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The Western Himalayan Region (WHR) is under constant threat from Land Use and Land Cover Change (LULCC) brought on by various socioeconomic activities such as urbanization, agricultural expansion, and population growth. Detailed research into the scope of these changes is necessary to comprehend the challenges they represent. This study aimed at (1) examining and quantifying spatiotemporal patterns of LULCC from 1975 to 2015, (2) mapping the hotspots of forest loss, and (3) modelling future LULCC for the year 2055 using medium spatial resolution multispectral satellite imagery (MSS, TM, LISS-I, LISS-III, AWiFS), field data, visual interpretation and logistic regression model in the WHR. Logistic regression integrated various drivers of LULCC, including climatic, topographic, and socio-economic factors and past LULCC trends to forecast potential LULC in the WHR by 2055. The results highlight an outrageous 184% increase in regional urbanization. Expansion of urban and cropland (12%) led to deforestation which reduced the area of natural habitats, specifically forests (−11%), water bodies (−8%) and scrubland (−6%). A significant rise in barren land by 30% was noted, while there was a decrease of 20% in glacier/snow melt. The future projection for 2055 anticipates continuing current trends, emphasizing an intensified urban expansion of 63% and an approximate 9% reduction in overall forest coverage. The accuracy of the predicted 2015 LULC map was assessed using ROC/AUC (Receiver Operating Characteristic/Area under Curve) which was found to be 0.79. [ABSTRACT FROM AUTHOR]

Fine classification of city-scale buildings using satellite imagery is a crucial research area with significant implications for urban planning, infrastructure development, and population distribution analysis. However, the task faces great challenges due to low-resolution overhead images acquired from high-altitude space-borne platforms and the long-tailed sample distribution of fine-grained urban building categories, leading to a severe class imbalance problem. To address these issues, we propose a deep network approach to the fine-grained classification of urban buildings using open-access satellite images. A Denoising Diffusion Probabilistic Model (DDPM) based super-resolution method is first introduced to enhance the spatial resolution of satellite images, which benefits from domain-adaptive knowledge distillation. Then, a new fine-grained classification network with Category Information Balancing Module (CIBM) and Contrastive Supervision (CS) technique is proposed to mitigate the problem of class imbalance and improve the classification robustness and accuracy. Experiments on Hong Kong data set with 11 distinct building types revealed promising classification results with a mean Top-1 accuracy of 60.45%, which is on par with street-view image based approaches. A comprehensive ablation study demonstrates that the CIBM and CS modules improve Top-1 accuracy by 2.6% and 3.5%, respectively, over the baseline approach. In addition, these modules can be easily integrated into other classification networks, achieving similar performance improvements. This research advances urban analysis by providing an effective solution for detailed classification of buildings in complex mega-city environments using only open-access satellite imagery. The proposed technique can serve as a valuable tool for urban planners, aiding in the understanding of economic, industrial, and population distribution within cities and regions, ultimately facilitating informed decision-making in urban development and infrastructure planning. Data and code will be publicly available at https://github.com/ZhiyiHe1997/UB-FineNet. [ABSTRACT FROM AUTHOR]

• We study the specific impact of the digital economy on the upgrading of urban residents' consumption structure and its mechanism of action. • We analyze the heterogeneity at the level of city development. • The development of the digital economy is conducive to promoting the upgrading of urban residents' consumption structure. • Disposable income and industrial structure upgrading are important internal mechanisms. • Compared to first-tier and second-tier cities, the digital economy has contributed more to upgrading residents' consumption structure in third-tier cities. Based on the panel data of Chinese cities from 2011 to 2020, this paper studies the impact of the digital economy on urban residents' upgrading of their consumption structure. The digital economy promotes the upgrading of urban residents' consumption structure. Moreover, the digital economy has a more significant effect on promoting the upgrading of residents' consumption structure in third-tier cities. The mediation effect proves that increasing disposable income and upgrading the industrial structure are crucial mechanisms. Based on pertinent findings and the development levels of various cities, this paper proposes policies to strengthen the digital infrastructure, improve residents' income, optimize industrial structure, and establish differentiated measures. [ABSTRACT FROM AUTHOR]

Urban development in South America has experienced significant growth and transformation over the past few decades. South America's urban development and trees are closely interconnected, and tree cover within cities plays a vital role in shaping sustainable and resilient urban landscapes. However, knowledge of urban tree canopy (UTC) coverage in the South American continent remains limited. In this study, we used high-resolution satellite images and developed a semi-supervised deep learning method to create UTC data for 888 South American cities. The proposed semi-supervised method can leverage both labeled and unlabeled data during training. By incorporating labeled data for guidance and utilizing unlabeled data to explore underlying patterns, the algorithm enhances model robustness and generalization for urban tree canopy detection across South America, with an average overall accuracy of 94.88% for the tested cities. Based on the created UTC products, we successfully assessed the UTC coverage for each city. Statistical results showed that the UTC coverage in South America is between 0.76% and 69.53%, and the average UTC coverage is approximately 19.99%. Among the 888 cities, only 357 cities that accommodate approximately 48.25% of the total population have UTC coverage greater than 20%, while the remaining 531 cities that accommodate approximately 51.75% of the total population have UTC coverage less than 20%. Natural factors (climatic and geographical) play a very important role in determining UTC coverage, followed by human activity factors (economy and urbanization level). We expect that the findings of this study and the created UTC dataset will help formulate policies and strategies to promote sustainable urban forestry, thus further improving the quality of life of residents in South America. [ABSTRACT FROM AUTHOR]

This study observes and records land cover changes in Al-Baha to track urban growth. The study develops a schematic vision of urban mass's current and future shape and distribution and its growth to achieve sustainable urban development, reduce service and social differences between city areas, and integrate urban and rural areas. The study uses inductive methods to monitor urban developments, population growth, and land use through Al-Baha's structural schemes by extracting digital data from satellite imagery to survey historical land cover changes. The mapping software ArcGIS v10.8 processed these digital data and the final map compositions. Through this urban mass study, the research predicted city growth and development. Capabilities and functions must shape urban and rural-urban communities. The development must also consider the National Urban Development Strategy, the relative importance of rural-urban communities, and their expected functional role in influencing the development of small rural communities adjacent to them to reduce migration from rural areas near the city. The study highlighted changes in city land coverage. Al-Baha expanded from 1982 to 1995. Al-Baha's transformation from village to city accelerated, increasing its area from 31 km2 to 44 km2. Many villages beyond 40 were included in the decisions. From 2006–2021, the city's area grew 221%. It increased from 60 km2 to 133 km2 in an urban area, indicating false urban growth. The study stressed the importance of geographic information systems (GIS) and remote sensing (RS). The study recommends urban development in suitable areas because agricultural development is not feasible, especially in the northeast. Land use changes should be prevented by planning regulations because these agricultural areas are essential. Helping urban development move away from agricultural areas, especially on the eastern axis, is crucial. Create new urban centers along Al-Baha's western cliff to attract residents and relieve pressure. Limited linear expansion, especially in the northeast, and more expansive urbanization are also significant. Maps should also show when the Al-Baha region's expansionary scope changed and the urban boundaries that had to be reached by a specific time while development plans were efficiently monitored. [ABSTRACT FROM AUTHOR]

Compact building models are demanded by global smart city applications, while high-definition urban 3D data is increasingly accessible by dint of the advanced reality capture technologies. Yet, existing building reconstruction methods encounter crucial bottlenecks against high-definition data of large scales and high-level complexity, particularly in high-density urban scenes. This paper proposes a Building Section Skeleton (BSS) to reflect architectural design principles about parallelism and symmetries. A BSS atom describes a pair of intrinsic parallel or symmetric points; a BSS segment clusters dense BSS atoms of a pair of symmetric surfaces; the polyhedra of all BSS segments further echo the architectural forms and reconstructability. To prove the concepts of BSS for automatic compact reconstruction, this paper presents a BSS method for building reconstruction that consists of one stage of BSS segments hypothesizing and another stage of BSS segments merging. Experiments and comparisons with four state-of-the-art methods have been conducted on 15 diverse scenes encompassing more than 60 buildings. Results confirmed that the BSS method achieves frontiers in compactness, robustness, geometric accuracy, and efficiency, simultaneously, especially for high-density urban scenes. On average, the BSS method reconstructed each scene into 623 triangles with a root-mean-square deviation (RMSD) of 0.82 m, completing the process in 110 s. First, the proposed BSS is an expressive 3D feature reflecting architectural designs in high-density cities, and can open new avenues to city modeling and other urban remote sensing and photogrammetry studies. Second, for practitioners in smart city development, the BSS method for building reconstruction offers an accurate and efficient approach to compact building and city modeling. The source code and tested scenes are available at https://github.com/eiiijiiiy/sobss. [Display omitted] • Building Section Skeleton (BSS) is proposed with novel definitions of BSS atoms and segments. • BSS revamps traditional shape skeletons to reflect architectural design principles about parallelism and symmetry. • A BSS method consisting of two stages is developed for compact building reconstruction from urban point clouds. • The BSS method of reconstruction was confirmed compact, robust, geometrically accurate, and efficient. [ABSTRACT FROM AUTHOR]

Building footprint information is crucial for comprehending global urban development processes. Deep learning algorithms have shown significant potential in building extraction from high spatial resolution imagery. However, the requirement for large-scale annotated data has been a limitation for applying deep learning methods to city-level or national-level building mapping. The dynamic change and distinct landscape variation of cities in different geographic locations further emphasizes the need for automatic building footprint extraction. In this paper, we propose a Self-supervised Knowledge Transfer (SKTrans) framework for extracting building footprints from unlabeled remote sensing images over large areas. To address building tone differences cross regions and time periods, a tone shift mechanism is introduced to reduce the contrast, brightness, and saturation differences between buildings. Furthermore, considering building style diversity across different cities, a knowledge integration module is proposed to develop a comprehensive depiction including tonal differences, multi-scale variance, structural attributes and semantic confusion between roads and buildings. The effectiveness of SKTrans is demonstrated on three public datasets of WHU, Massachusetts, and Inria. To further evaluate the feasibility of large-scale mapping for automatic building footprint, global generalization experiments cross regions and time periods, which is based on imagery from five countries of different continents were implemented. The comprehensive results demonstrate that SKTrans surpasses existing state-of-the-art methods, supporting the time-series city-level building mapping without labeled dataset. Additionally, the architectural landscape pattern changes can be quantitatively analyzed based on the generalization results to facilitate sustainable urban development. Overall, SKTrans provides a new insight to meet the needs of high-precision label-free building mapping and update from large-scale multi-style remote sensing images. [ABSTRACT FROM AUTHOR]

City events take place in the Zhangzhou Olympic Sports Center, resulting in traffic. Hence, this study analyzed the road planning and design around Zhangzhou Olympic Sports Center through traffic demand forecasting. The simulated data and road plan underwent macro prediction model technology and numerical simulation technology through Emme and TransCAD. The regional road network structure, traffic demand forecast, plane, longitudinal section, and cross-sectional program selection were investigated to determine a reasonable design program. While urban development programs were implemented, the study ensured an increase in the city's economic growth alongside the guaranteed value of citizens' welfare. [ABSTRACT FROM AUTHOR]

Getting precise aspects of road through segmentation from remote sensing imagery is useful for many real-world applications such as autonomous vehicles, urban development and planning, and achieving sustainable development goals (SDGs). 1 1 https://sdgs.un.org/goals. Roads are only a small part of the image, and their appearance, type, width, elevation, directions, etc. exhibit large variations across geographical areas. Furthermore, due to differences in urbanization styles, planning, and the natural environments; regions along the roads vary significantly. Due to these variations among the train and test domains (domain shift), the road segmentation algorithms fail to generalize to new geographical locations. Unlike the generic domain alignment scenarios, road segmentation has no scene structure and generic domain adaptive segmentation methods are unable to enforce topological properties like continuity, connectivity, smoothness, etc., thus resulting in degraded domain alignment. In this work, we propose a topology-aware unsupervised domain adaptation approach for road segmentation in remote sensing imagery. During domain adaptation for road segmentation, we predict road skeleton, an auxiliary task to enforce the topological constraints. To enforce consistent predictions of road and skeleton, especially in the unlabeled target domain, the conformity loss is defined across the skeleton prediction head and the road-segmentation head. Furthermore, for self-training, we filter out the noisy pseudo-labels by using a connectivity-based pseudo-labels refinement strategy, on both road and skeleton segmentation heads, thus avoiding holes and discontinuities. Extensive experiments on the benchmark datasets show the effectiveness of the proposed approach compared to existing state-of-the-art methods. Specifically, for SpaceNet to DeepGlobe adaptation, the proposed approach outperforms the competing methods by a minimum margin of 6.6%, 6.7%, and 9.8% in IoU, F1-score, and APLS, respectively. (The source code is available on Github). [ABSTRACT FROM AUTHOR]

Road silt loading (sL) is an important parameter in the fugitive road dust (FRD) emissions. In this study, the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) combined with the AP-42 method was firstly developed to quickly measure and estimate the sLs of paved roads in Beijing, China. The annual average sLs in Beijing was 0.59±0.31 g/m2 in 2020, and decreased by 22.4% compared with that in 2019. The seasonal variations of sLs followed the order of spring > winter > summer > autumn in the two years. The seasonal mean road sLs on the same type road in the four seasons presented a decline trend from 2019 to 2020, especially on the Express way, decreasing 47.4%-72.7%. The road sLs on the different type roads in the same season followed the order of Major arterial ∼ Minor arterial ∼ Branch road > Express road, and Township road ∼ Country highway > Provincial highway ∼ National highway. The emission intensities of PM 10 and PM 2.5 from FRD in Beijing in 2020 were lower than those in 2019. The PM 10 and PM 2.5 emission intensities at the four planning areas in the two years all presented the order of the capital functional core area > the urban functional expansion area > the urban development new area > the ecological conservation and development area. The annual emissions of PM 10 and PM 2.5 from FRD in Beijing in 2020 were 74,886 ton and 18,118 ton, respectively, decreasing by ∼33.3% compared with those in 2019. [Display omitted] [ABSTRACT FROM AUTHOR]

This work addresses the challenge of classifying watersheds to support land use policy-making in rapidly developing, wet tropical regions, using a case study of the Brantas River Basin, Java, Indonesia. Hierarchical Clustering on Principal Components of the watershed descriptors resulted in three optimal clusters. Differentiation among these three clusters is mainly related to climatic regimes, topographic features, and land uses. Stepwise regression was used to identify the watershed descriptors that explain the spatial variability of four flow indices (95% non-exceedance percentile Q95; 5% non-exceedance percentile Q5; the slope of the flow duration curve SFDC; and the runoff coefficient RC). This gave, for these four indices in turn, R2 values of 0.77, 0.76, 0.84 and 0.45. The results show that built-up areas and dryland forest are primary land-use controls on flow indices. Clustering results suggest that existing regional development trends will have major hydrological impacts, especially related to runoff generation and groundwater. The results support the view that failure to implement land-use policy – failure that is expected to increase built-up areas across the watershed and increase forest loss in the upper watershed - will jeopardize watershed hydrological functions. The findings of this research support the need for frequent and updated land-use monitoring to control urban development and conserve dryland forest, as well as land-use policies that control increases in built-up areas and that minimize forest loss. [ABSTRACT FROM AUTHOR]

The dynamics of built-up height are a crucial aspect of urban form, enabling the characterization of urban growth patterns and the attainment of sustainable development goals. While past studies have focused on urban extent mapping, little has been done to reveal changes in vertical structures in built-up areas. In this study, we reconstructed annual urban form dynamics in Beijing, China, from 1990 to 2020, utilizing Landsat time-series data. First, we identified urban growth and renewal years using a temporal segmentation approach. Then, we reconstructed the annual dynamics of built-up heights through logical reasoning, using the reference height in 2020 and the identified changing years. We evaluated the derived dataset and analyzed the urban growth patterns (i.e., upward and outward) over the past three decades. The detected change years are reliable, with an overall accuracy of 88% (± 1 year). Meanwhile, the reconstructed built-up height data showed good agreement with surveyed results (R2: 0.92), with a root mean square error of 2.87 m and a mean absolute error of 2.07 m. Most expanded built-up areas during 1990–2020 were located at the fringe of the central city, and about 16% experiencing multiple changes. Overall, outward growth was prominent in Beijing during the first decade, while upward growth became dominant in most districts thereafter. The proposed framework provides a new way to reveal annual urban form dynamics through time series analysis, with great potential to support relevant studies such as urban climate modeling and carbon emissions studies. [ABSTRACT FROM AUTHOR]

Lagos is Africa's most populous megacity and one of the world's fastest-growing urban areas. Lagos city's land use and land cover (LU/LC) classes have changed dramatically in recent decades as a result of its continuing population growth and other human and anthropogenic activities. The UN 2030 Agenda for Sustainable Development must be adopted in order to preserve the available land cover classes in Lagos. Goal 11 of the Sustainable Development Goals aims to make cities and human settlements more inclusive, safe, resilient, and long-term. The use of remote sensing and geographic information systems (GIS) to track the progress of SDG 11 is an essential strategy. Remote sensing and geographic information systems were used to model and analyze the data in this study. To achieve this aim, remotely sensed data, such as Landsat 7 ETM + and 8 OLI, was used to determine the rate of changes in Lagos from 2010 to 2020 by adopting the Maximum Likelihood Classifier (MLC) and then project the likely changes that may occur by 2025 and 2030. Observed ground truthing information was adopted for validation and for checking the accuracy of the classification. The result shows that from 2010 to 2015 and to 2020, built-up area had increased from 11.73 % to 12.81 % and finally to 29.51 %, while agricultural land declined by 11.84 % to 3.37 % and then to 2.99 %. Water bodies and wetland percentages decreased from 19.00 % and 19.50 % in 2010 to 17.39 % and 8.48 % in 2015, and to 18.37 % and 16.92 % in 2020. Forest land and bare land classes have also changed from 25.4 % and 12.52 % in 2010, to 33.37 % and 24.58 % in 2015, and to 18.10 % and 14.11 % in 2020. The study shows that remote sensing and GIS are excellent tools for monitoring the environment and for the development of a sustainable city. [ABSTRACT FROM AUTHOR]

Cities in ecologically vulnerable areas have high ecological sensitivity, and the balance between urban expansion and the ecological environment is easily broken, leading to various environmental problems. These problems seriously interrupt the sustainable health development of urban ecosystems. Studying urban ecological network construction from the perspective of multifactor ecological processes is of important significance to the ecological safety and resource management of cities. In this study, an analysis of ecological elements was conducted separately to account for the "vertical" and "horizontal" ecological processes present in the ecological network. By using the superposition mode of vertical ecological processes, the composition of vital ecological patches was analyzed, and important ecological patches within the ecosystem were identified through ecological sensitivity evaluation index system. On the other hand, the composition of ecological corridors was analyzed through the use of horizontal ecological processes. The biological corridor was determined by source identification of biological processes and resistance surface analysis while the catchment corridor was determined through runoff simulation. Based on these findings, it was possible to propose an urban ecological network construction system specifically designed for Loess Plateau regions using a superposition of ecological sensitivity, biological processes, and catchment processes. Finally, a case study of the urban ecological network system of Loess Plateau regions was conducted in Huanxian City. Comparing the proposed urban ecological network of the Loess Plateau regions and the generated scheme with the overall planning scheme of 2016, the patch density and the largest patch index decreased by 1.522 and 13.794, respectively, while the fractal dimension, interspersion and juxtaposition index, the contagion index, and the connectivity index increased by 0.003, 2.188, 14.076, and 1.366, respectively. This trend proves that the research scheme improved in terms of ecological performance. Research conclusions can provide useful references for the construction of urban ecological networks in underdeveloped and ecologically vulnerable areas in China while offering guidelines for making decisions on the green development and management of urban spaces. [ABSTRACT FROM AUTHOR]

Urban areas' performance in water, energy, infrastructure, and socio-economic sectors is intertwined and measurable through Sustainable Development Goals (SDGs) 6–13. Effective synergy among these is critical for sustainability. This study constructs an indicator framework that reflects progress towards these urban SDGs in China. Findings indicate underperformance in SDGs 8–11, suggesting the need for transformative actions. Through network analysis, the research reveals complementarities among these SDGs. Notably, the SDG space divides into socio-economic and ecological clusters, with SDG 6 (Clean Water and Sanitation) central to both. Additionally, SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure) act as bridges, while greater synergies exist between SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action). An in-depth view at the indicator-level shows a core-periphery structure, emphasizing indicators like SDG 6.2 (Wastewater Treatment Rate) and SDG 6.6 (Recycled Water Production Capacity per capita) as pivotal. This study confirms the urban SDG space's stability and predictiveness, underscoring its value in steering well-aligned policy decisions for sustainable growth. [ABSTRACT FROM AUTHOR]

Fig. 4 Co-occurrences of urban waste policies based on the "5R" principles and the policy instruments used to address waste. [Display omitted] • A classification framework and accompanying research approach are introduced. • Combinations of policy instruments, "R" strategy and waste type are emphasized. • The "Rethink", "Reduce", and "Recycle" strategies are mostly used by cities. • Projects, legal and innovation are the policy instruments mostly implemented. • Chinese cities combine multiple urban waste policies to become zero-waste cities. Chinese cities are experiencing rapid urban development while facing severe challenges of environmental pollution. China's central government has proposed several policies to reduce urban waste. However, little is known about the adoption of these policies. Here, we raise the question how can circular policies be classified, and how can this classification be applied to cities in China that wish become zero-waste cities? We develop a framework to classify urban waste policies according to: (a) the "5R" principles ("Rethink", "Reduce", "Reuse", "Recycle", and "Recover"), (b) four types of waste (industrial, agricultural, municipal, and hazardous) and (c) six types of policy instruments (legal, economic, network, communication, innovation and projects). We use this framework to analyze urban waste policies implemented by sixteen zero-waste demonstration projects in China. The present study emphasizes combinations of policy instruments, "R" strategy and waste type in the implementation of zero-waste policies. We find that the "Rethink", "Reduce", and "Recycle" principles have been widely implemented by local authorities in contrast to the principles "Reuse" and "Recover". Local governments address waste management by embracing regulations, innovation instruments, and project arrangements, while network-based, economic, or communicative policy instruments are used less often. Based on the results we suggest that local governments embrace a comprehensive approach to the use of the "5R" principles and deploy a diverse portfolio of policy instruments. [ABSTRACT FROM AUTHOR]

Under the background of China's high-quality economic growth with total factor productivity (abbreviated as TFP) growth as a key driver, this study attempts to integrate heterogeneous industrial agglomeration, innovation agglomeration, and institutional distance into the theoretical analysis framework of urban green total factor productivity (abbreviated as GTFP). The impact and effect of industrial agglomeration on urban GTFP growth, and the moderating role of innovation agglomeration and institutional distance in the above effects are examined empirically. The findings indicate a significant inverted "U" relationship between the three types of industrial agglomeration and urban GTFP growth. From the critical values, the three types of industrial agglomeration do not cross the critical value on the whole, showing the promoting effect on the growth of urban GTFP. Under the different types of city divisions (small, medium and large cities, east-central-west cities, and north-south cities), the effect of the three types of industrial agglomeration on GTFP growth in different types of cities has typical heterogeneity. Innovation agglomeration and institutional distance play a positive regulatory role in the impact of industrial agglomeration on the growth of urban GTFP. It is further found that innovation agglomeration plays a threshold role in the impact of industrial agglomeration on urban GTFP, i.e., the positive contribution effect of three types of industrial agglomeration on urban GTFP growth gradually increases with the increase of urban innovation agglomeration. This paper introduces the research results of industrial agglomeration on urban GTFP and provides policy implications for improving GTFP. [ABSTRACT FROM AUTHOR]

This study investigates the green total factor productivity of urban agglomerations, a high-level urban organisational form, by estimating the green total factor productivity (GTFP) of 285 cities in China from 2003 to 2017 using global data envelopment analysis and a super-slack-based measure model with undesirable output. Based on these estimations, we obtain the GTFP of 19 urban agglomerations and analyse the spatiotemporal evolution, dynamic evolution of spatial distribution, and regional differences in the urban agglomeration GTFP using various analytical tools such as the Dagum Gini coefficient, subgroup decomposition, σ and β convergence analysis, and kernel density estimation. Additionally, we identify and analyse the driving factors of GTFP growth in urban agglomerations by employing a panel model from the perspective of improving the efficiency of cities within urban agglomerations and optimising the development of intercity industrial and spatial structures. The results are as follows: First, the GTFP of urban agglomerations generally exhibit a fluctuating upward trend with low values in northwest-central China and high values in the north-southeastern coastal areas. Second, the GTFP differences among the urban agglomerations present an overall convergent trend, with the smallest gap between the national-level urban agglomerations and a stable performance. The gaps between regional and local urban agglomerations undergo considerable narrowing of the evolutionary trend, whereas gaps between local urban agglomerations and other urban agglomerations keep expanding. Third, economic growth, environmental regulation, energy consumption, and foreign direct investment and technological progress are conducive to improving urban GTFP, and a U-shaped relationship exists between cooperative industrial agglomeration and urban agglomeration GTFP. We suggest that strengthening regional collaborative environmental governance can improve the GTFP in urban agglomerations. [ABSTRACT FROM AUTHOR]

Decentralization has always been considered the reason local governments in China lack incentives for green development. Whether conferring honorary titles can motivate the competition mode of local governments to shift to low-carbon sustainable development is a scientific problem worth studying. In this paper, the civilized city policy is taken as a quasi-experiment, and its effect is evaluated using the method of difference-in-differences. The results show that civilized city policy can effectively promote the improvement of green total factor carbon efficiency. The mechanism is that the policy encourages local governments to mobilize multiple actors to participate in green development practices including strengthening local governments' environmental control, promoting the technological innovation of enterprises, and increasing public participation in environmental affairs. Heterogeneity analysis of local government incentives shows that the civilized city policy is more effective in cities where local officials are less than 54 years old and the city GDP growth rate is midstream in the province. The study confirms that awarding honorary titles to cities in China can effectively guide local governments toward a sustainable development model and provides new ideas for other countries in the world to use local policies to address global climate change. [ABSTRACT FROM AUTHOR]

Sustainable city development is an approach to city planning and management that takes into account the balance between economic, social and environmental aspects in order to ensure sustainable social development, environmental protection and ensuring a high quality of life for residents. The aim of the article is to draw attention to the problems in the field of parking vehicles in a smart city, which should be solved as soon as possible. Problems related to parking in the city are a common challenge that can affect the comfort of living of residents, traffic, natural environment and transport efficiency. Many cities lack parking spaces in relation to the number of vehicles, leading to difficulties in finding a parking space. This can lead to traffic jams that increase the time it takes to find a parking space, increase traffic-related emissions and reduce the quality of life for residents. The research method to solve the problem related to the management of parking spaces is focused on the analysis of the city's problems and guidelines resulting from the sustainable development of the European Union. In the application part, open data resources were used to carry out the simulation in the proprietary application solution. The result of the article, which is a scientific research, is the presentation of the author's application in the Digital Twin concept for the simulation of parking space management. The simulation is the result of research conducted using open data published on the Internet. The conclusion of the research is that in the process of effective management of parking spaces, simulation in the Digital Twin concept can be used. There is great potential in this approach. [ABSTRACT FROM AUTHOR]

Efficient management of air quality requires a comprehensive emission inventory to support decision-making on air quality improvement. This article presents a comprehensive framework for detailed emission inventory development in cities with low-quality basic data, which examines the emission of primary criteria pollutants (CO, NO x , SO 2 , PM 2.5 , PM 10 , and VOC) from mobile sources, residential, commercial, and public services, fuel stations, transport terminals, energy conversion sections, and industries. This research was applied to Tabriz in Northwest Iran, one of the polluted medium-sized cities with a population of 1.77 million. Results show the city daily emission per capita is 569.8 g of CO, 68.6 g of NO x , 38.6 g of VOC, 17.6 g of SO x , and 3.7 g of PM. Vehicular emissions accounted for 98% of CO, 91% of VOCs, 61% of NO x , and 56% of PM; meaning alternative policy strategies in vehicles would reduce emissions rapidly. Fifteen applicable and effective scenarios in transport and one concerning stationary sources were proposed and reduction potential of them was evaluated. Effectiveness of the public transport improvement and replacement of old passenger cars were founded the key scenarios. These two alternatives decrease 14 and 2 tons of SO 2 and 6797 and 2394 tons of NO x annually with the cost of $99.5 MM and $366.5 MM, respectively. The findings of this study provides the choice of travel method by each citizen is a function of cost, speed, comfort and safety of travel; therefore, all the requirements of any scenarios must be fully considered in the implementation step. [Display omitted] [ABSTRACT FROM AUTHOR]

Advances in automotive engineering have brought about a range of new vehicle technologies, such as automation, connectivity and electrification, which are expected to have multiple effects on different aspects of people's lives and have the potential of radically transforming the transportation status quo. This paper explores the effects that such new technologies can have on land use by employing a Land Use and Transportation Interaction (LUTI) modelling approach. A new methodology is developed to simulate the effects of automation, connectivity and electrification on accessibility and to conduct a sensitivity analysis. The analysis is carried out on a regional scale to determine the effects of the new technologies on multiple cities that form a region. The case study for this application is the region of the West Midlands (UK). The results suggest that new vehicle technologies can affect accessibility, population and employment in the cities of the region, the region itself, as well as the peripheral zones beyond the boundary of the region in a 15-year modelling period. Most notably, the two main urban cores of the region are found to not lose their financial power, despite increases in employment opportunities and population density in more rural outskirts. The increased accessibility also results in the relocation of lower-income households to places with lower housing rent. The sensitivity analysis shows that these findings are mostly impacted by changes in road capacity (which is expected to be generally higher as a result of these new technologies), as well as different penetration levels in the fleet. • Regional accessibility increases with the existence of new vehicle technologies. • Activity is affected from vehicle automation, connectivity and electrification. • The centres of the largest cities will not lose their financial power. • Activity increases in the peripheral zones of the cities, indicating urban sprawl. [ABSTRACT FROM AUTHOR]

Within the context of climate change and the quest for more sustainable cities, greener urban solutions are gaining traction through emerging concepts that have been orienting municipalities' regeneration and development agendas, including the so-called nature-based solutions (NbS), which have been discussed, planned, and proposed worldwide by academics, NGOs, and policymakers. Comprising different scales and typologies, NbS makes up a modern toolkit of actions towards decarbonized, climate-resilient, and ecologically healthy cities, claiming ample ecological, social, and economic benefits. A literature analysis indicates a greater presence of research and projects focused on NbS in countries in the Global North than in the South; however, given their accelerated urban growth, lack of green areas, and degradation of local environments, cities of the South urgently need such solutions. Nonetheless, research on the effects of urban greening agendas in the Global North has demonstrated that solutions may be entangled with neoliberal practices of space production that exacerbate inequalities, resulting in harmful social impacts such as displacement of people and increases in land and housing costs. This study seeks to build an anticipatory understanding of practices that articulate NbS in the Global South from a Brazilian viewpoint. Given Brazil's reality of social and environmental injustices, we focus on whether implementing NbS could amplify such problems. Our objective is to contribute to the debate by (1) understanding how the NbS concept is being appropriated, in practice, in Brazil, and (2) reflecting and pointing out paths and recommendations on how to plan NbS through a justice lens. • Nature-based solutions (NbS) are spreading rapidly in the Global North. • Empirical work on NbS and the dimensions of justice in the Global South is lacking. • Environmental justice policy and planning are absent from Brazil's NbS projects. • We identify possible undesired social impacts of NbS and preventive measures. • There is a need to include "developing a Just City" as a goal in the planning axis. [ABSTRACT FROM AUTHOR]

Sustainable development goals (SDGs) in the United Nations 2030 Agenda call for action by all nations to promote economic prosperity while protecting the planet. Projection of future land-use change under SDG scenarios is a new attempt to scientifically achieve the SDGs. Herein, we proposed four scenario assumptions based on the SDGs, including the sustainable economy (ECO), sustainable grain (GRA), sustainable environment (ENV), and reference (REF) scenarios. We forecasted land-use change along the Silk Road (resolution: 300 m) and compared the impacts of urban expansion and forest conversion on terrestrial carbon pools. There were significant differences in future land use change and carbon stocks, under the four SDG scenarios, by 2030. In the ENV scenario, the trend of decreasing forest land was mitigated, and forest carbon stocks in China increased by approximately 0.60% compared to 2020. In the GRA scenario, the decreasing rate of cultivated land area has slowed down. Cultivated land area in South and Southeast Asia only shows an increasing trend in the GRA scenario, while it shows a decreasing trend in other SDG scenarios. The ECO scenario showed highest carbon losses associated with increased urban expansion. The study enhances our understanding of how SDGs can contribute to mitigate future environmental degradation via accurate simulations that can be applied on a global scale. [ABSTRACT FROM AUTHOR]

Increased population density is mainly linked to urban and infrastructural expansion. This expansion leads to urban sprawl which is connected to land cover change and social and ecological transformation. Urban boundaries can expand towards cultural and natural heritage sites. This is an evaluation of how our culture and natural heritage affect urban growth and their relation to sustainable tourism which has become an urgent need. The study outlines the development of four cities in Jordan from 1996 to 2020. It also explores the impact of cultural heritage on natural heritage in the delivery of urban city growth and its role in developing sustainable tourism. ​Quantitative method has been used by employing GIS and qualitative method by using case studies. The study concludes with an exploration of the relationship between natural and cultural sites as well as the relationship of tourism and population density with cultural heritage site encroachment. This conclusion has contributed towards the provision of a model that consists of multi recommendations for decision-makers in order to preserve the cultural and natural heritage areas through developing sustainable tourism and creating sustainable communities. The significance of this study is that it is the first study that discusses the increase of encroachment on natural and cultural sites, and the impact of tourism on this. This study also enhances knowledge by providing a tool for evaluating the expected level of preservation for cultural and natural heritage sites, and the extent to which cities are transformed from tourist cities (with populations that pass through) to tourist accommodations cities. [ABSTRACT FROM AUTHOR]

Improving the efficiency with which natural resources are utilized is an indispensable for achieving sustainable development and carbon neutrality. By analyzing the utilization efficiency of energy, water, and land, we established a comprehensive natural resource utilization efficiency index (NRUEI). We then calculated the 2016 index for 165 cities in China, and investigated what caused it to vary. We found three main results: (1) the NRUEI varied greatly across China and there were significant positive correlations between urban energy utilization efficiency (EUE), water utilization efficiency (WUE) and land utilization efficiency (LUE); (2) the NRUEI showed a significant positive correlation with a city's population size, economy (Gross Domestic Product (GDP)), and the level of urban social development (GDP per capita); (3) cities in East China have the highest natural resource utilization efficiency, while cities in Northeast China have the lowest. These results indicate that China's increasing urban development is associated with rising natural resource utilization efficiency and that the city's endowment of natural resources is an important factor affecting that efficiency. Further, the results showed that the determinants of a city's NRUEI differed in large and small cities. Lastly, our results suggest that improving EUE is key for improving NRUEI in urban China, and different efficiencies can be improved intertwined. A major takeaway of this study is that there is great potential for improving natural resource utilization efficiency in Chinese cities and we include city-specific suggestions for efficiency improvements. [Display omitted] [ABSTRACT FROM AUTHOR]

• Women and men experience the same barriers to riding a bike, however women experience additional barriers related to their gender. • Women have specific concerns about riding on the road alongside motor vehicle traffic and the associated risks, and experience confidence-related barriers to participation. • There are opportunities to reduce the gendered inequities in bike riding outside of infrastructural changes. There is substantial potential to improve low rates of bike riding participation in Australian women. Understanding of the barriers to and enablers of riding a bike is essential for planning of urban environments and development of interventions to promote accessible active transport. It is well established that there are differences in the needs and experiences of people of different genders in urban environments, however our understanding of the needs of women who are not yet riding a bike are limited. We aimed to quantify perceived barriers and enablers to riding a bike for transport between women and men, and to explore reasoning behind these. Using a mixed methods sequential explanatory design, we purposively sampled people by age, gender and area of residence in Greater Melbourne, Australia. The sample participated in an online survey of barriers to and enablers of riding a bike. Participants who completed the online survey indicated if they were interested in participating in further qualitative research which aimed to gain a deeper understanding of their attitudes toward, barriers to and enablers of riding a bike. A total of 40 semi-structured interviews were conducted with 20 women and 20 men who were categorised as Interested but Concerned in bike riding. Of the 912 surveys collected, 717 were completed and included in analyses. Significant differences were identified in the barriers and enablers reported between women and men, where more women reported concerns regarding riding on the road. In interviews, more women reported issues relating to a lack of confidence and concern about their safety riding a bike around motor vehicle traffic compared to men. Women have specific concerns about riding on the road alongside motor vehicle traffic and the associated risks, and a lack of confidence in their ability and knowledge of bike riding and bikes themselves. It is imperative that women's perspectives and needs are considered in the planning and promotion of bike riding globally to prevent and tackle gendered inequities. [ABSTRACT FROM AUTHOR]

Traffic flow prediction (TFP) has attracted increasing attention with the development of smart city. In the past few years, neural network-based methods have shown impressive performance for TFP. However, most of previous studies fail to explicitly and effectively model the relationship between inflows and outflows. Consequently, these methods are usually uninterpretable and inaccurate. In this paper, we propose an interpretable local flow attention (LFA) mechanism for TFP, which yields three advantages. (1) LFA is flow-aware. Different from existing works, which blend inflows and outflows in the channel dimension, we explicitly exploit the correlations between flows with a novel attention mechanism. (2) LFA is interpretable. It is formulated by the truisms of traffic flow, and the learned attention weights can well explain the flow correlations. (3) LFA is efficient. Instead of using global spatial attention as in previous studies, LFA leverages the local mode. The attention query is only performed on the local related regions. This not only reduces computational cost but also avoids false attention. Based on LFA, we further develop a novel spatiotemporal cell, named LFA-ConvLSTM (LFA-based convolutional long short-term memory), to capture the complex dynamics in traffic data. Specifically, LFA-ConvLSTM consists of three parts. (1) A ConvLSTM module is utilized to learn flow-specific features. (2) An LFA module accounts for modeling the correlations between flows. (3) A feature aggregation module fuses the above two to obtain a comprehensive feature. Extensive experiments on two real-world datasets show that our method achieves a better prediction performance. We improve the RMSE metric by 3.2%–4.6%, and the MAPE metric by 6.2%–6.7%. Our LFA-ConvLSTM is also almost 32% faster than global self-attention ConvLSTM in terms of prediction time. Furthermore, we also present some visual results to analyze the learned flow correlations. [ABSTRACT FROM AUTHOR]

The high-speed rail (HSR) is one of the most important, if not the most important, emerging transportation that could exert significant influences in many areas, including economic development, social development, financial development, environmental protection, etc. This paper focuses on examining the impacts of HSR on the development of the industrial structure. Since most of the studies in this area are related to central cities (provincial capitals and municipalities directly under the central government), to fill in the gap in the literature, in this paper, we investigate the impacts of HSR on non-central cities in China. To do so, we use the propensity score matching difference-in-difference (PSM-DID) method to investigate the siphoning, spillover, and moderating effects of the opening of the HSR on the development of the industrial structure in the cities along with or nearby the HSR. In addition, we conclude both the robustness tests and the heterogeneity analysis in our study. We find that the opening of HSR significantly promotes the rationalization of non-central cities' industrial structure, as well as improves the advancement of the industrial structure for non-central cities which are less than 100 km away from the central city. Moreover, the four moderating variables, the urban innovation index, the new urbanization construction level, the nearest distance from the central city, and the medical services insurance coverage rate, make the HSR has a positive impact on the rationalization level of industrial structure. Our findings are useful for both central and local governments and policymakers in accurately formulating policies related to the planning and construction of HSR, city planning, and planning the development of the industrial structure for each city nearby the HSR. • Investigate the impacts of HSR on industrial developments for non-central cities. • Propose five hypotheses in terms of the siphoning, spillover and moderating effects. • Construct econometric models and conduct empirical studies to prove the newly proposed hypotheses are correct. • Provide policy suggestions for both central and local governments. [ABSTRACT FROM AUTHOR]

Malezales are hydrophytic grasslands restricted to the province of Corrientes, northeastern Argentina, being considered natural wetlands. Although poorly studied and practically lacking legal protection, which hinders their sustainable management, they are of great economic importance for extensive livestock and forestry industry, in addition to their provision of environmental services and biodiversity. In the last decades, this ecosystem has been the stage of a process of expansion of planted forests, stimulated by policies to encourage afforestation. The present study aimed to estimate and zoning forest expansion over malezales for the year 2050, as well as to evaluate the sustainability of the forest expansion process, considering its conflicts with priority areas for recovery and conservation of the ecosystem. We presented an innovative approach to improve the land use planning in regions with multiple policy-driven conflicts among land uses. Remote sensing tools and geographic information systems were used to map (QGIS), model, project and zone (IDRISI) forestry expansion and its conflicts with areas of environmental interest. The results showed that forest expansion policies caused an intense process of replacing malezales by planted forests, intensely affecting agriculture and livestock and areas of ecological interest. Predictive modeling suggests a worsening of this scenario in 2050. The proposed zoning after conflict identification shows that it is possible to conciliate recovery, conservation and sustainable afforestation of malezales, and serves as a subsidy for planning and decision making. However, its application must be conditioned to further discussions between the actors involved, considering their local and specific needs. • Land-use scenario modeling aids in the planning process for environmental conservation and recovery of degraded areas. • Areas most likely to become forest in 2050 are already forested. • Commercial afforestation pressure over important areas for birds' conservation will increase in 2050. • It is possible to conciliate future commercial forest expansion and the environmental conservation/recovery of malezales. • National policy for forestry expansion needs improvement to avoid high environmental and economic risks. [ABSTRACT FROM AUTHOR]

To halt land take in Europe, the European Union set a "no net land take by 2050″ target in 2011. However, land take continues to occur in European countries, with recent studies suggesting that local decision-making is playing a major role in these land-use conversions. In this study, we investigated how urban growth boundaries (UGBs) are used by local governments to manage urban growth in Romania. A mixed-method approach was adopted, combining analysis of UGB changes over the past decade in all Romanian cities (N = 319) with a survey among representatives of local governments involved in land-use decision-making (N = 91 cities). The results showed that many cities have expanded their UGBs, despite population loss and sufficient undeveloped land within UGBs, showing that local government decisions conflict with policy targets at the European level. This is even the case when there is no physical need for land-take limits to be exceeded. We show that population dynamics and the extent of nature conservation areas significantly contribute to UGB changes, though these explain just a small fraction of all UGB changes. Furthermore, we identified a wide range of motivations among decision-makers regarding changing UGBs, including not only the fiscal system but also cities' competitiveness and decisions about the long-term vision for development. We argue that policy innovations in urban containment should (i) aim to balance the interests of governments at different administrative levels, (ii) account for the particularities of each state member's planning system, and (iii) allow for integrated and strategic city planning. • Urban growth boundaries (UGBs) are continuing to expand despite population loss and sufficient undeveloped land. • Local government decisions conflict with European policy targets relating to no land take. • Motivations for UGB expansion include cities' competitiveness and long-term vision for development. • The study provides a basis for understanding the role of land-use containment instruments in steering urban expansion. [ABSTRACT FROM AUTHOR]

In the context of increasing globalization and global competition, urban mobility in terms of different private Taxi transport projects is gaining relevance. In the last decade, interest in studying the impact of Taxi options on changes in urban mobility and consumer preferences has increased. The most important recent line of study is the development of the dimensions of urban mobility and the possible incorporation of new ones and the Taxi option is one of the most important dimensions in urban mobility dynamism. Therefore, it becomes a necessary task to measure the amount and level of academic work that has been carried out on urban mobility, its dimensions, and the effect that Taxi options may have. So, the main objective of this paper is to examine the current state of urban mobility, carrying out a bibliometric analysis. 6687 research papers published between 1967 and 2021 have been analysed based on the results of the Web of Science Core Collection (WoS), identifying publications and co-authorship among the most recognized authors, the countries with the highest percentage of scientific production, the most prominent citations, the most influential journals, and the co-occurrence of keywords. In summary, the most recurring topics that show the academic development of urban mobility have been identified, guiding on future topics to be incorporated into the study and measurement of urban mobility options, such as Taxi, ride-sourcing, ride-pooling, ride-sharing and others. • Taxi and urban mobility are two key factors for society and two lines of research that are in full development and growing exponentially. • This study thus confirms the great potential of this line of research and the great interest it should generate for the most prestigious journals. • Mobility is a relevant issue for all cities on the planet and generate great interest for the most prestigious journals. • The existence of a line of research related to the study of electric and autonomous vehicles, sustainable development, and the optimization of urban mobility has been observed. [ABSTRACT FROM AUTHOR]

Due to the imbalance between their historic physical buildings and the requirements of its residents, heritage sites are subject to several urban pressures. However, the major potential for urban growth in such locations is in their historic assets. The purpose of this research is to provide an approach for conserving and enhancing urban history in a manner that is beneficial to the environment, society, culture, and economics. Heritage conservation is attempting to distinguish itself. This is due to the fact that conservation and sustainability objectives do not always coincide. The findings are based on research conducted in Mosul and a study of sustainable development's concepts and pillars. With the use of UNDP reports, the present condition in Mosul was determined. The results demonstrate the need of devising a strategy to safeguard historic cities while allowing residents to continue to reside there. This plan should include objectives, strategies, and instruments to ensure that the "historic living city" can adapt and evolve in accordance with the sustainable development principles and the sustainability cycles. The paper uses an inductive methodology to apply sustainable development to historic city centers worldwide. [ABSTRACT FROM AUTHOR]

Key cities represent the strongest competitiveness level of each province and city. At present, the problem of unbalanced development level of key cities in China is more prominent. Improving urban competitiveness has become an urgent problem for urban governments. In order to study the competitiveness of 35 key cities in China, this paper formulates a total of 27 indicators from the five levels of economic development, social undertakings, public infrastructure, ecological environment and technological innovation, and uses measurement software to draw the advantages and disadvantages of relevant urban development. The results show that the top cities in the comprehensive competitiveness of 35 key cities in China include Beijing, Shanghai, Shenzhen and Guangzhou, and the differences among key cities are more prominent in all dimensions. The relative level of competitiveness development of key cities corresponds to the level of regional economic development and technological innovation to a certain extent. [ABSTRACT FROM AUTHOR]

[Display omitted] • Despite higher density in the urban population, woodpigeon individuals were characterised by lower chewing louse abundance. • Birds with lower weights showed higher parasitic loads, which became more noticeable in urban woodpigeons. • Different from rural woodpigeons, parasites typical of feral pigeons were found on urban individuals. • Most of the species found were chewing lice, with Columbicola claviformis and Campanulotes bidentatus being dominant. The type of habitat occupied by avian populations has a marked effect on the parasitises they host. The growth of cities and urban areas in recent decades has favoured some species of birds adapted to these types of habitats – urban exploiters – although the effects of urbanisation on the parasitism of wildlife are not always well known. This study compares the ectoparasites characteristic of two differentiated populations of woodpigeons, one located in a predominantly urban environment and the other in a rural one. Most of the species found were chewing lice, with Columbicola claviformis and Campanulotes bidentatus being dominant. Despite the higher density of the urban population, woodpigeon individuals were characterised by a lower abundance of chewing lice, as well as the presence of ectoparasites typical of feral pigeons such as Hohorstiella lata and the hippoboscids fly , Pseudolynchia canariensis. Similarly, birds with lower weights showed a higher parasitic load, which became more noticeable in urban woodpigeons. The lower ectoparasite load of urban hosts represents a health advantage compared with rural populations, which could be one of the causes of greater growth and reproductive success in urban populations of woodpigeons. [ABSTRACT FROM AUTHOR]

Urban sprawl has led to changes in landscaping. For instance, open areas and green urban spaces (GUSs) 1 1 GUSs: Green Urban Spaces. are replaced by buildings, streets, and infrastructure. Permeable and wet surfaces have also been transformed into non-permeable and dry surfaces. This, unfortunately, creates a major problem known as Urban Heat Islands (UHI). The rise in temperature makes the urban centres warmer when compared to their rural outlying areas. This affects the environmental goodness, energy consumption demands, quality of wellbeing. However, there is limited knowledge concerning the change in the use of GUSs, the relationship between the area of ​​these spaces, and the buildings formation on the exacerbation of the UHI in the cities. The research study aim is to assess the impact of the area of GUSs and the building s formation on the exacerbation of the (UHI) in Baghdad city. The purpose of this study is to improve the understanding of an integrated approach for open green spaces by reviewing city's experience with a main focus of environmental sustainability, cooler temperature, and thermal comfort. The research selected three typical GUSs in Baghdad (Ziyouna) as a case study. Those spaces were transformed into various types of buildings for different uses. The UHI impact is identified and compared in two scenarios (GUSs and added building) using computer climate simulation (ENVI-met) tool. The tool also assessed and measured surfaces and air temperature (CLUHI & SUHI) at different points in the selection of three typical models. The results demonstrated several factors combined with the change of urban land uses that are responsible for exacerbation of UHI in terms of buildings' height, formation, ground coverage, and construction including pavement materials and colour. [ABSTRACT FROM AUTHOR]

This paper develops a scenario analysis and visualization tool for an Integrated Transport, Land-Use and Energy (iTLE) model to spatially analyze and predict changes in transport and land-use environment. The decision support tool operates by taking the iTLE model output data as input which includes residential location of households, individuals' characteristics, and vehicle fleet information. Use of the tool is showcased through a scenario analysis of a 'business as usual (BAU)' projection versus a 'COVID-19 pandemic scenario' for Halifax, Canada. Agent-based microsimulation explores the possible future changes in households' socio-demographic characteristics and travel behaviour in the post-pandemic time. Forecasting up to the year 2025 and comparing between BAU and pandemic scenario shows that, many of the lower median income areas in the BAU projection are estimated to have a much lower median income under the COVID-19 scenario. Furthermore, the COVID-19 scenario only slightly decreases the proportion of the overall population with a transit pass. Under the pandemic scenario, the percentage of households with three or more cars experiences significant growth in urban and suburban areas. Outcomes of this study will offer policymakers a greater understanding of the transformation pattern of urban and suburban neighborhoods in the post-pandemic period. The developed iTLE VIZ tool will allow planners to formulate complex transport and land-use scenarios and simulate them for examining urban systems transformation. [ABSTRACT FROM AUTHOR]

The Latin American region has been marked by a historic process of extractivism and weak institutional structures, causing deep socio-environmental and economic crises. The resaturation of territorial justice has then become the center of the debate. Nature-based solutions, for their innovative and systemic nature, could be key in approaching these complex problems. However, the interplay between these strategies and justice is not clear enough. This article addresses this interaction centering on protected areas, the most traditional response from regional governments to nature degradation. We attempt to test the hypothesis that integrating protected areas in land use planning policies improves the exercise of justice, understanding it from a place-based point of view. To this end, we carried out quali- and quantitative analysis of social perceptions, historical background, land use policies and governance in Tandil and Tornquist, two municipal districts of the Province of Buenos Aires, Argentina. The results showed that i) protected areas were associated with justice if a conservation project reached a legal rule and if the community was involved in its formulation and management; ii) the integration of protected areas in land use planning policies helped to satisfy both conditions. We end by proposing a theoretical model which outlines how three strengths of land use planning can turn PAs into more just NbS. We also discuss the need to develop a broader and place-based approach of justice as "territorial justice". • More comprehensive and place-based senses of justice are necessary. • Territorial justice expresses a decolonizing sense of justice. • Protected areas are a special kind of nature-based solutions (NbS). • Integrating NbS in land use planning (LUP) is key to achieve territorial justice. • LUP's main strengths are being local, participative, comprehensive and justice-oriented. [ABSTRACT FROM AUTHOR]

China has witnessed 556 million people migrating to urban areas over the past three decades with the process of urbanization, which has brought enormous pressure on electricity consumption and urban sustainable development. This paper establishes the generalized Divisia Index Decomposition Method (GDIM) model, and aims to reveal the electricity consumption mechanism of urban residents in China between 2000 and 2018. The results show that residential income, per capita electricity consumption and residential appliances are the main driving factors for the growth of urban residential electricity consumption, while the energy-saving willingness and expenditure structure have the inhibiting effect. With the expansion of urban residential income, the increase in income and air-conditioning numbers will continue to promote the growth of urban residential electricity consumption. Then, this paper puts forward relevant suggestions to alleviate the pressure of electricity demand and sustainable development from urban residents in China. [Display omitted] • The growth of power consumption in residential sector mainly comes from urban areas. • Establish GDIM model to decompose urban residential electricity consumption in China • Income has the greatest driving effect on urban residential electricity consumption. • Air-conditioning is the main source of the effect of household appliances. • Energy-saving willingness inhibits urban residential electricity consumption. [ABSTRACT FROM AUTHOR]

This study proposes a new method for monitoring land cover change in urban areas using all available Landsat time series data, named the Ensemble of Bidirectional Time Series Analysis (EBTSA). In this method, the bidirectional Continuous Change Detection and Classification (CCDC) and the Chow Test are combined to improve the robustness against data scarcity in earlier times and reduce break detection errors and refine classification results. There are three key stages in this method: break detection using bidirectional CCDs, break refinement using the Chow Test, and bidirectional model integration and classification. The EBTSA method was evaluated over the Tianjin metropolitan area in China using Landsat data from 1989 to 2018. Results show that the proposed method improved spatial and temporal accuracies of both land cover classification and change detection, by reducing the influence of sparser Landsat data in the earlier years and the break detection errors. Using the land cover change results in the Tianjin area obtained using the EBTSA method, we analyzed the spatio-temporal distribution of land cover classification and change detection. It is found from the results that the Tianjin area experienced dramatic urban land changes, characterized by rapid urban expansion and noticeable transition from vegetation to urban land, with diverse changes from urban land to various nonurban land cover types. Results of this study showcase the effectiveness of the proposed method in land cover change monitoring in urban areas, which facilitates a more comprehensive understanding of urban land change dynamics and diversity. [ABSTRACT FROM AUTHOR]

Al Ahsa Metropolitan Area (AMA), located in the Eastern Region of Saudi Arabia, has witnessed rapid population growth with remarkable urban expansion during the past few decades due to the discovery of oil. Because of this rapid growth, AMA is currently exposed to many short and long-term social, economic, and environmental challenges that need to be studied and assessed to provide solutions for the betterment of the population. This study examines the historical growth of AMA by using Geographical Information System data and satellite image classification techniques for the last 30 years. The results show that the total urban area of AMA has significantly increased from 199 sq. km. to 276 sq. km. during the past 30 years from 1992 to 2022 with a sharp increase of 25.5 % in the last 10 years only. Statistical analysis of the historical data predicted an increase of 26.8 % in the area of settlements during the next decade up to the Year 2032. After a study of land use maps it was also observed that the increase in settlements caused a decrease in vegetation to 18 % in the last decade. The research presents beneficial statistics which shall help the decision-makers and related authorities in managing the development process in the area in a better and more sustainable manner. [ABSTRACT FROM AUTHOR]

Regional reconstructions of historical cropland change are essential to improve the accuracy of global datasets. In Shaanxi province, central China, frequently affected by rebellions and natural disasters over the past 300 years, the cropland area fluctuated. In this study, based on local gazetteers, statistics, and survey data, systematic steps are followed to reconstruct the cropland area change since 1650 in Shaanxi province. The result shows four stages of changes in the total cropland area: steady increase during 1650–1830 stimulated by policies and population growth, decrease during 1830–1937 affected by wars and natural disasters, rapid growth during 1937–the 1980s, and rapid decrease after the 1980s influenced by urbanization and the agricultural planting structure adjustment. The total cropland area increased from 2.2 × 104 km2 in 1650 to 3.99 × 104 km2 in 2016. The majority of the cropland concentrated on the Guanzhong region from 1650 to 2016. The cropland expanded from the center to the surroundings in the Guanzhong region, from northeastern to southwestern in northern Shaanxi, and from western to eastern in southern Shaanxi before the 1980s. Cropland area declined in all three regions after the 1980s. The comparisons show most cropland area data in the Qing dynasty from the existing regional studies are still highly dependent on the registered tax-paying cropland area. Without considering agricultural history, changes in the SAGE cropland in Shaanxi province over the past 300 years are irrational. Spatially, HYDE 3.2 dataset cannot show the "real" spatial distribution of the cropland before 1930, because too much cropland is allocated to northern and southern Shaanxi. [ABSTRACT FROM AUTHOR]

The maturation of digital(ized) consumption, together with the amplification of cities' initiatives in response to local and global environmental challenges, has placed goods transport, an essential but impactful activity, at the forefront of urban stakeholders' scrutiny. High-performance and low-impact supply chains benefit from the presence of logistics facilities in proximity to goods' destinations. This development of logistics facilities in high-demand areas, which are essentially urban, dense and mixed-use, we term 'proximity logistics'. It is the focus of this article. Proximity logistics entails extending and refining networks of logistics facilities towards urban cores and allows them to counteract some of the undesirable effects that their historic tendency to outward migration (or logistics sprawl) potentially brings about. The phenomenon is established around the world, albeit to different extents. In this article, we discuss the trends supporting proximity logistics' development and present a typology of facilities it could entail, followed by case studies of five cities: New York (United States); Paris (France); Seoul (South Korea); Shanghai (China); and Tokyo (Japan). We characterize the state of practice of logistics facilities in each city's dense, mixed-use areas, compare the characteristics in light of their context and distill learnings in support of sustainable land use patterns. [ABSTRACT FROM AUTHOR]

Since the 20th century, the world is facing two major problems: the serious deterioration of the ecological environment and the accelerated decline of living quality of people residing in the urban environment. Urban development policies, ecological patterns, production and consumption modes have an important impact on global environmental changes that threaten the future living of mankind. The focus of urban space construction has also turned to the fields of ecological security, energy development, resource management and urban ecological virtuous circulation. Investigating urban spatial structure features from the perspective of urban metabolic system is important for ecological security and resource management. Shangluo urban space in Qinling area is used as the research object and an analysis system of urban spatial structure based on ecological network analysis is proposed in this study. First, an ecological network model of urban space was constructed from the research perspective of ecological network analysis and the system metabolic level was evaluated using metabolic scale, intensity, and efficiency. Second, the system structure of urban metabolic network and its functional relations were analyzed. On this basis, interactive relationships among different components in the metabolic system were explored via symbiosis index and symbiotic, competitive, predatory, and control relations. Meanwhile, the ecological network analysis method is used to construct an analysis system for urban spatial structure in the Qinling mountain area. Finally, the analysis system of urban spatial structure in the Qinling mountain area is applied to examine the urban spatial structure of Shangluo, Qinling Mountains, China. Results showed that resource utilization efficiency of Shangluo City presents a rising trend and the city is located in a strong structural center in the regional space. Predatory and control relations played a dominant role among ecological relations in the urban metabolic structure, and the urban space presented a clear uniaxially extended spatial structure. Sensitivity of internal environment was extremely evident, and the natural spatial structure was an important basis for urban space development in Shangluo. The urban spatial structure analysis system in this research is constructed with the three aspects of "metabolic level", "ecological relationship" and "compartment weight" of the spatial structure information, which solves the problem that the conventional spatial structure analysis system is difficult to quantify the ecological network information, and it provides a new idea to explain the internal component interaction mechanism and spatial structure composition of the urban system. The results of this study can provide not only useful reference for urban spatial structure analysis of underdeveloped ecological capital areas in China but also a basis for sustainable development planning of urban spaces. [ABSTRACT FROM AUTHOR]

• China's central government balances local autonomy and central regulation. • Decentralization and centralization are used to explore flexible governance under the authoritarian system. • Goal-oriented governance employs hierarchical planning and experimentation. • Feedback about decentralization from local government influences state decisions. • Local policy-making and urban governance as a wavering multi-level interaction process. This study views decentralization and centralization as complementary strategies for balancing state control and local autonomy, with the goal of exploring effective governance under authoritarian regimes. We examine the governance framework the central government employs to balance "encouraging local autonomy" and "protecting the centrality of regulation," analyzing urban development and the central-local interaction under this governance framework. We believe that goal-oriented governance with information transmission at its core is the key to reaching such equilibrium, accompanied by two critical governance techniques: hierarchical planning systems and decentralized experimentation. The hierarchical planning system, with the auxiliary evaluation mechanism, passes down national goals and provides administrative guidance to local governors. Meanwhile, the procedural and experimental nature of plan formation has encouraged local policy innovation and bottom-up information feedback. Under goal-oriented governance and manageable experimentation, urban development decisions are formulated, and urban transformation takes place. The study deepens our understanding of the tentative nature of China's state rescaling, i.e., the search for a balance between state control and local autonomy to defuse governance problems at a given time. It also broadens our understanding of China's policy-making and urban governance as a wavering multi-level interaction rather than a dichotomous process of centralization and decentralization. [ABSTRACT FROM AUTHOR]

Peri-urban areas provide both challenges and opportunities for agricultural production, often generating complex multifunctional landscapes and high levels of farm diversification. In Australia, this complexity reflects the interplay of factors affecting farmer decision-making against a backdrop of limited government support for farmers and some of the world's most extensive urban sprawl. Drawing on data from a sample of farms in South Australia's Adelaide Hills, part of the peri-urban fringe of the state capital, Adelaide, this analysis uses the concept of farm business trajectories and path dependence to investigate how different types of farmers are shaping multifunctionality. Using a sequential mixed methods approach that combines a questionnaire survey and in-depth interviews, the research investigates alternative farming pathways and conceptualises both negative and positive aspects of path dependency. Applying a two-step cluster analysis, seven different groups of farmers are recognised in terms of recent and intended changes to their farming system. A clear distinction is drawn between commercial, productivist enterprises and the semi- or non-commercial smallholdings that are contributing to growing landscape fragmentation. The growth of farm-based tourism and processing, alternative food networks, and amenity lifestyles are portrayed as part of a spectrum of farm pathways nested within the multifunctional peri-urban landscape. Some 'lock in' mechanisms are supporting adaptation to changing socio-economic and land use conditions, while others are hindering opportunities for sustainable outcomes, but together the complexity of multifunctional agriculture is adding to regional resilience. • Multifunctional agriculture (MFA) comprises diverse farm-based enterprises. • Path dependence, inertia and lock-in contribute to varied farming trajectories. • Within MFA productivist trajectories contrast with less commercial alternatives. • Distinctive farm clusters contribute differentially to MFA implying diverse futures. • MFA in the peri-urban fringe involves deagrarianisation and landscape fragmentation. [ABSTRACT FROM AUTHOR]

As one of the central cities in the Wuling Mountains, Huaihua is regarded as the main body and core economic development area in the process of Wuling's future new urbanization, exerting a pivotal influence on the five provincial border areas (Hunan, Hubei, Chongqing, Guizhou and Guangxi). But studies on urban expansion in this city are few, so this paper makes efforts to simulate its urban land expansion by constructing the Cellular Automata model (the Weight-CA model) taking into account differences in land types conversion. Firstly, the paper obtains the time-series Landsat spectral bands (Red, NIR) and NDVI images using the time–space fusion model; then the optimal combination of classification features is screened based on J Bh distance and the object-oriented random forest algorithm is applied for land cover classification; the paper finally constructs the Weight-CA model for the simulation and validation of urban land expansion in Huaihua. Study results in the paper have shown that the Landsat spectral bands obtained with the ESTARFM have a relatively high correlation with real Landsat images. The land cover classification based on the optimal classification feature combination and the object-oriented random forest algorithm is high in accuracy, the total of which exceeding 84 % over 4 years. Meanwhile, based on the Weight-CA model, the simulation accuracy of urban land expansion in Huaihua in 2010 and 2015 reached 89.98 % and 89.60 % compared with the real values. It is operationally ready and practical and of strong practical significance to extract land cover types by Landsat and MODIS data fusion, and simulate urban land expansion using the Weight-CA method. [ABSTRACT FROM AUTHOR]

Research on the evolutionary ecology of urban areas reveals how human-induced evolutionary changes affect biodiversity and essential ecosystem services. In a rapidly urbanizing world imposing many selective pressures, a time-sensitive goal is to identify the emergent issues and research priorities that affect the ecology and evolution of species within cities. Here, we report the results of a horizon scan of research questions in urban evolutionary ecology submitted by 100 interdisciplinary scholars. We identified 30 top questions organized into six themes that highlight priorities for future research. These research questions will require methodological advances and interdisciplinary collaborations, with continued revision as the field of urban evolutionary ecology expands with the rapid growth of cities. The impact of urbanization on biodiversity has been well documented, yet research into the complex dynamics of ecological and evolutionary processes in urban areas is still in its infancy. When novel research challenges emerge, a horizon scan exercise is an integrated approach that brings together global interdisciplinary-minded individuals to identify future research questions that can influence new collaborations and funding agenda. Our horizon scan identified 30 questions for future research in urban evolutionary ecology covering themes in fundamental ecological and evolutionary processes, temporal and spatial scales, sustainability, climate change, sociopolitical and ethical considerations, and innovation in technology. [ABSTRACT FROM AUTHOR]

• A deep freight-on-rail-transit strategy is proposed to integrate urban transport. • Drivers and barriers to deep FoRT strategy are identified. • Suitability of MRT-based integrated logistics system adoption in China is assessed. • Influencing factors of project adoption and policy implications are suggested. • Government support and public–private partnerships are critical to project success. Integrating goods movement into public/mass rapid transit (MRT) is an emerging initiative to improve urban freight transport services and sustainability. This paper explores new prospects to achieve extensive non-road city logistics based on a deep freight-on-rail-transit (FoRT) strategy. To begin, the strengths, weaknesses, opportunities, and threats (SWOT) of deep FoRT are analyzed in view of the development status quo of urban China. Next, a multi-criteria assessment model driven by real-world data and 11 quantified metrics is proposed to judge the suitability for developing the MRT-based integrated logistics system (MILS) in 16 Chinese cities. Finally, critical factors influencing MILS project adoption are explicated, and the possible supportive policies are discussed from aspects of planning, regulation, funding, marketization, and innovations. Results show that the alignment with national development goals, rich social-environmental benefits, and stakeholder interest are the primary drivers of deep FoRT strategy, whereas poor planning and decision-making, governance and management deficiencies, and high investment could be the main hurdles. Priority of MILS project adoption in the selected cities is divided into four tiers, where Shanghai, Beijing, and Shenzhen are recognized as the three best candidates. Strong and coordinated policies are needed to integrate the strategy into urban planning. [ABSTRACT FROM AUTHOR]

With the acceleration of urban expansion, urban change detection (UCD), as a significant and effective approach, can provide the change information with respect to geospatial objects for dynamic urban analysis. In recent years, through the use of machine learning and artificial intelligence, change detection methods have gradually developed from the traditional pixel-based comparison methods in the 1980s to data-driven deep learning methods. Deep learning methods have huge advantages in the application of remote sensing big data, by virtue of their huge feature extraction and expression capabilities. Many change detection datasets have been released to meet the requirements of deep learning. However, the existing datasets suffer from three bottlenecks: (1) the volume of the datasets is small, which can easily cause overfitting; (2) most datasets have a spatial resolution of meters, making it difficult to detect changes in small objects because there are multi-scale objects in urban areas; and (3) most of the datasets have been designed for binary change detection (BCD), and lack semantic annotation, so that they cannot be used to obtain the direction of the change or to analyze the type of change, for further application in urban areas. Therefore, it is difficult to apply these datasets to detect large-scale urban semantic changes in complex environments. To address these issues, a large-scale ultra high resolution (0.1 m) UCD dataset for deep learning based BCD and semantic change detection (SCD) is introduced in this article, which is named the Hi-UCD dataset. We selected an area of 102 m2 in Tallinn, the capital of Estonia, as the study area. There are a total of 40800 pairs of 512 × 512 patches, nine types of land cover and 48 types of semantic change in the Hi-UCD dataset. We developed three metrics–binary consistency, change area consistency and no-change area consistency–to evaluate the semantic consistency of the SCD methods from different aspects. A comprehensive analysis and investigation is provided in this article after we benchmarked this dataset using deep learning methods for BCD and SCD. We also found that the unchanged samples can help distinguish the changed area, and HRNet used as the backbone to construct a multi-task model can perform well in the Hi-UCD dataset. Meanwhile, the visualization results obtained with the Hi-UCD test set, which is a large geographic area covering 54 km2, are shown to reflect the real-world urban application scenarios. The experimental results show that the Hi-UCD dataset is a challenging yet useful benchmark dataset, which can be used for analyzing large-scale refined urban changes. [ABSTRACT FROM AUTHOR]