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In insects, different pigments, such as melanins and pterins, are involved in thermoregulation. The degree of melanisation often varies along geographical gradients, according to the so-called thermal melanism hypothesis, i.e. darker forms are found in colder places because they can warm up more quickly. Similarly, pterins work as heat sinks and thus are expected to be more abundant in colder sites. Cities, which are warmer than surrounding areas (Urban Heat Island (UHI) effect), might also be expected to influence pigmentation, although studies are lacking. Here, we sampled workers of the social paper wasp Polistes dominula (Christ, 1791) (Vespidae) across an urbanisation gradient in an Italian metropolis and used iNaturalist pictures of this species across Italy to study pigmentation patterns at both urban and larger geographical scales. We found a lower yellow intensity of abdominal spots at warmer locations. Scanning Electron Microscopy strongly suggested that yellow colouration is due xanthopterin, known to be the heat sink molecule in other social vespids. Thus, wasps from warmer (i.e., urban) environments are likely to have fewer xanthopterin granules, in line with the lack of need for heat storage due to the local thermal gradient (UHI effect). At the country level, we found that wasps at higher latitudes had smaller yellow spots on the thorax and only two spots instead of four at higher altitudes, in full accordance with the thermal melanism hypothesis. In conclusion, climatic conditions seem to affect insect colour patterns both along urban and wider geographical gradients, although colour changes may affect different body parts and pigments likely according to different needs. • In urban hotter sites, workers show lower intensity of yellow pigmentation (xanthopterin). • Along an urbanisation gradient, there was weak consistence with the thermal melanism hypothesis. • Along the same gradient, there was a likely lack of need for heat storage due to the urban heat island effect. • At country level, latitudinal variations in yellow spots were in accordance with the thermal melanism hypothesis. [ABSTRACT FROM AUTHOR]

Travelers often change their behavior in reaction to adverse weather conditions. This paper seeks to conduct an empirical evaluation of both ordered and unordered discrete outcome frameworks for examining the adaptive behavior decisions of intercity travelers and investigate the varying effects of explanatory factors on different alternatives of adaptive behavior during adverse weather. The data from 754 respondents in the Beijing-Tianjin-Hebei urban agglomeration, China are collected by a two-phase survey instrument. To capture the unobserved heterogeneity more effectively, this paper develops three advanced models to investigate the variations in intercity travel behavior during adverse weather. Four alternative adaptive behaviors are determined as outcome variables: maintaining original travel plans, changing only the intercity mode, changing the departure date, and canceling the trip, while potential influencing factors including adverse weather conditions, trip-related characteristics, individual attributes and urban agglomeration attributes are statistically assessed. The results indicate that the unordered models consistently outperform their ordered counterparts, and the incorporation of multilayer heterogeneity enhances the model fit. Furthermore, significant factors and their coefficient values vary across the different adaptive behavior alternatives. Intercity travelers demonstrate a higher probability of changing departure dates or canceling trips during snowy and windy days compared to rainy and foggy days. Trains exhibit higher flexibility and reliability during adverse weather, and access attributes significantly affect intercity travel adaptive behavior. Additionally, the analysis of individual and urban agglomeration attributes uncovers variations in adaptive behavior among individuals and cities. These findings provide profound insights into the complexities and variations of intercity travel behavior during adverse weather, and propose practical strategies to mitigate the detrimental impacts of adverse weather on intercity travelers. • Adaptive behavior of intercity travelers during adverse weather is investigated. • Unordered framework outperforms ordered counterparts in adaptive behavior study. • Multilayer unobserved heterogeneity in the adaptive behavior is accounted for. • The varying effects of explanatory factors on different adaptive alternatives are examined. • Practical strategies are proposed to mitigate negative impacts of adverse weather. [ABSTRACT FROM AUTHOR]

• Field experiment in mandatory recycling scheme tests effectiveness of door stepping. • Majority of households in mandatory recycling schemes separates waste correctly. • Minority of households is responsible for most miss sorting. • Door stepping does not influence behavior of households in mandatory schemes. • Door stepping can improve recycling behavior in voluntary recycling schemes. Household organic waste has great potential for closing nutrient cycles in agriculture. This requires proper waste separation by households. Personal communication at the doorstep potentially improves household waste separation behaviour but it is expensive and findings from existing research are mixed. Based on results of previous studies and from a quasi-experiment with non-equivalent groups design in two German municipalities, this paper argues that efficiency of personal communication depends on its context. It can positively influence behaviour when recycling is voluntary and participation rates are low. However, it has no significant effects if recycling is mandatory. One explanation could be different perceptions of recycling in mandatory and voluntary schemes. In voluntary schemes door stepping can activate the intrinsic motivation of households. In mandatory schemes, all households need to participate irrespective of intrinsic motivation. This research shows that this creates a situation in which a small share of households is responsible for almost all contamination. This can be overcome by considering extrinsic factors that affect recycling behaviour. The paper recommends further research to understand which combination of incentives, sanctions and information is efficient in affecting behaviour change in mandatory recycling schemes. [ABSTRACT FROM AUTHOR]

As a trending mobility choice, e-scooters have become popular in many cities. A number of authorities have initiated shared e-scooter trial schemes to assess the feasibility of the vehicles prior to enacting official legalisation. This paper aims to provide an evidence review of shared e-scooters and investigate how existing evidence may inform long-term policies. This carries significant relevance for jurisdictions that are in a conflicting position with e-scooters, such as New South Wales (NSW), Australia whose context motivates this study. The evidence review focuses on three themes derived from experience with shared e-scooters within the broader micromobility landscape, namely: safety; where shared e-scooters fit into the modal landscape; and the environmental impacts. Findings confirm that ensuring the safety of shared e-scooters requires complex solutions, which may include a clear regulatory framework for e-scooters, safety education and skill training, innovative data collection and analysis methods, and an approach to safety management that is user-based, location-based, and time-based. In terms of modal fit policymakers should encourage first and last-mile combinations with public transport, with consideration of user characteristics; while climate impact is strongly correlated to the mode replaced by e-scooter trips. The paper provides insights for policymakers on the regulation and positioning of shared e-scooters. • Many jurisdictions are struggling to determine policies for e-scooters. • Existing e-scooter evidence sheds light on possible long-term policies. • Safety management should consider different users, locations, and times. • First and last-mile combinations with public transport should be encouraged. • Climate impact is strongly correlated to the mode replaced by e-scooter trips. [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]

Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

On-demand transit (ODT) has been widely piloted in recent years by many transit agencies in response to changing travel behaviour and preferences among people. Some agencies have adopted ODT to replace underperforming bus routes, as part of a continuous service planning process while others incorporated it within network re-design. All these trends highlight the critical need for transit agencies to have guidance for incorporating ODT into transit network planning both at the strategic, tactical, and service planning levels. Thus, the purpose of this research is to provide a discussion of the key guiding principles to facilitate the development of transit networks with integrated on-demand and scheduled services. To achieve this goal, a thorough review of the states of practice and research was conducted. Findings from the practice review were also reinforced through ODT practitioners' engagement in Canada. This paper provides discussions on the service goals and objectives of an integrated network design and highlights the key planning requirements for developing integrated networks. At the service planning level, the paper provides a discussion on service goals, service design parameters, and scenario development of ODT service. • On-demand transit (ODT) have grown in many cities around the globe, mostly as pilot projects. • Review of the literature and practice shows that planning for ODT is based on best practices , without "built" guidelines. • Principles of planning are discussed within two applications, the network design level, and the service planning level. • Opportunities of integration and mode selection criteria are defined to integrated ODT with existing bus network. • Simulation and analytical tools are useful to complement the principles of planning in the decision-making processes. [ABSTRACT FROM AUTHOR]

With the rapid advancement of 3D sensors, there is an increasing demand for 3D scene understanding and an increasing number of 3D deep learning algorithms have been proposed. However, a large-scale and richly annotated 3D point cloud dataset is critical to understanding complicated road and urban scenes. Motivated by the need to bridge the gap between the rising demand for 3D urban scene understanding and limited LiDAR point cloud datasets, this paper proposes a richly annotated WHU-Urban3D dataset and an effective method for semantic instance segmentation. WHU-Urban3D stands out from existing datasets due to its distinctive features: (1) extensive coverage of both Airborne Laser Scanning and Mobile Laser Scanning point clouds, along with panoramic images; (2) containing large-scale road and urban scenes in different cities (over 3. 2 × 1 0 6 m 2 area), with richly point-wise semantic instance labels (over 200 million points); (3) inclusion of particular attributes (e.g., reflected intensity, number of returns) in addition to 3D coordinates. This paper also provides the performance of several representative baseline methods and outlines potential future works and challenges for fully exploiting this dataset. The WHU-Urban3D dataset is publicly accessible at https://whu3d.com/. [ABSTRACT FROM AUTHOR]

This paper develops a spatial equilibrium model for a competitive two-city system consisting of a high-income and a low-income city. Using this model, we investigate the effects of intracity and intercity commuting subsidies on such urban performances as spatial structures, residents' utility, and social welfare of cities and the system. The three unilateral subsidy scenarios and two subsidy competition scenarios are investigated individually. Results show that intercity commuting subsidy gives residents incentives to reside in the low-income city and intercity commuting to the high-income city, while intracity commuting subsidies lead to the inflow of population. Subsidy competitions increase residents' utility and mitigate the impacts of unilateral subsidies on the social welfare of the system. A numerical example and case study based on city pairs of Jing-Jin-Ji Urban Agglomeration in China are conducted to examine the proposed model. • Establish a spatial equilibrium model in a competitive two-city system. • Investigate the effects of unilateral intracity and intercity commuting subsidies on urban performances. • Explore the subsidy competitions between cities and compare results with unilateral subsidies scenarios. • Provide a case study based on Jing-Jin-Ji Urban Agglomeration in China. [ABSTRACT FROM AUTHOR]

Airborne hyperspectral images can be used to map the land cover in large urban areas, thanks to their very high spatial and spectral resolutions on a wide spectral domain. While the spectral dimension of hyperspectral images is highly informative of the chemical composition of the land surface, the use of state-of-the-art machine learning algorithms to map the land cover has been dramatically limited by the availability of training data. To cope with the scarcity of annotations, semi-supervised and self-supervised techniques have lately raised a lot of interest in the community. Yet, the publicly available hyperspectral data sets commonly used to benchmark machine learning models are not totally suited to evaluate their generalization performances due to one or several of the following properties: a limited geographical coverage (which does not reflect the spectral diversity in metropolitan areas), a small number of land cover classes and a lack of appropriate standard train/test splits for semi-supervised and self-supervised learning. Therefore, we release in this paper the Toulouse Hyperspectral Data Set that stands out from other data sets in the above-mentioned respects in order to meet key issues in spectral representation learning and classification over large-scale hyperspectral images with very few labeled pixels. Besides, we discuss and experiment self-supervised techniques for spectral representation learning, including the Masked Autoencoder (He et al., 2022), and establish a baseline for pixel-wise classification achieving 85% overall accuracy and 77% F1 score. The Toulouse Hyperspectral Data Set and our code are publicly available at www.toulouse-hyperspectral-data-set.com and www.github.com/Romain3Ch216/tlse-experiments/ , respectively. [ABSTRACT FROM AUTHOR]

• Broadband infrastructure significantly boosts urban innovation. • Internet penetration rate and information technology (IT) industry are the two impact channels. • The influence of broadband infrastructure on urban innovation has significant heterogeneity. • Broadband infrastructure has a stronger effect on radical innovation than on incremental innovation. • The impact of broadband infrastructure on urban innovation has spatial spillover effect. Broadband infrastructure plays a key role in supporting innovation. This paper takes the "Broadband China" demonstration policy as a quasi-natural experiment, adopts the data of 284 cities and multi-phase Difference-in-Differences (DID) approach to explore the impact of broadband infrastructure on urban innovation. We find that broadband infrastructure significantly boosts urban innovation, the increase of internet penetration rate and the development of information technology industry are the two influence channels. Heterogeneity tests show that the boosting effect of broadband infrastructure on innovation are stronger in eastern cities, large cities, key cities and cities with better educational resources. We also find that broadband infrastructure plays a stronger role in promoting radical innovation than incremental innovation, and the "Broadband China" demonstration policy produces a positive spillover effect on nearby cities' innovation. [ABSTRACT FROM AUTHOR]

• A distribution dynamics approach is employed to examine the converge of TFEE across Chinese PAA level cities. • The findings show a clear convergence in TFEE. • Convergence comes more from efficiency drops in high TFEE cities than from efficiency gains in low TFEE cities. • The environmental protection polices in key cities improved energy efficiency. • Large-sized cities show better performance in energy efficiency than small- and medium-sized cities. Improving energy efficiency is considered the most direct route to reducing carbon emissions on a massive scale. To examine the long-run trend of China's energy efficiency, this paper employs a distribution dynamics approach to analyze the convergence of total-factor energy efficiency (TFEE) across 286 Chinese cities between 2002 and 2014. The result suggests the existence of convergence, which comes more from the efficiency declines in the high TFEE cities rather than the efficiency gains in the low TFEE cities. Despite the fact that a few cities have performed well in energy efficiency, the majority of cities have converged to a low-efficiency point. Further analyses show that the inefficiency was attributed to inefficient energy use in small- and medium-sized cities. Our analysis provides strong scientific support for China's ongoing energy conservation and environmental protection policies. [ABSTRACT FROM AUTHOR]

• Introduced SWM 4.0 by considering Industry 4.0 technologies in waste management. • Reviewed I4.0 role in waste types, processes, and strategies of waste management. • Developed SWM 4.0 framework through smart factories, cities, businesses, and people. Smart Waste Management (SWM) discusses the waste management process for different types of waste while introducing an intelligent approach to controlling the amount of waste. This paper introduces SWM4.0, which applies Industry4.0 (I4.0) technologies in various related events. First, the paper presents a systematic literature review on the role of I4.0 technologies in SWM activities regarding waste types, waste management processes, and 5R strategies. Then, existing solutions supporting SWM4.0 are extracted to develop a framework for exploring the use of I4.0 technologies. This framework includes sharing the four main pillars that contribute to the success of SWM4.0, namely smart people, smart cities, smart enterprises, and smart factories. Furthermore, this review suggests the possibility of unifying and extending existing solutions and identifying the necessary links and interfaces for researchers. For managerial implications, the framework identifies future strategies to fulfill specific SWM tasks and to foster new technological solutions for future research. [ABSTRACT FROM AUTHOR]

The identification of the technical cooperation mode in the field of hydrogen energy is of great importance in guiding technological innovation. Based on the social network analysis (SNA) and spatial network method, this paper constructs the technical cooperation graph of China's industry-university-research (IUR) tripartites in the field of hydrogen technology. Based on the performed graphs, it shows the game and evolution of hydrogen technology innovation in three stages, respectively 2000–2010, 2011–2015 and 2016–2019. Meanwhile, this paper calculates the changes of network indicators and found that: (1) the network density showed a downward trend, from the initial 0.062 to 0.003. (2) The degree centrality of the network decreased from 14.7% to 5.7%. (3) The average path length and clustering coefficient indicate that the internal connections within the network were relatively close from 2000 to 2010, and had small-world characteristics. From 2016 to 2019, although the clustering coefficient increased, the average path length also increased significantly, indicating that the internal connections of the network did not become closer. From the network characteristics, the collaborative innovation network of China's hydrogen energy industry continues to expand in scale and scope, and the cooperation relationship is stable. However, it shows the characteristics of low network density and loose cooperation relationship, gradually developing into a scale-free network. Developed provinces and cities in North and East China occupy core positions in the industry-university-research network, while other regions are gradually expanding their cooperation efficiency; however, the overall cooperation frequency is relatively low in Northeast China, and most provinces and cities in South and Northwest China are in edge positions with poor collaboration capabilities. • Network analysis sheds light on China's hydrogen energy tech cooperation via patent. • Collaborative innovation in hydrogen technology evolves through three stages. • Tight internal connections with small-world properties seen in network (2000–2010). • Network's internal connections didn't become closer (2016–2019). • Network transforms from a stable and expanding structure into a scale-free network. [ABSTRACT FROM AUTHOR]

It is no secret that decision-making around mass transit infrastructure can be highly political. Transport policy research, however, has tended to view political dynamics mainly as barriers. There is a need to better understand how and under what conditions political interests and institutions can enable mass transit projects, especially in cities which are not yet locked into car-centric transport systems. This paper addresses this gap with new inductive evidence from 32 expert interviews on the politics of bus rapid transit (BRT) in low- and middle-income countries. It develops two novel analytical frameworks, one on the politics of system adoption and another on the politics of system durability. The first framework highlights how BRT proposals often pitch broad but shallow political support against narrow yet deep political opposition. This renders them inherently contentious. Proposals move forward when their implementation generates political benefits for powerful decisionmakers. The second framework challenges the conventional view that BRT systems prove durable when their operations perform well. Instead, it posits that systems endure when their operations mitigate or adapt to adverse political feedback. The paper offers a novel holistic perspective on how to understand the politics of BRT, and presents a critical intervention in the BRT literature which has tended to focus on isolated political dynamics, such as the need for a local champion or resistance from paratransit operators. • Political analysis can strengthen policymaking for mass transit development. • BRT proposals often pitch broad, shallow support against narrow, deep opposition. • Proposals move forwards when they generate political benefits for decisionmakers. • BRT operations, in turn, often suffer from adverse political feedback. • BRT systems prove durable when operations mitigate or adapt to political feedback. [ABSTRACT FROM AUTHOR]

For freight and servicing movements entering a city, parking provides the access enabling service to customers. This will invariably occur on the street in parking spots or in modern buildings in off-street facilities. In light of changing urban planning priorities and as a result, declining on-street loading zone spaces, this paper explores the provision and challenges of off-street loading docks to support freight and servicing task activity in major urban centres. While it may not be fully appreciated, provisions to adequately accommodate a city's generated freight task is critical to urban planner's broader objectives. As a non-discretionary transport task, freight vehicles will continue to enter cities. If good off-street loading dock facilities are not provided, vehicles will seek out legitimate or illegal on-street parking, and urban planner's place making objectives are likely to be compromised. The paper first considers the planning approaches that govern the provision of loading docks. This paper focuses on Sydney but draws on comparisons primarily to the Borough of City of London. Based on recent observations in Sydney, it then considers various stakeholder perspectives towards loading dock provision and use. Modelling approaches to forecast better requirements that could assist to overcome the planning issues faced are then outlined. The paper concludes with actions taken to address the challenges. • Lack of tools for planning loading docks leads to conflict between developers and government. • Poor provision of loading docks in new developments can compromise urban planning objectives. • Regression and clustering analysis techniques allow the capacity of loading docks and their levels of service to be estimated. [ABSTRACT FROM AUTHOR]

Introduction : In pursuit of sustainability goals, many cities are introducing measures to increase the usage of bicycles as a means of transportation. City planners aim to ensure that this increase does not lead to an increase in crashes, but must make corresponding infrastructure decisions with limited information. Sufficient data to perform a statistical analysis of location-specific crash frequencies is rarely available. For example, only approximately 10% of all bicycle crashes are reported to the police (Shinar et al., 2018). Therefore, urban planners often rely on expert opinion, which may lead to suboptimal prioritization and realization of infrastructure improvements. Method: This paper demonstrates how surveys on bicycle crashes can be used to aid urban planners in making infrastructure decisions. In addition to confirming the location and characteristics of reported crashes, surveys can uncover characteristics of crashes that are not reported to the police, situations in which a crash almost occurred, and locations perceived by cyclists to be dangerous. Surveys also allow urban planners to investigate non-infrastructure related causes of crashes, such as the frequency with which individual cyclists use other modes of transportation. Practical Applications: The usefulness of surveys in the determination of urban cycling safety is demonstrated in this paper through analysis of survey results from the city of Zurich in 2018. [ABSTRACT FROM AUTHOR]

In the path version of the Travelling Salesman Problem (Path-TSP), a salesman is looking for the shortest Hamiltonian path through a set of n cities. The salesman has to start his journey at a given city s , visit every city exactly once, and finally end his trip at another given city t. In this paper we show that a special case of the Path-TSP with a Demidenko distance matrix is solvable in polynomial time. Demidenko distance matrices fulfill a particular condition abstracted from the convex Euclidian special case by Demidenko (1979) as an extension of an earlier work of Kalmanson (1975). We identify a number of crucial combinatorial properties of the optimal solution and design a dynamic programming approach with time complexity O (n 6). [ABSTRACT FROM AUTHOR]

Novel view synthesis (NVS) of urban scenes enables the exploration of cities virtually and interactively, which can further be used for urban planning, navigation, digital tourism, etc. However, many current NVS methods require a large amount of images from known views as input and are sensitive to intrinsic and extrinsic camera parameters. In this paper, we propose a new unified framework for NVS of urban scenes with fewer required views via the integration of scene priors and the joint optimization of camera parameters under an geometric constraint along with NeRF weights. The integration of scene priors makes full use of the priors from the neighbor reference views to reduce the number of required known views. The joint optimization can correct the errors in camera parameters, which are usually derived from algorithms like Structure-from-Motion (SfM), and then further improves the quality of the generated novel views. Experiments show that our method achieves about 25. 375 dB and 25. 512 dB in average in terms of peak signal-to-noise (PSNR) on synthetic and real data, respectively. It outperforms popular state-of-the-art methods (i.e., BungeeNeRF and MegaNeRF) by about 2– 4 dB in PSNR. Notably, our method achieves better or competitive results than the baseline method with only one third of the known view images required for the baseline. The code and dataset are available at https://github.com/Dongber/PriNeRF. [ABSTRACT FROM AUTHOR]

Street view imagery (SVI) is instrumental for sensing urban environments, benefitting numerous domains such as urban morphology, health, greenery, and accessibility. Billions of images worldwide have been made available by commercial services such as Google Street View and crowdsourcing services such as Mapillary and KartaView where anyone from anywhere can upload imagery while moving. However, while the data tend to be plentiful, have high coverage and quality, and are used to derive rich insights, they remain simple and limited in metadata as characteristics such as weather, quality, and lighting conditions remain unknown, making it difficult to evaluate the suitability of the images for specific analyses. We introduce Global Streetscapes — a dataset of 10 million crowdsourced and free-to-use SVIs sampled from 688 cities across 210 countries and territories, enriched with more than 300 camera, geographical, temporal, contextual, semantic, and perceptual attributes. The cities included are well balanced and diverse, and are home to about 10% of the world's population. Deep learning models are trained on a subset of manually labelled images for eight visual-contextual attributes pertaining to the usability of SVI — panoramic status, lighting condition, view direction, weather, platform, quality, presence of glare and reflections, achieving accuracy ranging from 68.3% to 99.9%, and used to automatically label the entire dataset. Thanks to its scale and pre-computed standard semantic information, the data can be readily used to benefit existing use cases and to unlock new applications, including multi-city comparative studies and longitudinal analyses, as affirmed by a couple of use cases in the paper. Moreover, the automated processes and open-source code facilitate the expansion and updates of the dataset and encourage users to create their own datasets. With the rich manual annotations, some of which are provided for the first time, and diverse conditions present in the images, the dataset also facilitates assessing the heterogeneous properties of crowdsourced SVIs and provides a benchmark for evaluating future computer vision models. We make the Global Streetscapes dataset and the code to reproduce and use it publicly available in https://github.com/ualsg/global-streetscapes. [Display omitted] • Largest labelled dataset, with 346 attributes that characterise street photos. • Baseline models and ground truth labels for benchmarking computer vision models. • Reproducible framework to sample and enrich SVIs from cities all around the world. • In-depth discussion of how the dataset could drive novel research questions. • Taking forward the work of Mapillary and KartaView, and their contributors. [ABSTRACT FROM AUTHOR]

There is an ongoing process that greenhouse gas emissions of transport will be incorporated in the European Emissions Trading System. The cap-and-trade approach will result in substantial price increases for fossil fuels which will affect affordability of the transport systems. Within this paper the regressive effect on car-owning households is described in different area categories of the urban and rural region in Germany. Equal-per-household redistribution of the carbon revenue could reverse the regressive effect into a progressive effect. However, there is substantial variation within the different economic status groups leaving notable shares of households with a very low economic status without a positive net transfer. This share will be lowest in the metropolises of the urban region and highest in small-sized cities/village areas of the urban and rural region. Particularly in the latter area categories, these households may need temporary mobility allowances due to limited abatement options. Despite the environmental bonus, electric car-owning households still belong to groups of higher economic status, and public transport supply is limited, particularly in the small-sized cities/village areas of the urban and rural region. • The financial burden of transport carbon pricing varies by the economic status of households. • Within all economic status groups, the financial burden varies also by area categories. • Equal-per-household-payments could turn the regressive effect of carbon pricing progressive. • Yet some households with a very low economic status may still need temporary mobility allowances. [ABSTRACT FROM AUTHOR]

In this paper, we develop the concept of a "Sustainable Mobility Guarantee". We first review existing "Mobility Guarantees", which are rather motivated by socioeconomic interests than environmental sustainability and classify them. Based on this assessment, we define a Sustainable Mobility Guarantee, which extends existing approaches with environmental interests. It is an emerging concept in policymaking to ensure a certain level of mobility without the need for private cars - particularly in rural areas - but it is still in its infancy and lacks clear definitions. The concept embraces the idea of Classical Mobility Guarantees while seeking to enable and promote the use of non-automobile modes for everyday travels for everyone, not only for specific trip purposes like commuting, nor for specific target groups like the elderly. We then discuss the practical implementation and financial feasibility. Implementation is possible through programmatic or regulatory approaches, which may serve as a potential transitional basis for legal regulation. At least in developed countries, implementing mobility services realizing a Sustainable Mobility Guarantee is deemed financeable, given that financial instruments now subsidizing automobile use are shifted towards implementation of the guarantee, without being detrimental to the economy. • Policy, laws and regulations to guarantee human mobility are reviewed and classified from several perspectives. • A Classical Mobility Guarantee aims to provide fallback for people without car or ability to drive. • A Sustainable Mobility Guarantee aims to motivate people to shift away from cars both in cities and rural areas. • The concept for a Sustainable Mobility Guarantee is developed and transition is discussed. • An analysis of implementation cost is estimated and discussed using Austria as a case study. [ABSTRACT FROM AUTHOR]

Local authorities have a strategic role in mitigating the environmental impacts of the transport sector. However, they struggle to integrate environmental issues into their decision-making processes, especially planning. In the European context of the Sustainable Urban Mobility Plan approach and Strategic Environmental Assessments (SEAs), this paper scrutinises three French localities to determine the current best practices and limitations for designing mobility plans and integrating environmental issues. Several limitations are identified: (1) limited expertise in defining and characterising actions and objectives, which complexifies plans' design, understanding, and monitoring; (2) a lack of a framework to conduct long-term quantitative environmental assessments and to use the results to influence decision effectively; and (3) monitoring processes are barely described in the documents, and the planning horizon where objectives are defined is not in sync with the indicators' mandatory evaluation period. This French case study thus reveals that European planning practices must be further analysed and improved to deal with the rising environmental concerns, e.g. through an operational framework to design mobility plans with effective integration of environmental issues. • Planning supports local authorities in moving towards a more sustainable mobility. • There is no robust approach to defining and characterising actions and objectives. • Robust long-term quantitative assessments are lacking to support planning. • Monitoring modalities are scarcely described in plans and SEAs. • Improving planning frameworks would help the integration of environmental issues. [ABSTRACT FROM AUTHOR]

Governments have implemented many regulations to solve traffic congestion and pollutant emissions. Traffic restriction (TR) policy is the most common and widely used traffic regulation. However, it is difficult to alleviate traffic pollution through TR policies. Only a few studies focus on TR policies in multiple cities. In this paper, we classify traffic restrictions by geographical factors and evaluate the impact of different policies based on PSM-DID first. Then, we classify the mixed restrictions and test their effects on air pollution. The results show that TR policy improves air quality regardless of the season. Moreover, the effect of TR policy is not affected by the superposition of the type of traffic restriction. For cities implementing the same TR policy, geographic factors can lead to different outcomes. This finding provides a reference for governments in reducing air pollution. • Traffic restrictions significantly affected air quality in different regions of China. • Cities implemented traffic restrictions have improved air quality in adjacent cities. • Effect of traffic restrictions does not depend on the number of mixed restrictions. [ABSTRACT FROM AUTHOR]

Assessments of the bike-sharing industry traditionally focus on its effects on other markets, municipalities, or general well-being. This paper deviates from this on how the market is organised. Using information on the aggregate number of firms in cities and greater cities across Europe, we found non-proportional changes in market size with respect to changes in market structure. This is crucial information inferring changes in profits, costs, or degree of product differentiation. To distinguish between these three sources, we utilised additional firm-level data on capacity and type of service provided. Our results suggest that the non-proportional increase in market size after an entry is most likely associated with increased intensity of competition and new forms of offered services, i.e. product differentiation. We did not find evidence that newcomers have been entering with substantially larger capacities per capita compared to incumbents. From a policy perspective, entry into the bike-sharing industry has benefited consumers through market expansion and caused a potential decrease in profits. • A non-proportional market size increase after the entry of the second and third firms. • No association for entry barriers; no entries with larger capacity. • Increases likely associated with differentiation: entrants likely dockless or e-bikes. • Entry and competition benefited consumers through market expansion and may decrease profits. [ABSTRACT FROM AUTHOR]

Taking a mixed method and comparative case study approach, this paper has analyzed the formulation process of mobility policy strategies and plans and their implementation in four Asian cities. The key findings are: (1) there was some evidence on leadership shown by mayors, governors, public transport administrators and police in all four cities; (2) limited stakeholder engagement in the whole process of policy formation to implementation and some forms of donor influence were observed in three capital cities that resulted in follow-up projects or studies; and (3) the implementation of policies and plans faced many challenges relating to leadership, resources, prioritization, and coordination among various organizations. There was much focus on the formulation of mobility policies and plans and the users could not feel a meaningful improvement to urban mobility services despite the implementation of large urban mobility projects. A comprehensive evaluation framework is proposed and used to evaluate the whole process of improving urban mobility from policy formulation to implementation. There seems to be much preference for large urban transit projects vis-à-vis infrastructure for active mobility and low-cost solutions. The research also indicates the need for meaningful public engagement so that the mobility plans take a citizen-centric approach that reflects the needs of the urban residents, rather than taking a modernistic approach with solutions more suitable for middle-income groups. Delays in the implementation of major projects also suggest that more realistic planning, scheduling, and improvement in project management and coordination is necessary. • Reviews and assesses the whole process of mobility polices and plans in Asian cities. • There was some evidence of leadership shown by mayors, governors, public transport administrators and police. • Limited stakeholder engagement in the process of policy formation to implementation and some donor influence observed. • There was much focus on the formulation of mobility polices and plans and without much improvement to mobility services. • A comprehensive evaluation framework is proposed to evaluate mobility polices and plans. [ABSTRACT FROM AUTHOR]

The aim of this paper is to study whether politicians manipulate tax policy to extract private rents. We focus on the local personal income tax in the setting of Italian cities, which is a progressive instrument that allows mayors to set different rates to distinct wage groups. We exploit discontinuities in mayors' salaries, that are based on population thresholds, to study whether mayors apply lower rates to their own tax bracket, thereby distorting tax policy. The main results document large rent-seeking activity in tax policy. First, we show that when mayors's salary is exogenously located in the following tax bracket it receives a significantly lower tax rate than the previous one, compared to the control group. Second, we show that this rent-seeking activity is highly detrimental for the public treasury, with a considerable reduction in fiscal revenues. And finally, we document that the individual gain for rent-seeker politicians is rather limited and that there is no evidence of voters' punishment in the next elections. These results suggest that when tax policy is prone to be manipulated politicians do not hesitate to engage in rent-seeking activities even in case of little returns. [ABSTRACT FROM AUTHOR]

Freedom of Information (FOI) is considered a crown jewel of reforms fostering public administration transparency and accountability. However, FOI's symbolic power alone cannot overcome the organizational barriers and obstacles to its effective implementation. This paper presents the results of a field experiment performed in Italy, a late FOI adopter, where an FOI request was sent to the 307 municipalities with more than 30k inhabitants. The experimental design exploits marginal wording variation in the requests to test whether municipalities discriminate between ordinary citizens and high-profile requesters. The experimental evidence suggests that most Italian municipalities reply to FOI requests. The results show two opposite types of discretionary bias: Northern municipalities tend to favor high-profile requesters, whereas Southern municipalities tend to respond to them with a higher degree of attrition. The study investigates the determinants of this difference. [ABSTRACT FROM AUTHOR]

• Research progress of observation-based ozone formation sensitivity is reviewed. • Threshold values for Photochemical Indicator methods need to be localized. • Reaction mechanisms and monitoring capability need to be improved for OBM. • Ozone formation sensitivity in China presents the gradual shifting tendency. • Dynamic regulation capability for ozone pollution control needs to be built. Observation-based method for O 3 formation sensitivity research is an important tool to analyze the causes of ground-level O 3 pollution, which has broad application potentials in determining the O 3 pollution formation mechanism and developing prevention and control strategies. This paper outlined the development history of research on O 3 formation sensitivity based on observational methods, described the principle and applicability of the methodology, summarized the relative application results in China and provided recommendations on the prevention and control of O 3 pollution in China based on relevant study results, and finally pointed out the shortcomings and future development prospects in this field in China. The overview study showed that the O 3 formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NO x -limited regime due to the implementation of the O 3 precursors emission reduction policies; O 3 pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O 3 pollution control measures should be improved. There are still some current deficiencies in the study field in China. Therefore, it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved; the atmospheric chemical mechanisms should be vigorously developed, and standardized methods for determining the O 3 formation sensitivity should be established in China in the near future. [Display omitted] [ABSTRACT FROM AUTHOR]

Receivers and intermediary establishments typical to urban areas have unique freight behaviour and are understudied, particularly in developing countries. This paper uses establishment-based freight survey data to examine their freight generation patterns in the Chennai metropolitan area, India. Three sets of Simple Linear Regression (SLR) models, three single predictor proportional odds logit models, one multiple linear regression model, and one multiple predictor proportional odds logit model with business size (employment, area, and operational age) and indicators of establishment category as regressors are developed each for both freight production and freight attraction. Partial proportional odds logit models are developed in a few cases to overcome the limitations of proportional odds logit models. The best SLR model varied with the establishment category for freight production and attraction. The establishment area model is the best among single predictor proportional odds logit models. The multiple predictor proportional odds logit models marginally improved the fit over single predictor models. The proportional odds logit model results show that the establishment category has a greater impact on freight generation levels than business size variables. Since earlier studies rarely focused on receivers and intermediary establishments, policymakers may benefit from the developed models and study insights while estimating freight demand and developing freight policies. • Receivers and intermediary establishments' freight generation is studied. • Partial Proportional Odds (PO) logit models are developed for freight attraction. • Area model is the best single predictor PO logit model for freight generation. • Establishment type affects freight generation more than business size variables. [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]

• Robust infrastructure is essential to enhance urban productivity and support urban development. • Transportation infrastructure enhances urban productivity by promoting economic agglomeration. • Information infrastructure promotes urban productivity through labor mobility and agglomeration effects. • The promotion effect on urban productivity in eastern regions and megacities is more obvious. • Transportation and information infrastructure have positive spatial spillover effects on urban productivity. Improving total factor productivity is an important driving force for achieving high-quality economic development. Based on the panel data of 256 cities in China from 2009 to 2019, this paper investigates the effect of transportation and information infrastructure on urban productivity. The results show that transportation and information infrastructure promote urban productivity, and the effect in eastern regions and megacities is more obvious. The mechanism analysis shows that transportation infrastructure enhances urban productivity by promoting economic agglomeration, and information infrastructure enhances urban productivity by promoting labor mobility, economic agglomeration, financial agglomeration and industrial agglomeration. The spatial spillover effect shows positive spatial autocorrelation of urban productivity. Transportation and information infrastructure have significant positive spatial spillover effects on urban productivity. China should continue to promote the construction of transportation infrastructure, strengthen investment in information infrastructure, and promote the joint construction, sharing, coordination and integration of transportation and information infrastructure. [ABSTRACT FROM AUTHOR]

At present, scholars hold two opposite views on the spatial impact (i.e., positive and negative impact) of high-speed rail (HSR) on tourism economy. To better explore the spatial impact of HSR on tourism economy, this paper uses the difference-in-differences (DID) to empirically test the causal effect of HSR and tourism economy, specifically by using the panel data of cities in Northeast China from 2010 to 2018 as research sample. On the whole, empirical results show that HSR has become an important factor in promoting the development of tourism economy. The impact of HSR on tourism economy in different years indicates that with the continuous promotion of HSR, the effect of HSR-driven tourism economy has become increasingly evident. On this basis, this paper classifies cities according to different types and finds that compared with ordinary prefecture-level cities, central cities are more affected by HSR. Compared with cities with high abundance of tourism resources, cities with low abundance of tourism resources are more affected by HSR. Therefore, current article is convinced that while seizing the opportunity of HSR, cities should actively avoid the negative impact brought by the development of HSR and truly promote the balanced development of regional tourism. • We provide a broader understanding of the issue of HSR and tourism economy through detailed data and quantitative evidence. • Taking Northeast China as an example, the positive effect of HSR on tourism economy in underdeveloped regions is verified. • The impact of HSR on the tourism economy in Northeast China is heterogeneous. • The findings provide support for synergistic HSR planning and tourism development. [ABSTRACT FROM AUTHOR]

• To solve the forecasting problems of time-lead and nonlinearity in a system, a novel grey multivariable model is proposed. • To reduce the morbidity of the model, the solution of the proposed model is deduced through a derivation method. • The grey prediction evolution algorithm is employed to find the optimal value of parameters. • The validity of the new model was verified by three examples and applied to house price forecasting. Time lags or leads and non-linearity of complex systems are critical to address in accurate scientific prediction. However, few studies have focused on time-lead and nonlinear models with limited information. Therefore, this paper aims to develop a novel grey multivariate model with time-lead operator τ and nonlinear factor r from the perspective of this problem. Next, the solution of the proposed model is deduced through a derivation method to reduce the morbidity of the model. Then, the parameter identification of the model is given on the basis of the least-squares method. The grey prediction evolution algorithm is employed to find the optimal value of parameters τ and r to meet the minimum errors. Finally, house prices of Wuhan, Beijing and Shanghai in China are performed to verify the validity and reliability of the new model. The results demonstrate the model we proposed has satisfactory prediction precision, demonstrating that time-lead and nonlinear factor in the model is reasonable. At the end of the paper, the house prices of these three cities from 2022 to 2028 are also predicted. The average annual growth rate in the three regions is 2.49%, 3.57% and 2.97%, respectively. These results are useful to policy analysis regarding house price correlations. They provide insights for market investors and policy makers. [ABSTRACT FROM AUTHOR]

The deployment of hydrogen refueling stations is vital to the development of fuel cell vehicles. Past studies on the hydrogen refueling stations didn't consider congestion on paths and assumed all flows are on the shortest paths of OD pairs, which is not consistent with travelers' route choice behavior. In this paper, we study flow refueling location allocation based on the user-equilibrium (UE) status, which is consistent with travelers' route choice behavior. We present a flow-capturing location allocation (FCLA) model on UE conditions. We also presented an equilibrium algorithm avoiding cannibalization to solve the model. Based on the transportation network of Anaheim city in California in the US, we compared the results of applying a non-equilibrium method to the FCLA model and applying the equilibrium method to the FCLA model on UE conditions. The results of the two algorithms and models are different. The equilibrium model and algorithm can capture more flow and has a higher flow-capturing ratio. What's more, the equilibrium model and algorithm can fully capture the expected flow in practice since the real transportation network is basically in UE status. The equilibrium model and algorithm presented in this paper is the first study of this kind to locate stations in cities and is useful in the deployment of hydrogen refueling stations. • Study flow refueling location allocation based on the user-equilibrium (UE) status. • A flow capturing location allocation (FCLA) model on UE conditions. • An equilibrium algorithm avoiding cannibalization to solve the model. • Compare between non-equilibrium method and equilibrium method in flow capturing. [ABSTRACT FROM AUTHOR]

• We study the relationship between GVC embedding and carbon emission density. • A mediation effect model was established to test the mechanism. • There is a U-shaped relationship between urban GVC embedding and carbon emission density. To achieve its carbon peak and neutrality plan, whether China's global value chain (GVC) embedding has a carbon emission reduction effect is a question worthy of attention. This paper measures the GVC embedding degree of 218 Chinese cities from 2000 to 2016, and constructs a panel data model to investigate the impact and its mechanism of GVC embedding on carbon emission intensity. This study finds that there is a significant U-shaped relationship between GVC embedding and carbon emission intensity, and a series of robustness test results support this conclusion. Export scale, energy consumption structure and technological innovation play a mediation role in the impact path of GVC embedding on carbon emission intensity. Based on this, this paper proposes that while participating in GVC, China needs to actively utilize the emission reduction effect of GVC, promote the transformation of export mode to high quality, reduce the use and dependence on high-carbon resources such as coal, and encourage companies to innovate. [ABSTRACT FROM AUTHOR]

Based on the evidence from listed company microdata and data from 285 cities in China, this paper studies the coordinated development of two-way FDI (CDFDI) in improving green energy efficiency (GEE). In particular, this paper examines the spatial heterogeneity effects of CDFDI on GEE. The results showed that CDFDI had a positive impact on the GEE of local and surrounding cities. Mechanistic examinations show that the effects of CDFDI on GEE are mediated by technological diffusion, nationalization, and environmental regulation. After dividing different city types, the impact of CDFDI is also different. By constructing a spatial decay weight matrix, this paper also finds that the positive spatial spillover effect of CDFDI is limited to 1050 KM. Finally, different investment motive portfolios also has a heterogeneous impact on the local and surrounding cities' GEE. After dividing the time nodes, the effect of this heterogeneity is more prominent. • We use multiple undesired output indicators covering eight pollutants to measure green energy efficiency (GEE). • CDFDI has a significant boost to GEE in local and surrounding cities. • The impact of CDFDI on GEE is moderated by technological diffusion, nationalization, and environmental regulation. • The spatial spillover effects of CDFDI are heterogeneous by city category and geographic distance. • CDFDI with different investment motives has heterogeneous effects on local and surrounding cities' GEE. [ABSTRACT FROM AUTHOR]

This paper presents the background, setup, and results of a stated choice experiment investigating the influence of three different intersection based innovations on cyclists' route choice decisions. Next to commonly used route attributes, the following three intersection based innovations were investigated: 'Flo', a bicycle speed advice tool; 'Schwung', a bicycle - traffic light communication tool; and 'BikeScout', an intersection flashing system. The generated stated choice experiment was included in an online questionnaire that was filled out by 608 respondents who evaluated in total 3648 choice tasks. The evaluations were analyzed using a Multinomial Mixed Logit model. The model estimation results show that the commonly used route attributes (travel time, type of bicycle path facility, pavement quality level, motorized traffic speed, bicycle crowdedness, and number of traffic light intersections) have the highest influence on cyclists' route choice decisions. The impact of intersection based innovations on cyclists' route choice decisions is limited. • Most of the respondents indicated that they are not familiar with the included innovations (BikeScout and Flo/Schwung). • Most respondents indicated that they understand the meaning/working of the presented innovations after looking at movie. • Commonly used route attributes have the highest influence on cyclists' route choice decisions. • Impact of intersection related innovations on cyclists' route choice decisions is limited. [ABSTRACT FROM AUTHOR]

Newly constructed areas (NCA) are continuously emerging with the development of urbanization, which, however, triggered a series of ecological and environmental issues. Therefore, monitoring NCA is of great significance for sustainable urbanization. Extraction of NCA from remote sensing images involves semantic segmentation of constructed areas and change detection. However, the acquisition of samples for training change detection models is time-consuming. In this study, we proposed a multi-task learning framework including unsupervised change detection and supervised semantic segmentation for NCA extraction. The main contributions of this study are: (1) A deep multivariate alternation detection (DMAD) algorithm was proposed for unsupervised change detection of hyperspectral images. By introducing the optimization objective of Multivariate Alternation Detection (MAD) in the loss functions, the features of changed areas can be extracted more effectively; (2) A multi-task learning framework was proposed for the joint training of DMAD change detection and supervised semantic segmentation, where the two modules were mutually optimized via semantic masks and consistency loss. Based on Orbita Hyperspectral Satellites (OHS) images, we conducted experiments in two cities (Qinzhou and Wuzhou) of Guangxi province. The experimental results indicated that the proposed method can achieve the F1-score better than existing unsupervised change detection methods (e.g., DCCA and DSFA) by an average of 15%, and the OA better than existing semantic segmentation methods (e.g., U-Net and FreeNet) by an average of 1%. The F1-score and Kappa for NCA extraction reached above 0.80 for both study areas. The implementation of this paper will be made available at https://github.com/tulilin/Multitask_NCA. [ABSTRACT FROM AUTHOR]

City modeling and generation have attracted an increased interest in various applications, including gaming, urban planning, and autonomous driving. Unlike previous works focused on the generation of single objects or indoor scenes, the huge volumes of spatial data in cities pose a challenge to the generative models. Furthermore, few publicly available 3D real-world city datasets also hinder the development of methods for city generation. In this paper, we first collect over 3,000,000 geo-referenced objects for the cities of New York, Zurich, Tokyo, Berlin, Boston, and several other large cities. Based on this dataset, we propose AETree, a tree-structured auto-encoder neural network, for city generation. Specifically, we first propose a novel Spatial-Geometric Distance (SGD) metric to measure the similarity between building layouts and then construct a binary tree over the raw geometric data of the building based on the SGD metric. Next, we present a tree-structured network whose encoder learns to extract and merge spatial information from the bottom-up iteratively. The resulting global representation is reversely decoded for reconstruction or generation. To address the issue of long-dependency as the level of the tree increases, a Long Short-Term Memory (LSTM) Cell is employed as a basic network element of the proposed AETree. Moreover, we introduce a novel metric, Overlapping Area Ratio (OAR), to quantitatively evaluate the generation results. Experiments on the collected dataset demonstrate that the proposed model outperforms baseline models, such as LayoutTransformer and LayoutVAE, in terms of key metrics. Specifically, the proposed model achieves a Jensen–Shannon Divergence (JSD) of 0.0033, compared to 0.0041 and 0.0061 for LayoutTransformer and LayoutVAE, respectively. Similarly, for the Overall Accuracy Rate (OAR), the proposed model scores 1.66, significantly better than 28.24 and 19.01 for the baseline models Furthermore, the latent features learned by AETree can serve downstream urban planning applications. Project webpage is available at https://ai4ce.github.io/RealCity3D. [ABSTRACT FROM AUTHOR]

• We explore the impact of the COVID-19 pandemic on cyclists' reactions to weather. • During COVID-19, cyclists in transit-oriented cities reacted stronger to weather. • In student cities, the weather elasticity did not change during pandemic. • Results of 2.2 million hourly bicycle count observations from 69 counting stations. Cycling can only unfold its full potential for environmental sustainability, livable cities, and health if people cycle under most seasonal and weather conditions. During the COVID-19 pandemic, many people preferred cycling over public transit, in order to avoid infection. This change may also have affected the weather–cycling association: the pandemic mainly attracted new, fair-weather cyclists; and it may have encouraged cyclists to continue cycling, even under less favorable conditions. In this paper, we explore how the COVID-19 pandemic affected the association between weather and cycling. We analyze data from bicycle counting stations in Germany, combined with city- and hour-specific weather information and a continuous measure of pandemic intensity. The data set contains more than 2.2 million hourly bicycle count observations from 69 counting stations, covering the years 2017–2021. Results from the most transit-oriented cities in the sample, Berlin and Munich suggest that the cycling volume was more dependent on weather conditions at times of high pandemic intensity. This suggests that the pandemic put new people in the saddle, but these additional cyclists were largely fair-weather cyclists who only cycled when the weather was sufficiently nice. For policy, this could set two targets. First, encourage the new pandemic-cyclists to stay on the bike and, second, support them in transitioning into year-round cyclists eventually. [ABSTRACT FROM AUTHOR]

Southeastern Turkey perished by the M w 7.8, Kahramanmaras earthquake on February 6, 2023, at 01:17 UT (04:17 LT). The Kahramanmaras-centered event, hit by the break of the East Anatolian Fault Line, is felt in Syria, Egypt, Lebanon, Iraq, and Cyprus on the border of Turkey. Together with Syria, it causes loss of lives and severe damage in 10 cities. This work is dedicated to the people of the region. The study discusses the causality of anomalies by conducting ionospheric anomaly research via the interpolated TEC map obtained from the CODE according to the coordinates of the epicenter of the earthquake (latitude, longitude). The TEC amplitudes are observed by evolving the time-domain TEC map into the frequency-domain with the Fourier transform. The peaks of the amplitudes allow preliminary information for the anomaly days. For the anomaly, the TEC (TECU) boundaries are drawn by the statistical specification. The TEC map outside these boundaries is marked as an anomaly. The causality of abnormalities is tried to be read through the triad of the geomagnetic storm(s) , solar activity , and the earthquake effect. One can find seven anomaly days in the paper. January 30, February 2, 3, 11, 15, 16, and 21 are the anomaly days. The essay probably detects the anomaly before 3 days related to the Southeastern earthquake. • Reads the causality of the earthquake in southeast Turkey (Mw 7.8), through the ionosphere-earth crust relationship. • Notices potential anomalies by presenting the time-domain TEC atlas in the frequency domain with Fourier spectral analysis. • Considering all possible TEC anomaly essentials detect the precursors of the earthquake 3 days before the event day. [ABSTRACT FROM AUTHOR]

Mobility as a service (MaaS) is an emerging framework that integrates multiple transport services into a single and intuitive platform. This paper contrasts the urban passenger transport markets in developed versus developing economies to understand the challenges of integrating mobility services using the MaaS framework, with a focus on decarbonization and sustainability as societal goals. In addition, we conducted a Life Cycle Assessment of carbon emissions and energy requirements of travel alternatives in the city of Santiago, Chile, to shed light on the effects of multimodality as an environmental tool. A summary of findings follows. Data sharing and open data are new in developing countries, and thus more investment in data infrastructure is required so that MaaS can leverage digital technology and network optimization. If the scalability of MaaS is an open question in developed countries, it is more so in developing countries, owning to institutional and financial constraints that are present in the latter. The lack of public subsidies to support formal public transport is a key limitation for the implementation of MaaS schemes and multimodal frameworks in the developing world. Regarding formality, in countries with an informal public transport sector, a potential implementation of MaaS will be spatially constrained to those locations where public transport operates formally and frequently (BRT and rail lines), limiting its spatial coverage and posing social equity issues. In countries with scarce or no public funds available for the transport sector, MaaS could be used as a catalyst for a broad environmental and equity-seeking transport pricing reform which requires a direct involvement of public sector in both regulation and financial backing. We conclude that the formalization and general improvement of the public transport sector, the regulation of shared-mobility platforms including the formalization of the work of drivers, and the setting of proper pricing and subsidization instruments in the direction of internalizing the social costs of motorized traffic, are all prerequisites for any MaaS system that aims to improve economic efficiency, social equity, and sustainability. • Assess MaaS as a framework for decarbonization in developing world. • Discuss governance and equity issues in implementing MaaS. • Identify carbon policy for different cities to achieve sustainability. • Conduct a life cycle assessment to inform carbon strategies. • Scalability is a key challenge in both developing and developed worlds. [ABSTRACT FROM AUTHOR]

Trip-based models and activity-based models represent two extreme ends of the spectrum of travel demand models in data granularity requirement and ability to reflect the underlying motivation to travel. Modelling of representative freight activity-travel patterns (RFAPs) has the potential to serve as the bridge between these approaches. RFAP clusters represent homogeneous groups of establishments, where utility maximization models predict the probability that an establishment belongs to a particular cluster. However, it is still an open question how to define, interpret and model activity-travel patterns in the context of freight system. To answer this question, this study conducted a large-scale establishment-based freight survey (EBFS) in seven cities of India and resulted in a sample of 432 establishments and their 1613 shipment records. In the first part, this paper proposes a novel approach for identifying RFAPs based on the notion that "activities" that inspire trip-making for passenger is equivalent to "freight orders" in the case of establishments. The cluster analyses revealed the presence of three well separated main clusters and nine less separated nested clusters. Through interpretation and labelling of these RFAPs, freight travel market is categorized into useful segments. The results suggested that a priori industrial classification systems used in trip-based models are overly simplified representations of the complex structure of the travel patterns. In the last part, freight activity-travel pattern generation (FAPG) models are developed which predicts the probability that an establishment exhibits a particular RFAP. The FAPG models developed using these RFAPs could replace the traditional freight generation (FG) and freight trip generation (FTG) models due to its ability to convert the assigned activity-patterns to trips or tonnage. For example, FAPG model suggest that at an employment level of 120, there is a 56% probability that establishments will exhibit MDV-HFMH (medium duty vehicles - high frequency medium haul) pattern which, in turn, implies that FP = 1630 tons/year; shipment frequency, i.e., FTP = 8 trips/week; length of haul = 240.6 km and commercial vehicle type choice = MDV. Thus, FAPG models can present an enhanced representation of freight flows since both FG and FTG are jointly modeled in this approach. That is, the best features of both commodity-based modelling (i.e., ability to capture the fundamental mechanism that drives freight demand) and vehicle-based modelling (i.e., ability to capture freight traffic implications) are included in FAPG models. The study findings are expected to assist in identifying the variations in establishments' preferences so that it is possible to identify the type of transport supply improvements that the establishments will respond to accurately, and thus prioritize the infrastructure investments. Moreover, the discussions on these findings are expected to improve the behavioral and spatial foundations of traditional freight models. • Defines "freight orders" as logical equivalent of "household activities" that drive trip-making. • Activity based approach is used for modelling freight travel using EBFS data. • Identifies homogeneous segments of representative freight activity-travel patterns (RFAPs). • Propounds freight activity-travel pattern generation (FAPG) models based on RFAPs. • FAPG gives enhanced representations of freight flows (FG, FTG, vehicle type, haulage). [ABSTRACT FROM AUTHOR]

In a constant evolving world, change detection is of prime importance to keep updated maps. To better sense areas with complex geometry (urban areas in particular), considering 3D data appears to be an interesting alternative to classical 2D images. In this context, 3D point clouds (PCs), whether obtained through LiDAR or photogrammetric techniques, provide valuable information. While recent studies showed the considerable benefit of using deep learning-based methods to detect and characterize changes into raw 3D PCs, these studies rely on large annotated training data to obtain accurate results. The collection of these annotations are tricky and time-consuming. The availability of unsupervised or weakly supervised approaches is then of prime interest. In this paper, we propose an unsupervised method, called DeepCluster 3D Change Detection (DC3DCD), to detect and categorize multiclass changes at point level. We classify our approach in the unsupervised family given the fact that we extract in a completely unsupervised way a number of clusters associated with potential changes. Let us precise that in the end of the process, the user has only to assign a label to each of these clusters to derive the final change map. Our method builds upon the DeepCluster approach, originally designed for image classification, to handle complex raw 3D PCs and perform change segmentation task. An assessment of the method on both simulated and real public dataset is provided. The proposed method allows to outperform fully-supervised traditional machine learning algorithm and to be competitive with fully-supervised deep learning networks applied on rasterization of 3D PCs with a mean of IoU over classes of change of 57.06% and 66.69% for the simulated and the real datasets, respectively. The code is available at https://github.com/idegelis/torch-points3d-dc3dcd. • DC3DCD, unsupervised learning method for multiclass 3D point cloud change detection. • Revisiting the DeepCluster principle for change segmentation in raw 3D point clouds. • Results are better than classical supervised machine learning methods. • Results are equal to rasterization-based deep learning supervised networks. • In a binary-to-multiclass scenario, DC3DCD competes with fully supervised methods. [ABSTRACT FROM AUTHOR]

• The nexus between FinTech development and inclusive growth is analyzed. • The indicator system for inclusive growth is established. • The spatial econometric approach and machine learning are applied. • The case of an emerging economy is considered. This study investigates the impact of financial technology (FinTech) on inclusive growth (IG) by exploiting a panel of 281 prefecture-level Chinese cities in the years 2011–2020 using the spatial econometric model and machine learning algorithm. The results show that FinTech positively impacts IG, while there is no spatial spillover effect. The evidence from the machine learning algorithms suggests that as FinTech advances to a higher level, its positive impact on IG increases. The mechanism test shows that the latter effect is achieved through entrepreneurial stimulation and human capital enhancement. Moreover, the impact of FinTech on IG is more pronounced in large and medium-sized cities and cities in the eastern region. However, it does not significantly affect small cities or cities in the central region. This paper, therefore, offers new insights on the interaction between FinTech and IG along with the analysis of the effects related to the development of FinTech on IG in China. [Display omitted] [ABSTRACT FROM AUTHOR]

• The amount of separately collected bio-waste, its composition and selected properties are subject to seasonal variations. • Food waste is the main component of bio-waste from each tested site. • Substantial part of contaminants (e.g. plastics, glass) was found in the waste stream. • Waste collected in containers in multi-family housing area the most contaminated. • Heavy metals content of tested samples varied, both in terms of location and season. The progress of civilisation contributes, among other things, to an increase in the mass of waste produced in households. A significant part of it is bio-waste (about 31% in Poland). It is generally agreed that bio-waste is a suitable substrate for valorisation through fermentation with biogas production. Designing new and optimising existing facilities, however, requires precise data on the composition of bio-waste and its properties, which is challenging due to seasonal variability, place of origin (single- or multi-family housing, urban or rural) and collection method. This paper presents the method adopted for conducting the study and the results of an annual, monthly analysis of the morphological composition and selected properties of bio-waste from source-segregated households from 4 rural municipalities and 4 cities, from neighbourhoods with single-family and multi-family housing in Poland. In household bio-waste, the proportion of food waste content ranges from 36.7 to 47.6% (annual average values). The proportion of edible food waste in relation to the total weight of food waste is 5 to 7 times lower. The yearly percentage of garden waste varied from 35.8 to 52.8%. A considerable amount of impurities (such as plastics, glass, and stones) is present in the bio-waste stream. The waste collected in containers in urban areas with multi-family houses is the most polluted (16.6%). The proportion of pollutants in bio-waste collected in bags (rural areas and cities with single-family housing) does not exceed 10%. [ABSTRACT FROM AUTHOR]

The quest for a theory of cities that could offer a quantitative and systematic approach to managing cities represents a top priority. If such a theory is feasible, then its formulation must be in a mathematical way. As a contribution to organizing the mathematical ideas that deal with such a systematic way of understanding urban phenomena, we review the main theoretical models present in the literature that aim at explaining the origin and emergence of urban scaling. We intend to present the models, identify similarities and connections between them, and find situations in which different models lead to the same output. In addition, we report situations where some ideas initially introduced in a particular model can also be introduced in another one, generating more diversification and increasing the scope of the original works. The models treated in this paper explain urban scaling from different premises, i.e. from gravity ideas, densification and cites' geometry to a hierarchical organization and social network properties. We also investigate scenarios in which these different fundamental ideas could be interpreted as similar — where the similarity is likely but not obvious. Furthermore, concerning the gravity model, we propose a general framework that includes all analyzed models as particular cases. We conclude the paper by discussing perspectives of this field and how future research designs and schools of thought can build on the ideas treated here. • We review the mathematical models which explain the emergence of urban scaling. • We identify similarities and connections between these models. • Models consider different premises, e.g. gravity ideas, cities' geometry, and network properties. • Regarding the gravity idea, we propose a general framework [ABSTRACT FROM AUTHOR]

• First Multiple Linear Regression analysis of waste management systems in EU capitals. • Door-to-door bio-waste collection linked to higher overall dry recyclables capture. • On average, dry recyclables sorting doubled in capitals with door-to-door bio-waste collection. • Linkage between door-to-door bio-waste collection and boosted sorting needs further research. • Convenience, communication campaigns and system maturity likely causal factors. • Severe lack of available data hampers evidence-based EU policymaking. The European Union Waste Framework Directive revised in 2018 sets an ambitious target of recycling 55 percent of municipal solid waste by 2025. Separate waste collection is an important prerequisite for achieving this target, but progress is uneven among Member States and has slowed down in recent years. This makes it paramount to identify effective waste management systems to enable higher recycling rates. Waste management systems vary greatly within Member States and are established by municipalities or district authorities, making the city-level the ideal level of analysis. Based on quantitative analysis of data from 28 European Union capitals (pre-Brexit), this paper speaks to debates about the effectiveness of waste management systems more broadly and the role of door-to-door bio-waste collection in particular. Drawing on encouraging findings in literature, we investigate whether door-to-door bio-waste collection contributes to boosting the collection of dry recyclables such as glass, metal, paper and plastic. Employing Multiple Linear Regression, we sequentially test for 13 control variables including six related to different waste management system and seven controls related to urban, economic and political aspects. We find evidence that door-to-door bio-waste collection is associated with greater amounts of separately collected dry recyclables. Cities with door-to-door bio-waste collection, on average, sort 60 kg per capita per year more of dry recyclables. Although the causal mechanisms behind such a relationship need further investigation, this finding indicates that European Union waste management could benefit from a stronger promotion of door-to-door bio-waste collection. [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]