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Continuous enhancement of sustainable development capacity is one of the goals of building a well-off society. In order to understand the development of each region, it is necessary to make a comprehensive evaluation of their sustainable development capacity. This paper presents a study of the 11 regions of Hebei Province, China. Considering the influence of time on urban development, this paper comprehensively evaluates the sustainable development ability of each region in Hebei Province from three dimensions of society, economy and environment based on panel data. The evaluation results show that Shijiazhuang has the strongest sustainable development capacity. On this basis, the promoting factors and restricting factors of sustainable development in each region are found by using grey correlation analysis method. This study provides a reference for the future sustainable development of each district. [ABSTRACT FROM AUTHOR]

In the process of global urban development, there are urgent ecological security and environmental pollution problems, green development is the fundamental way for urban sustainable development, economic transformation and mitigation of ecological and environmental problems. Based on the panel data of 283 cities at prefecture level and above in China from 2003 to 2017, this paper analyzes spatial–temporal evolution characteristics of urban green development efficiency (UGDE) and the peer effects of UGDE between cities of different grades. It is found that during the study period, in terms of temporal evolution, the average UGDE in China increased from 0.47 in 2003 to 0.61 in 2017, with a cumulative growth rate of 29.79%, showing a rising trend in general. In terms of spatial evolution, the number of low-efficiency cities and medium-efficiency cities continued to decrease. The eastern region has always been the main distribution area of higher-efficiency cities and high-efficiency cities; in the central region, UGDE in most cities improved significantly; in the western region, UGDE has always lagged behind that in the eastern and central regions. In addition, the center of gravity of UGDE presented a trend of northwest migration in general, with a total displacement of 100.07 km, and UGDE showed a spatial dispersion trend. The empirical results indicate that the improvement of UGDE in large cities has a driving effect on that in neighboring medium cities and small cities through the positive peer effect, and the growth of UGDE in medium cities has a promoting effect on that in neighboring small cities through the positive peer effect; the increase of UGDE in medium cities has a positive peer effect on that in neighboring large cities, and the growth of UGDE in small cities has a positive peer effect on that in neighboring medium cities; UGDE promotes each other between large cities through the positive peer effect. [ABSTRACT FROM AUTHOR]

In the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics. [ABSTRACT FROM AUTHOR]

As urban development accelerates and natural disasters occur more frequently, the urgency of developing effective emergency shelter planning strategies intensifies. The shelter location selection method under the traditional multi-criteria decision-making framework suffers from issues such as strong subjectivity and insufficient data support. Artificial intelligence offers a robust data-driven approach for site selection; however, many methods neglect the spatial relationships of site selection targets within geographical space. This paper introduces an emergency shelter site selection model that combines a variational graph autoencoder (VGAE) with a random forest (RF), namely VGAE-RF. In the constructed urban spatial topological graph, based on network geographic information, this model captures both the latent features of geographic unit coupling and integrates explicit and latent features to forecast the likelihood of emergency shelters in the construction area. This study takes Beijing, China, as the experimental area and evaluates the reliability of different model methods using a confusion matrix, Receiver Operating Characteristic (ROC) curve, and Imbalance Index of spatial distribution as evaluation indicators. The experimental results indicate that the proposed VGAE-RF model method, which considers spatial semantic associations, displays the best reliability. [ABSTRACT FROM AUTHOR]

Increased urbanization and population lead to increased consumption of manufactured goods. This ultimately results in increased production of waste. Identifying its composition is crucial for planning an effective solid waste management strategy. This study assesses the characteristics and composition of the waste generated within the Uyo Capital City Development Area of Akwa Ibom State, Nigeria. This is to aid in developing a scientifically supported waste management pilot system for the state. Direct waste sorting and characterization were conducted on the municipal solid waste arriving at the landfill during the study period. Over 50% of the generated wastes are recyclables and composed of plastics, metals, and paper, while the fraction of organic waste is over 30%. Similarly, the waste generation per capita is 1.34 kg/person/day, while the generation forecast over the next ten years is estimated to increase by approximately 40%. Furthermore, over 9,000 surveys were completed by residents to establish a problem statement about the existing waste collection and disposal system, and possible solutions. Importantly, a majority of survey respondents were willing to source-separate their wastes and supported paying a fee for adequate waste collection. This strongly indicates that an integrated waste management system could be established to generate value from the collected waste. Supplementary revenue can be generated through composting, recycling, and land reclamation. [ABSTRACT FROM AUTHOR]

With the development of information technology, such as cloud computing and 5G technologies, the construction of smart cities has been an essential part of the city's long-term development strategy for the 14th five-year plans in China. After a few years of development, the research problem of the dynamic performance assessment of smart cities has been a hot and urgent issue. This paper constructed the dimensions of smart productivity, smart livability, smart governance, and eco-community based on the connotations of smart cities. Then, an indicator system including 35 indicators was built based on the four dimensions. To enlarge the overall differences of the final assessment values, we used the vertical and horizontal deviation maximization (VH-DM) method to measure the performances of 31 smart cities in China from the year 2014–2018. Two essential findings and driving indicators were identified from the assessment results. Firstly, the development among the smart cities was unbalanced and more than half of the smart cities (accounting for 64.52%) were below the average level. The local authorities considered the urban agglomeration strategies to alleviate the problem of unbalanced urban development. Secondly, some smart cities (such as Chongqing) with large scale of population and total resources showed a low level after the total resources were allocated to per capita, which provided a warning for the smart cities to pay more attention to individual development. The local authorities have proposed the high-quality development strategies to deal with such problems. [ABSTRACT FROM AUTHOR]

The aim of this study was to create a dataset of building locations in Poland from the 1970s–1980s. The source information was the historical 1:10 000 Polish topographic map. Building footprints were detected and extracted from approximately 8,500 scanned map sheets using the Mask R-CNN model implemented in Esri ArcGIS Pro software, and converted to point building locations. The dataset of building locations covers the entire country and contains approximately 11 million points representing buildings. The accuracy of the dataset was assessed manually on randomly selected map sheets. The overall accuracy is 95% (F1 = 0.98). The dataset may be used in conjunction with various contemporary land use, land cover and cadastral datasets in a broad range of applications related to long-term changes in rural and urban areas, including urban sprawl and its environmental and social consequences. It can also serve as a highly reliable reference dataset for regional or global settlement products derived, e.g., from early Landsat data. [ABSTRACT FROM AUTHOR]

In this research, remote sensing satellite imagery has been applied to assess dynamic and static sprawl measured simultaneously via a multi-technique approach. The first technique, which evaluates dynamic sprawl, essentially measures the "magnitude" and "direction". The second technique, which evaluates static sprawl, measures the "magnitude" and "pattern". The dynamic sprawl used in this study, shows in which "direction", in what "period" and to what "extent" Kerman had sprawl. In the static sprawl, the most sprawled pattern that the city of Kerman follows is Area-Edge, followed by Aggregation, Shape and Diversity, respectively. [ABSTRACT FROM AUTHOR]

Rapid population increment of big towns, creation of numerous small-towns, increasing demand for better urban-related facilities from the big towns and availability of better transport facilities always accelerate the process of urban-to-urban interaction. It will be interesting to understand in which pattern and extent the inter-urban interaction is taking place over a backward region like Purulia district, West Bengal. So, to understand the impact of urban-to-urban interaction on the process of urban development, the present study was executed to analyse the urban-to-urban interaction of the towns of four groups for the betterment of the big as well as small-towns in near future. Purulia district has now twenty-eight towns and these towns are grouped based on the distance between each other like the north-eastern town group, central town group, southern town group and western town group for a clear understanding of the pattern of interaction between them. The Synthesised Gravity Model has been applied to identify the pattern and intensity of interaction between the towns in the prescribed town groups which is a modern version of traditional gravity model. To quantify a town's influential factor on another town over the same region, the study used to identify a set of socio-economic variables and the data were collected based on a questionnaire method against these variables. The result of the study shows that in each of the selected town groups the interaction has occurred from small-town to the big town oriented. The study also revealed that the interaction between the towns has a massive impact on the process of urban development for the small and big towns. The suggested planning recommendations based on the study will be very helpful for planners for sustainable urban planning of the statutory as well as census towns in future. [ABSTRACT FROM AUTHOR]

Archaeological heritage worldwide is threatened through deliberate destruction in particular site looting making the location of archaeological sites potentially sensitive data. At the same time, public information about site locations are important for heritage management, as well as agricultural and urban development. Finding a balance between revealing detailed site locations and not providing data at all is a difficult task. Here we provide an approach to obfuscate archaeological site location data facilitated through a Discrete Global Grid System. We then apply the new obfuscation method to the global p3k14c data set. Veiling the locations of heritage sites with a Discrete Global Grid System allows tiered accuracy access for different stakeholders tailored to their respective needs as well as legal constraints and requirements of administrations. Discrete Global Grid System based obfuscation is globally scalable, consistent, reproducible, and can address the current heterogeneity of obfuscation methods. [ABSTRACT FROM AUTHOR]

With the increasing global population and escalating ecological and farmland degradation, challenges to the environment and livelihoods have become prominent. Coordinating urban development, food security, and ecological conservation is crucial for fostering sustainable development. This study focuses on assessing the "Ecology-Agriculture-Urban" (E-A-U) space in Yulin City, China, as a representative case. Following the framework proposed by Chinese named "environmental capacity and national space development suitability evaluation" (hereinafter referred to as "Double Evaluation"), we developed a Self-Attention Residual Neural Network (SARes-NET) model to assess the E-U-A space. Spatially, the northwest region is dominated by agriculture, while the southeast is characterized by urban and ecological areas, aligning with regional development patterns. Comparative validations with five other models, including Logistic Regression (LR), Naive Bayes (NB), Gradient Boosting Decision Trees (GBDT), Random Forest (RF) and Artificial Neural Network (ANN), reveal that the SARes-NET model exhibits superior simulation performance, highlighting it's ability to capture intricate non-linear relationships and reduce human errors in data processing. This study establishes deep learning-guided E-A-U spatial evaluation as an innovative approach for national spatial planning, holding broader implications for national-level territorial assessments. [ABSTRACT FROM AUTHOR]

Severe weather events, such as heat waves, floods, pollution, and health threats, are becoming more common in metropolitan places across the world. Overcrowding, poor infrastructure, and fast, unsustainable urbanization are some of the problems that India faces, and the country is also susceptible to natural disasters. This research analyzes climatic variables affecting urban hazards in Bangalore (also known as Bengaluru) via a thorough review. Heat waves, urban floods, heat islands, and drought were identified in 156 qualifying publications using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method. Contributing variables were also considered. City development and urbanization were key to changing climate and increasing urban dangers. While long-term climatic variable distribution is uneven, warming is evident. The report promotes strong urban planning techniques, comprehensive policies, more green areas, and sustainable development beyond short-term heat response programs to boost urban climate resilience. This study shows how climate, land use, and urban dangers are interconnected. Future studies may benefit by categorizing urban risk studies and identifying climatic factors. [ABSTRACT FROM AUTHOR]

During the past two decades, Qatar, a developing country, has invested heavily in infrastructure development to address several challenges caused by the rapid urbanization. Qatar has made a significant step toward its urban sustainability vision through the construction of the Doha Metro system. By adopting Transit-Oriented Development (TOD), Qatar is overcoming some urban challenges. TOD promotes compact, walkable, and mixed-use development around the transit nodes, which enhances the public realm through providing pedestrian-oriented and active spaces. Additionally, Qatar aims to transfer to a knowledge-based economy through developing an environment that will attract knowledge and creative human power. Qatar Foundation is taking the lead toward implementing a Knowledge-Based Urban Development (KBUD) through its flagship project: Education City (EC). This study aims therefore to evaluate the integration of TOD and KBUD strategies to leverage the potential of TOD in attracting knowledge and creative economy industries. The selected case study is Qatar National Library (QNL) metro station at the EC in Doha. The study examines the potential of QNL as a destination TOD to enhance the area's mission as a driver for a knowledge-based economy. The methodological approach is based on the analytical concepts obtained from the Integrated Modification Methodology as a sustainable urban design process. The study's results revealed that void and function, followed by volume, are the weakest layers of the study area's Complex Adaptive System which require morphological modification to achieve sustainability and a knowledge-hub TOD. The study offers recommendations to assist planners and designers in making better decisions toward regenerating urban areas through a knowledge-hub TOD contributing to the spill out of knowledge and creativity into the public realm creating a human-centric vibrant public space adjacent to metro stations. [ABSTRACT FROM AUTHOR]

The development of a city's green infrastructure is increasingly being driven by low-carbon innovation (LCI). However, knowledge of how LCI affects green economic efficiency (GEE) in China is largely unknown. This study investigates the spatial effects of LCI on GEE in 285 Chinese prefecture-level cities. The empirical findings show that LCI exerts significant beneficial effects on its GEE but negative effects on its neighbors. The positive direct effects on GEE are offset by negative indirect effects due to the lack of spatial linkage effect and the existence of the siphon and crowding-out effects among cities. Using a mediating effect model, we have identified three channels of LCI that affect GEE: industrial structure, energy consumption structure, and human capital. A further heterogeneity analysis indicates that the impacts of LCI on GEE differ by region and city development level. Furthermore, LCI in the building, greenhouse gas treatment, transportation, and sewage and pollutant treatment categories could greatly enhance local GEE. The findings herein provide an empirical experience for accurately accessing the spatial effect of LCI on GEE, and offer a critical decision-making reference for implementing a cross-city green linkage development mechanism. [ABSTRACT FROM AUTHOR]

Urban expansion within Greater Irbid Municipality (GIM) witnessed an extraordinary rise, expanding approximately ninefold between 1967 and 2020. Recent trends revealed a shift in urban growth towards southern and eastern regions. These dynamics carry critical implications for urban planners and environmental managers, urging a comprehensive understanding of the driving factors behind this expansion to anticipate future challenges. Employing logistic regression (LR) and geographically weighted logistic regression (GWLR) analyses using remote sensing data and GIS, spatially variant coefficients for driving factors emerged, illuminating the evolving landscape of urban development drivers within GIM. Yarmouk University historically promoted urban expansion, but recent proximity to Yarmouk University and JUST University, coupled with higher existing building percentages, inhibited further urbanization. The analysis also revealed that elevation and slope had negligible impacts on urban expansion. These findings underline the evolving dynamics of urban development drivers within the study region. The local perspective depicted significant spatial disparities in coefficients, highlighting variations in magnitude and direction. GWLR emerged as a more robust methodology, effectively capturing regional variations and enhancing model reliability. These findings hold immense value for informing current and future urban planning practices in Greater Irbid Municipality. Proactively addressing identified challenges and understanding the intricate dynamics of urban expansion can assist Irbid in shaping a sustainable and resilient future, avoiding potential pitfalls in its urban development endeavors. [ABSTRACT FROM AUTHOR]

Urban heritage is a vital resource that connects communities to their local identity. Unplanned developments and rapid urbanisation often harm the authenticity of historic areas, disrupting the cultural fabric and altering their character. This study introduces the Relative Positive Impact Index (RPII), a novel technique for assessing the socio-cultural impacts of urban revitalisation. The significance of RPII lies in its ability to quantitatively evaluate the impacts on the cultural fabric and integrity of historic urban areas, which is crucial for sustainable urban development. The study's objective is to apply RPII in evaluating qualitative socio-cultural characteristics in historic urban areas, with a focus on four main criteria and 16 sub-criteria, in the case of the Kuttichira precinct. The methodology integrates the analysis of published literature, a quantitative survey mapping the stakeholders' perception, and qualitative insights. This approach facilitates an in-depth understanding of how urban revitalisation affects local socio-cultural dynamics, preserving the authenticity and character of historic areas. The study reveals that the revitalisation project in Kuttichira positively impacts the socio-cultural fabric of the area, maintaining cultural integrity and addressing social challenges. These findings offer valuable insights for sustainable urban development and policymaking in historic areas. The study recommends the application of RPII in other urban precincts for comparative analysis and further development of urban development practices, contributing to informed urban policy and planning decisions. [ABSTRACT FROM AUTHOR]

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH3, NOx and N2O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$ 61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on. Here the authors demonstrate how managed urbanization in China could halve reactive nitrogen pollution to both the atmosphere and water resources. Investing 61 billion USD could provide 245 billion USD in benefits, while contributing to multiple SDG goals. [ABSTRACT FROM AUTHOR]