first proposes the theoretical mechanisms by which digital financial development affects residents’ total income and income distribution. After that, a two-stage generalized method of moments estimation model with endogeneity treatment is constructed to investigate the impact of digital finance on residents’ total income in 31 Chinese provinces. Moreover, Moran’s I and a spatial autoregression model are used to explore the impact of digital finance on residents’ income distribution. The results demonstrate that digital financial development can significantly contribute to the increase in residents’ total income in both urban and rural areas, thus contributing to regional sustainable wealth growth. In addition, digital finance has a spatial direct effect and a spatial spillover effect on the optimization of residents’ income distribution. This indicates that a region’s digital financial development benefits regional sustainable wealth growth, as it not only can improve residents’ income distribution within the same region but also can promote the income distribution of neighboring regions. Full article

Economic development often results in significant greenhouse gas emissions, contributing to global climate change, which demands immediate attention. Despite implementing various low-carbon policies to promote sustainable economic and environmental progress, current evaluations reveal limitations and deficiencies. Therefore, this study utilizes a dataset detailing policy intensity at a prefecture-level city in China to investigate the impacts of these policies on carbon emission reduction from 2007 to 2022 in 334 prefecture-level cities, employing a fixed-effects model. Additionally, it assesses the policies’ efficacy. The findings indicate a significant negative correlation between China’s low-carbon policies and carbon emissions, supported robustly by multiple tests. Specifically, a one-unit increase in China’s policy intensity correlates with a 0.53-unit reduction in carbon emissions. Furthermore, the heterogeneity analysis shows that variations in urban agglomerations, environmental resource endowments, pollution levels, and low-carbon policy intensities influence the effectiveness of these policies in reducing carbon emissions. This analysis underscores that policy intensity achieves emission reductions through technological innovation, industrial transformation, welfare crowding out, and pollution transfer, with varying impacts across different environmental contexts, pollution levels, and policy intensities. Based on this analysis, we recommend several policies: formulating low-carbon strategies tailored to local conditions, enhancing regional low-carbon policies, establishing cross-regional coordination mechanisms, and so on. These recommendations not only offer valuable policy insights for China but also serve as useful references for the green and sustainable development of other developing countries. Full article

Understanding the travel patterns of university campus visitors is crucial for developing effective transportation strategies. Existing research predominantly focuses on student commuting within specific regions, often overlooking the diverse needs of faculty and staff and varying campus contexts. This study addresses a significant gap in the literature by investigating travel behaviors at Beirut Arab University (BAU), which has not been previously studied in this context. BAU’s unique situation, with campuses in both urban and rural zones, presents distinct transportation challenges, particularly for those traveling between these areas. Through a comprehensive survey of students, faculty, and staff, this research explores differences in transportation modes, travel distances, durations, and patterns. Statistical techniques, including one-way analysis of variance (ANOVA), Chi-Squared, and McNemar-Bowker tests, reveal significant variations among traveler groups. The findings highlight specific needs, such as improvements in bus services, car-sharing programs, and parking facilities, essential for creating sustainable campus environments. By examining these travel behaviors, the study offers valuable insights into the complexities of campus transportation, contributing new perspectives to the field. The originality of this research lies in its focus on an underexplored area, providing a deeper understanding of how diverse university environments impact transportation choices. This work not only fills a critical void in campus transportation research but also offers practical recommendations for enhancing transportation systems in similar settings. Full article

Land use/cover change (LUCC) can either enhance the areal carbon reserve capacity or exacerbate carbon emission issues, thereby significantly influencing global climate change. Comprehending the impact of LUCC on regional carbon reserve variation holds great significance for regional ecosystem preservation and socioeconomic sustainable development. This study focuses on Liaoning Province, leveraging land use remote sensing data from three periods from 2000 to 2020, natural environmental data and socioeconomic data in conjunction with the Integrated Valuation of Environmental Services and Trade-offs (InVEST) model, and patch-generating land use simulation (PLUS) models. It analyzes the interactive relationship between LUCC and carbon reserves in Liaoning Province between 2000 and 2020 and forecasts the trajectory of carbon reserve changes in Liaoning Province under various scenarios: business as usual, urban development, cropland protection, and ecological protection, all based on LUCC simulations. The findings indicate the following: (1) Over the study period, Liaoning Province experienced significant LUCC characterized primarily by the transformation of farmland to built-up land. Carbon reserves initially declined and later increased due to LUCC changes, resulting in a cumulative increase of 30.52 Tg C. The spatial distribution of carbon reserves was influenced by LUCC, displaying a pattern of spatial aggregation, with higher values in the east and lower values in the west. (2) Across the four simulation scenarios, the spatial pattern of carbon reserves in Liaoning Province continued to exhibit the characteristic spatial aggregation of higher values in the east and lower values in the west. Under the urban development scenario, carbon reserves decreased by 34.56 Tg C tons, representing a 2.45% decrease compared to 2020. Conversely, under the business-as-usual, cultivated land protection, and ecological protection scenarios, carbon reserves displayed a growing tendency, reaching 1449.35 Tg C, 1450.39 Tg C, and 1471.80 Tg C, respectively, with changes of 0.09%, 0.16% and 1.63% compared to 2020. The substantial increase in carbon reserves under the ecological protection scenario primarily stemmed from the significant expansion of woodland and other ecological land areas. In light of these findings, Liaoning Province may consider laying down and strictly executing spatial policies for ecological protection in future land projecting. The PLUS model and InVEST model can help curb the uncontrolled expansion of built-up land, facilitate the increment of ecological land areas, and with effect augment carbon reserves, thereby ensuring the achievement of the “double carbon” target of carbon peak and carbon neutralization. Full article

The public sector literature on sustainability management accounting (SMA) has grown significantly in recent years, with numerous theoretical and empirical studies examining the purported link between management accounting and corporate sustainability within organisations. However, despite this surge, prior studies have largely confined their analytical scope to traditional SMA issues, such as corporate social, environmental, and governance responsibilities. Their analyses have predominantly concentrated on largely investigated elements such as situational linkages, transformational dynamics, agency issues, resistance, and conflicts. This study aims to address these limitations by examining corporate SMA systems within the burgeoning field of urban development. It utilises institutional theory and a case study from Egypt, a developing country, to explore how urban development could impact adopting a corporate SMA system in politically sensitive state-owned enterprises (SOEs). Contrary to existing literature, the findings indicate that urban development has created financial pressures for national governments, which have used these as a political instrument to implement a corporate SMA system within related SOEs. Additionally, the findings highlight the significant role of management accountants as central figures in integrating and standardising a corporate SMA system into the daily practices of current executives through advanced enterprise resource planning (ERP) technology. Moreover, as a development of institutional theory, the findings demonstrate the influence of corporate SMA reports on the decision-making processes of national governments in the context of urban development. Full article

Gaining an understanding of the intricate mechanisms between human activity and the built environment can help in promoting sustainable urban development. However, most scholars have focused on residents’ life and work behavior and have ignored the third activity (e.g., shopping, eating, and entertainment). In this study, a random forest algorithm and SHapley Additive exPlanation model were utilized to explore the nonlinear influence of the built environment on the attraction of the third activity (other than home and work). A comparative analysis of the inflow of the third activity from home and work was also carried out. The results show that the contributions of all built environment variables to the attraction of the third activity differ between home–other flow (HO) and work–other flow (WO) at the global scale, but their local effects are significantly similar. Furthermore, the nonlinear influence of the built environment on the attractions of the third activity can vary from one factor to another. A significant spatial heterogeneity can be observed on the built environment variables’ local effects on the attractions of the third activity. These findings can provide urban planners with insights that will help in the planning and optimization of communities for pursuing the third activity. Full article