María Magdalena Martínez-Rico, Luis Felipe Prieto-Martínez
This article investigates a family of centrality models for urban networks that incorporate both topological and non-topological factors. Since centrality is inherently recursive, these models can be formulated as fixed-point equations, which we refer to as shifted eigenproblems. Assuming a correlation between node centrality and occupancy, we discuss how experimental data can be used to estimate model parameters via least-squares methods. Furthermore, such data would allow us to infer the intrinsic attraction of each node, as well as the occupancy induced by must-visit points of interest, a task that is conceptually challenging. Once the model parameters are fitted and validated, our framework can be used to assess the impact of urban interventions, such as introducing a must-visit point of interest at a specific node or enhancing its intrinsic attraction. The resulting sensitivity analysis is therefore highly relevant for urban planning decisions. We also provide explicit formulas to facilitate this analysis.
Nepal has implemented an affirmative action policy in the federal civil service since 2007 to address historical injustices and inequalities and promote the representation of marginalized people, such as women, ethnic minorities, and underprivileged castes, in public sector employment. This move has contributed to empowering disadvantaged people, mainstreaming minorities, and promoting social justice by strengthening inclusion within the bureaucratic structure. A qualitative research methodology is applied to perform a scoping review of 87 scholarly articles and a media review of 45 news articles to reveal the reasons behind the reforms made by policy enterprises in Nepal. The findings scrutinize both the constructive and critical facets of affirmative action practices in Nepal’s public service from 2007 to 2024. Besides some positive results leading to cultural competencies, such as the increased representation of women, Dalits, and ethnic minorities, there are still substantial inequalities in equal opportunities for empowerment and active participation in decision-making processes. The main reasons for such negative situations are complex social, ideological, and legal barriers, narrow-minded and deeply established prejudices, the lack of sufficient financial and human resources to undertake the programs, patriarchal organizational culture, and ultimately inadequate political commitment. The paper recommends continued reforms, timely review, preventing elite capture, adaptation to changing needs, a focus on the inadequate representation of marginalized groups, and the promotion of affirmative action policies that will result in the ending of these hurdles and, eventually, a more representative and all-inclusive Nepalese civil service.
This study adopts an organisational ethnography perspective to assess the impact of integrating document production as a central element of environmental policy. The implementation of urban adaptation plans in Poland from 2007 to 2023 illustrates how EU-inspired, project-based development of environmental documents effectively addresses climate change adaptation as a manageable urban issue, engaging urban administration. However, attempts to go beyond this framework encounter constraints, and emphasising administrative feasibility has introduced challenges in addressing factors hindering policy success. The findings advocate for a critical approach to developing environmental documents, highlighting the multidimensional influence of document production on policy implementation.
Understanding how urban systems and traffic dynamics co-evolve is crucial for advancing sustainable and resilient cities. However, their bidirectional causal relationships remain underexplored due to challenges of simultaneously inferring spatial heterogeneity, temporal variation, and feedback mechanisms. To address this gap, we propose a novel spatio-temporal causality framework that bridges correlation and causation by integrating spatio-temporal weighted regression with a newly developed spatio-temporal convergent cross-mapping approach. Characterizing cities through urban structure, form, and function, the framework uncovers bidirectional causal patterns between urban systems and traffic dynamics across 30 cities on six continents. Our findings reveal asymmetric bidirectional causality, with urban systems exerting stronger influences on traffic dynamics than the reverse in most cities. Urban form and function shape mobility more profoundly than structure, even though structure often exhibits higher correlations, as observed in cities such as Singapore, New Delhi, London, Chicago, and Moscow. This does not preclude the reversed causal direction, whereby long-established mobility patterns can also reshape the built environment over time. Finally, we identify three distinct causal archetypes: tightly coupled, pattern-heterogeneous, and workday-attenuated, which map pathways from causal diagnosis to intervention. This typology supports city-to-city learning and lays a foundation for context-sensitive strategies in sustainable urban and transport planning.
Mohammed Ali El Adlouni, Ling Jin, Xiaodan Xu
et al.
Urban congestions cause inefficient movement of vehicles and exacerbate greenhouse gas emissions and urban air pollution. Macroscopic emission fundamental diagram (eMFD)captures an orderly relationship among emission and aggregated traffic variables at the network level, allowing for real-time monitoring of region-wide emissions and optimal allocation of travel demand to existing networks, reducing urban congestion and associated emissions. However, empirically derived eMFD models are sparse due to historical data limitation. Leveraging a large-scale and granular traffic and emission data derived from probe vehicles, this study is the first to apply machine learning methods to predict the network wide emission rate to traffic relationship in U.S. urban areas at a large scale. The analysis framework and insights developed in this work generate data-driven eMFDs and a deeper understanding of their location dependence on network, infrastructure, land use, and vehicle characteristics, enabling transportation authorities to measure carbon emissions from urban transport of given travel demand and optimize location specific traffic management and planning decisions to mitigate network-wide emissions.
We present the first scene-update aerial path planning algorithm specifically designed for detecting and updating change areas in urban environments. While existing methods for large-scale 3D urban scene reconstruction focus on achieving high accuracy and completeness, they are inefficient for scenarios requiring periodic updates, as they often re-explore and reconstruct entire scenes, wasting significant time and resources on unchanged areas. To address this limitation, our method leverages prior reconstructions and change probability statistics to guide UAVs in detecting and focusing on areas likely to have changed. Our approach introduces a novel changeability heuristic to evaluate the likelihood of changes, driving the planning of two flight paths: a prior path informed by static priors and a dynamic real-time path that adapts to newly detected changes. The framework integrates surface sampling and candidate view generation strategies, ensuring efficient coverage of change areas with minimal redundancy. Extensive experiments on real-world urban datasets demonstrate that our method significantly reduces flight time and computational overhead, while maintaining high-quality updates comparable to full-scene re-exploration and reconstruction. These contributions pave the way for efficient, scalable, and adaptive UAV-based scene updates in complex urban environments.
Commuting contributes substantially to urban greenhouse gas emissions and represents a critical focus for climate mitigation efforts. This paper explores the multifaceted nature of commuting-related carbon dioxide emissions by analyzing the influence of urban form, socio-economic attributes, and individual behaviors. It reviews analytical approaches including structural equation modeling, multi-objective optimization, and agent-based simulations that have been employed to understand and mitigate emissions. Building on these insights, the paper develops a conceptual framework for carbon-negative commuting that integrates spatial planning, behavioral interventions, technological innovations, and carbon offsetting strategies. Case studies from diverse global contexts illustrate both the feasibility and challenges of implementing these interventions. The discussion highlights key trade-offs, equity considerations, and governance barriers while identifying co-benefits such as improved public health and urban resilience. The paper concludes by emphasizing the need for interdisciplinary research and adaptive policymaking to operationalize carbon-negative commuting and align urban mobility systems with global decarbonization goals.
Mobility is a fundamental feature of human life, and through it our interactions with the world and people around us generate complex and consequential social phenomena. Social segregation, one such process, is increasingly acknowledged as a product of one's entire lived experience rather than mere residential location. Increasingly granular sources of data on human mobility have evidenced how segregation persists outside the home, in workplaces, cafes, and on the street. Yet there remains only a weak evidential link between the production of social segregation and urban policy. This study addresses this gap through an assessment of the role of the urban transportation systems in shaping social segregation. Using city-scale GPS mobility data and a novel probabilistic mobility framework, we establish social interactions at the scale of transportation infrastructure, by rail and bus service segment, individual roads, and city blocks. The outcomes show how social segregation is more than a single process in space, but varying by time of day, urban design and structure, and service design. These findings reconceptualize segregation as a product of likely encounters during one's daily mobility practice. We then extend these findings through exploratory simulations, highlighting how transportation policy to promote sustainable transport may have potentially unforeseen impacts on segregation. The study underscores that to understand social segregation and achieve positive social change urban policymakers must consider the broadest impacts of their interventions and seek to understand their impact on the daily lived experience of their citizens.
Albin Zeqiri, Julian Britten, Clara Schramm
et al.
Urban gardening is widely recognized for its numerous health and environmental benefits. However, the lack of suitable garden spaces, demanding daily schedules and limited gardening expertise present major roadblocks for citizens looking to engage in urban gardening. While prior research has explored smart home solutions to support urban gardeners, these approaches currently do not fully address these practical barriers. In this paper, we present PlantPal, a system that enables the cultivation of garden spaces irrespective of one's location, expertise level, or time constraints. PlantPal enables the shared operation of a precision agriculture robot (PAR) that is equipped with garden tools and a multi-camera system. Insights from a 3-week deployment (N=18) indicate that PlantPal facilitated the integration of gardening tasks into daily routines, fostered a sense of connection with one's field, and provided an engaging experience despite the remote setting. We contribute design considerations for future robot-assisted urban gardening concepts.
Abdul Saboor, Zhuangzhuang Cui, Evgenii Vinogradov
et al.
Accurate Probability of Line-of-Sight (PLoS) modeling is important in evaluating the performance of Unmanned Aerial Vehicle (UAV)-based communication systems in urban environments, where real-time communication and low latency are often major requirements. Existing PLoS models often rely on simplified Manhattan grid layouts using International Telecommunication Union (ITU)-defined built-up parameters, which may not reflect the randomness of real cities. Therefore, this paper introduces the Urban LoS Simulator (ULS) to model PLoS for three random city layouts with varying building sizes and shapes constructed using ITU built-up parameters. Based on the ULS simulated data, we obtained the empirical PLoS for four standard urban environments across three different city layouts. Finally, we analyze how well Manhattan grid-based models replicate PLoS results from random and real-world layouts, providing insights into their applicability for time-critical communication systems in urban IoT networks.
Urban heat islands (UHIs) are often accentuated during heat waves (HWs) and pose a public health risk. Mitigating UHIs requires urban planners to first estimate how urban heat is influenced by different land use types (LUTs) and drivers across scales - from synoptic-scale climatic background processes to small-scale urban- and scale-bridging features. This study proposes to classify these drivers into driving (D), urban (U), and local (L) features, respectively. To increase interpretability and enhance computation efficiency, a LUT-distinguishing machine learning approach is proposed as a fast emulator for Weather Research and Forecasting model (WRF) coupled to the Noah land surface model (LSM) to predict ground- (TSK) and 2-meter air temperature (T2). Using random forest regression (RFR) with extreme gradient boosting (XGB) trained on WRF output over Zurich, Switzerland, during heatwave (HW) periods in 2017 and 2019, this study proposes LUT-based (LB) models that categorize features by scales and practical controllability, allowing optional categorical weighting. This approach enables category-specific feature ranking and sensitivity estimation of T2 and TSK to most important small-scale drivers - most notably surface emissivity, albedo, and leaf area index (LAI). Models employing the LB framework are statistically significantly more accurate than models that do not, with higher performance when more HW data is included in training. With RFR-XGB robustly performing optimal with unit weights, the method substantially increase interpretability. Despite the needs to reduce uncertainties and test the method on other cities, the proposed approach offers urban planners a direct framework for feasibility-centered UHI mitigation assessment.
‘Culture-led’ regeneration is a widely practised yet long-contested approach in China’s urban redevelopment. Much of the existing work interprets these projects through Western frameworks of neoliberalism and growth machine politics, often portraying them as economically driven and culturally inauthentic, resulting in social displacement. While such critiques highlight important problems with culture-led cases, they risk oversimplifying the complexity of Chinese governance and overlooking how culture is redefined and mobilised within local contexts. This paper argues that Chinese culture-led regeneration must be understood through the state’s evolving definition of culture and its intentional deployment across economic, political and social domains. Earlier approaches largely framed culture as a material asset, embedded in heritage sites and industrial reuse, used to attract investment and stimulate growth. More recent discourses and policies expand this definition by treating culture as a social and political resource, central to fostering cohesion, legitimacy and sustainability. This shift reflects the evolving urban governance logics driven by the limits of demolition-heavy redevelopment, growing land restrictions and national mandates on heritage preservation and social stability. Drawing on key examples of creative industry clusters, heritage-led tourism and micro-regeneration, the paper demonstrates how culture-led regeneration in China reveals a conjunctural logic in which culture operates simultaneously as an economic, political and social instrument. Rather than assessing Chinese culture-led regeneration through universalist frameworks, this paper advocates for theorising with China by employing localised frameworks such as state entrepreneurialism. Further reshaping the debates on commodification, authenticity and the future of regeneration. It calls out to future research to further investigate the evolving role of culture in regeneration based on emerging evidence of the state’s gravitation towards extra-economic objectives.
Eftychia Ntostoglou, Daniel Ddiba, Dilip Khatiwada
et al.
The valorisation of urban biowaste can contribute to a circular and sustainable resource management. However, biowaste valorisation is not inherently sustainable. This study employs the Sustainable Development Goals (SDGs) to investigate the sustainability implications of biowaste valorisation. A narrative literature review provided an overview of the current scientific knowledge on interactions between biowaste valorisation and selected SDG targets. Then stakeholder interviews yielded insights into such interactions in a national context. Our findings show the potential for 19 synergies and 11 trade-offs between biowaste valorisation and 20 selected SDG targets that are addressed in detail. Although the synergies outnumber the trade-offs, different context-dependencies influence the nature and strength of the interactions. We highlight three types of context-dependencies relating to governance. This study informs the scientific community and decision-makers on planning for sustainable biowaste valorisation that addresses context-dependencies. The insights can guide countries and cities at early transition stages towards biowaste valorisation.
This research examines the environmental approval process in Nepal and compares it with those in India and Bangladesh, focusing on the time taken to complete the assessment of environmental study reports. The study conducts three levels of analysis. First, the policy review outlines all relevant environmental policies and laws, highlighting key provisions related to approval timelines. While not every step of the environmental study process has a mandated time frame, the legal time limits for report forwarding and approval are explicitly defined. Second, statistical analysis reveals a significant discrepancy between the statutory and actual approval times. While the legal mandate is just 35 days for Environmental Impact Assessment (EIA), assessing a report actually takes 339 days on average. The trend line reveals that the average time taken is decreasing. However, it is still much higher than India’s average EIA approval time of 64 days. Third, through a comparative analysis of eighteen different components of the environmental assessment process, this paper identifies the possible factors contributing to the delays, such as ambiguous jurisdiction, lack of nodal agency, lack of integrated guidelines, high centralization, and no use of e-governance. This paper also compares the thresholds that trigger the environmental study across eight sectors for three countries and finds that Nepal’s thresholds are narrower than India’s and comparable to Bangladesh’s. Recommendations made include clarifying jurisdictional roles, developing integrated guidelines, establishing specialized nodal agencies, and implementing digital systems. Overall, this research attempts to address flaws in Nepal’s environmental assessment system, offering solutions for efficient environmental regulation and improving the business environment in Nepal.
Since the early 2000s, cultural institutions have been instrumental in reshaping public spaces, fostering community engagement, and nurturing artistic innovation. Central to these initiatives are audience interaction and participation concepts, yet their definitions and applications in urban media art remain nebulous. This article endeavours to demystify these terms, examining the distinct characteristics and intersections of interactive and participatory art within urban contexts. A particular emphasis is placed on artworks that harmonise both elements, exploring the motivations and outcomes of this synthesis. The case study of We Are The Clouds serves as a focal point, exemplifying how strategic integration of interaction and participation can enhance community connection and reinvigorate public spaces. Through this analysis, the paper underscores the transformative power of urban media artworks in redefining neighbourhood experiences, empowering local voices, and revitalising the essence of public realms.
Human mobility is a fundamental process underpinning socioeconomic life and urban structure. Classic theories, such as egocentric activity spaces and central place theory, provide crucial insights into specific facets of movement, like home-centricity and hierarchical spatial organization. However, identifying universal characteristics or an underlying principle that quantitatively links these disparate perspectives has remained a challenge. Here, we reveal such a connection by analyzing the spatial structure of individual daily mobility trajectories using network-based modules. We discover a universal scaling law: the spatial extent (radius) of these mobility modules expands sublinearly with increasing distance from home, a pattern consistent across three orders of magnitude. Furthermore, we demonstrate that these modules precisely map onto the nested hierarchy of urban systems, corresponding to local, city-level, and regional scales as distance from home increases. These findings deepen our understanding of human mobility dynamics and demonstrate the profound connection between classical urban theory, human geography, and mobility studies.
Zeng Guanwen, Serok Nimrod, Lieberthal Efrat Blumenfeld
et al.
We analyze the patterns of traffic jams in urban networks of five large cities and an urban agglomeration region in China using real data based on a recently developed jam tree model. This model focuses on the way traffic jams spread through a network of streets, where the first street that becomes congested represents the bottleneck of the jam. We extended the model by integrating additional realistic jam components into the model and find that, while the locations of traffic jams can vary significantly from day to day and hour to hour, the daily distribution of the costs associated with these jams follows a consistent pattern, i.e., a power law with similar exponents. This distribution pattern appears to hold not only for a given region on different days, but also for the same hours on different days. This daily pattern of exponent values for traffic jams can be used as a fingerprint for urban traffic, i.e., jam-prints. Our findings are useful for quantifying the reliability of urban traffic system, and for improving traffic management and control.
Abstract As an important part of urban renewal, brownfield restoration and renovation are of great significance to the sustainable development of cities. The structure-process-outcome theory was introduced into this study to improve the rationality and scientific vigor of the redevelopment assessment process and to evaluate whether brownfield sites meet the conditions for redevelopment. Based on this theory, the relationship among structures, processes and outcomes can be well elucidated. Specifically, a good structure should contribute to an effective process, which will increase the possibility of a favorable outcome. The basic conditions, practice principles, and result orientation in the whole procedure of brownfield redevelopment were comprehensively analyzed. In addition, a more complete and reasonable three-level evaluation index system for brownfield redevelopment was established. In order to reduce the subjectivity in the evaluation process, an unbiased scientific brownfield redevelopment evaluation model was constructed using the continuous ordered weighted averaging operator-topology method. The evaluation decision system was applied to the renovation of a tract project in Chengdu, China. The results proved that the model could effectively and accurately evaluate the quality level of the brownfield redevelopment project, and the proposed recommendations can provide a basis for decision-making.
Many older people are facing various risks of cognitive impairment, while outdoor activities in open spaces may be helpful for their cognitive health. However, the effect of open spaces on cognitive health is unclear. This study aims to investigate the relationships between the cognitive health of older people and the built environment of open spaces. A questionnaire survey of 60 older people aged 60 and above was conducted. Results identified three major components of the built environment of open spaces, namely, planning, supporting facilities, and building services. According to the correlation and regression analysis, it is revealed that 8 BEOS items, including green ratio, a width of the pathway, maintenance of the whole garden, the color of green space, diversity of plants, location, and font of signage, artificial light of sitting area were positively related to memory, while only the size was negatively associated with memory. Only the green ratio could positively predict the concentration. The judgment was positively influenced by the green ratio, width of pathways, maintenance of the whole garden, color of green space and diversity of plants. A BEOS – cognitive health model for older people was built in this study. The results highlighted the importance of plants for cognitive health. Several recommendations, such as not-so-large sizes and diverse plants with vivid colors and signages with big fonts, etc., were proposed to improve the built environment of the open spaces and support the declining cognitive health of older people.