The relational shift in urban ecology: From place and structures to multiple modes of coproduction for positive urban futures.

This perspective emerged from ongoing dialogue among ecologists initiated by a virtual workshop in 2021. A transdisciplinary group of researchers and practitioners conclude that urban ecology as a science can better contribute to positive futures by focusing on relationships, rather than prioritizing urban structures. Insights from other relational disciplines, such as political ecology, governance, urban design, and conservation also contribute. Relationality is especially powerful given the need to rapidly adapt to the changing social and biophysical drivers of global urban systems. These unprecedented dynamics are better understood through a relational lens than traditional structural questions. We use three kinds of coproduction-of the social-ecological world, of science, and of actionable knowledge-to identify key processes of coproduction within urban places. Connectivity is crucial to relational urban ecology. Eight themes emerge from the joint explorations of the paper and point toward social action for improving life and environment in urban futures.

A transformative shift in urban ecology toward a more active and relevant future for the field and for cities.

This paper builds on the expansion of urban ecology from a biologically based discipline-ecology in the city-to an increasingly interdisciplinary field-ecology of the city-to a transdisciplinary, knowledge to action endeavor-an ecology for and with the city. We build on this "prepositional journey" by proposing a transformative shift in urban ecology, and we present a framework for how the field may continue this shift. We conceptualize that urban ecology is in a state of flux, and that this shift is needed to transform urban ecology into a more engaged and action based field, and one that includes a diversity of actors willing to participate in the future of their cities. In this transformative shift, these actors will engage, collaborate, and participate in a continuous spiral of knowledge → action → knowledge spiral and back to knowledge loop, with the goal of co producing sustainable and resilient solutions to myriad urban challenges. Our framework for this transformative shift includes three pathways: (1) a repeating knowledge → action → knowledge spiral of ideas, information, and solutions produced by a diverse community of agents of urban change working together in an "urban sandbox"; (2) incorporation of a social-ecological-technological systems framework in this spiral and expanding the spiral temporally to include the "deep future," where future scenarios are based on a visioning of seemingly unimaginable or plausible future states of cities that are sustainable and resilient; and (3) the expansion of the spiral in space, to include rural areas and places that are not yet cities. The three interrelated pathways that define the transformative shift demonstrate the power of an urban ecology that has moved beyond urban systems science and into a realm where collaborations among diverse knowledges and voices are working together to understand cities and what is urban while producing sustainable solutions to contemporary challenges and envisioning futures of socially, ecologically, and technologically resilient cities. We present case study examples of each of the three pathways that make up this transformative shift in urban ecology and discuss both limitations and opportunities for future research and action with this transdisciplinary broadening of the field.

Cities in nature.

More than half of the world's population live in cities, and they have benefitted from the ecosystem services provided by urban biodiversity. International conventions like the Convention on Biological Diversity have provided recommendations on how to engage local governments and cities in the implementation of their strategic plans. In parallel, recognizing this, cities conserve, restore and enhance biodiversity in many practical ways. A list of general strategies adopted by cities is presented. The rich and diverse experiences of eleven cities, i.e. Abu Dhabi, Auckland, Durban, Edinburgh, Edmonton, Hyderabad, Los Angeles, São Paulo, Singapore, Toluca and Vitoria-Gasteiz, which have successfully conserved biodiversity in urbanized landscape across the globe, are shared. These cities have all applied the Singapore Index on Cities' Biodiversity as an evaluation and monitoring tool for biodiversity conservation efforts, in addition to using it innovatively for other purposes. Cities can play a pivotal role in ensuring that Target 12 of the Kunming-Montreal Global Biodiversity Framework will be achieved. Upscaling cities' models of success would require a worldwide concerted effort involving everyone, i.e. all levels of stakeholders. Mainstreaming of biodiversity into all sectors, including commercial, economic, financial, industrial and technological, and the incorporation of biodiversity into decision-making in urban planning and management would be a game-changer. This article is part of the theme issue 'Bringing nature into decision-making'.

"Modernism with a Soul": Designing and Building Communities for Corporate and Civic Life.

This essay explores how film, feature and documentary, can offer a new perspective on modernist architecture, industrial design, and urban planning. Through the lens of two young directors, Kogonada and Davide Maffei, it traces the histories of two twentieth-century company towns: Ivrea, Italy, headquarters of Italian business machine giant Olivetti, and Columbus, Indiana, U.S.A., home to Cummins Inc., a global leader in diesel engine design and manufacturing. Adriano Olivetti and J. Irwin Miller shared the conviction that modernist architecture and design had a decisive role to play not just in the economic health of their respective firms but in the civic health of their surrounding communities. These companies have long abandoned the corporate idealism of their founding patrons. In film, Ivrea and Columbus have become architectural time capsules that raise important questions about the transformative power of architecture and design in the face of an increasingly competitive global economy.

Climate crisis risks to elderly health: strategies for effective promotion and response.

The climate crisis significantly impacts the health and well-being of older adults, both directly and indirectly. This issue is of growing concern in Canada due to the country's rapidly accelerating warming trend and expanding elderly population. This article serves a threefold purpose: (i) outlining the impacts of the climate crisis on older adults, (ii) providing a descriptive review of existing policies with a specific focus on the Canadian context, and (iii) promoting actionable recommendations. Our review reveals the application of current strategies, including early warning systems, enhanced infrastructure, sustainable urban planning, healthcare access, social support systems, and community engagement, in enhancing resilience and reducing health consequences among older adults. Within the Canadian context, we then emphasize the importance of establishing robust risk metrics and evaluation methods to prepare for and manage the impacts of the climate crisis efficiently. We underscore the value of vulnerability mapping, utilizing geographic information to identify regions where older adults are most at risk. This allows for targeted interventions and resource allocation. We recommend employing a root cause analysis approach to tailor risk response strategies, along with a focus on promoting awareness, readiness, physician training, and fostering collaboration and benchmarking. These suggestions aim to enhance disaster risk management for the well-being and resilience of older adults in the face of the climate crisis.

Revisiting Urban Street Planning and Design Factors to Promote Walking as a Physical Activity for Middle-Class Individuals with Metabolic Syndrome in Cairo, Egypt.

This paper revisits the planning and design factors of "pedestrianized" and "walkable" urban streets to encourage physical activity, focusing on their prioritization according to public health and smart growth. The aim is to create a conceptual framework for urban planners and designers to encourage walking and reduce metabolic syndrome (MetS) risks. Through a scoping review, the study found that while pedestrianized and walkable streets share many planning and design factors, they have different objectives. The study explores how urban planning and design can reduce MetS risk among middle-class individuals using online video storytelling for 30 participants in three districts of Cairo, Egypt: El Zamalek, Old Cairo, and Heliopolis. It identifies three factors to address MetS symptoms for middle-class individuals: strategic, design-oriented, and technical. Practitioners and policymakers can use this framework to evaluate the impact of their work. This study is particularly relevant for cities in the Global South that are facing similar challenges.

Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis.

Semantic segmentation of cityscapes via deep learning is an essential and game-changing research topic that offers a more nuanced comprehension of urban landscapes. Deep learning techniques tackle urban complexity and diversity, which unlocks a broad range of applications. These include urban planning, transportation management, autonomous driving, and smart city efforts. Through rich context and insights, semantic segmentation helps decision-makers and stakeholders make educated decisions for sustainable and effective urban development. This study investigates an in-depth exploration of cityscape image segmentation using the U-Net deep learning model. The proposed U-Net architecture comprises an encoder and decoder structure. The encoder uses convolutional layers and down sampling to extract hierarchical information from input images. Each down sample step reduces spatial dimensions, and increases feature depth, aiding context acquisition. Batch normalization and dropout layers stabilize models and prevent overfitting during encoding. The decoder reconstructs higher-resolution feature maps using "UpSampling2D" layers. Through extensive experimentation and evaluation of the Cityscapes dataset, this study demonstrates the effectiveness of the U-Net model in achieving state-of-the-art results in image segmentation. The results clearly shown that, the proposed model has high accuracy, mean IOU and mean DICE compared to existing models.

Definition and characteristics of climate-adaptive cities: a systematic review.

BACKGROUND: Cities, as frontline responders to climate change, necessitate a precise understanding of climate-adaptive features. This systematic review aims to define and outline the characteristics of climate-adaptive cities, contributing vital insights for resilient urban planning. METHODS: This systematic review, initiated on March 6, 2018, and concluded on August 26, 2021, involved reviewing multiple electronic databases based on the study's objectives. The Critical Appraisal Skills Program (CASP) tool was used for quality assessment and critical evaluation of articles retrieved through a comprehensive and systematic text search. Descriptive and thematic analyses were conducted to extract definitions, features, and characteristics of climate-adaptive cities. RESULTS: Out of 6104 identified articles, 38 articles met the inclusion criteria. In total, 20 definitions and 55 features for climate-adaptive cities were identified in this review. Codes were categorized into two categories and ten subcategories. The categories included definitions and features or characteristics of climate-adaptive cities. CONCLUSION: A climate-adaptive city, as derived from the findings of this study, is a city that, through effective resource management, future-oriented planning, education, knowledge utilization, innovation in governance and industry, decentralized management, and low-carbon economy, leads to the adaptability, resilience, sustainability, and flexibility of the capacity of individuals, communities, institutions, businesses, and systems within a city against all climate change impacts and reduces their negative consequences.

Sustainability outcomes and policy implications: Evaluating China's "old urban neighborhood renewal" experiment.

Globally, old urban neighborhood transformation has become a new urban sustainability focus for its significant contribution to the United Nation's Sustainable Development Goal 11. A regeneration-oriented approach is particularly important for Chinese cities with a dwindling land supply, obsoleting infrastructure, and inadequate standard of living. Using a mixed-methods approach informed by BREEAM Communities, we examined two Chinese initiatives-old urban neighborhood renewal (OUNR) and sponge city development (SCD)-through a comprehensive study of pilot project sustainability, policy emphases and gaps, and broader governance implications. We found that SCD's top-down technocratic management was highly efficient in enhancing neighborhood hydrological functions and physical environment. However, successes were undermined by the lack of climate considerations and civic participation. Besides actionable recommendations for applied scholarship and policymaking in China, we provide insight into how the OUNR/SCD initiatives may broadly inform worldwide urban regeneration practices through project and policy experimentations that build adaptive capacity.

Exploring the combined cooling effect of street canyon geometry and the surrounding built environment.

Exploring the impact of complex urban morphology on the urban heat island (UHI) effect is essential for sustainable environmental management and enhancing human well-being. This study explored the combined cooling effect of street canyon geometry and the surrounding built environment using a CatBoost model and the Shapley method. The findings indicated that in streets with low building height and density, a high proportion of sky and vegetation and a flatter skyline are conductive to mitigate UHI effect. In streets with high building height and density, a lower proportion of sky and vegetation, and a well-proportioned skyline, can effectively mitigate UHI effect. Regardless of the building density and height around the street, street trees are the optimal choice for greening construction and improvement of large and medium-sized cities in China, given their high controllability and the current urban stock background. Therefore, reasonable control and allocation of street trees can effectively adjust the street canyon geometry, providing suitable cooling strategies for streets with different surrounding built environments. This study proposed a method to mitigate the UHI effect through street canyon geometry, which can be extended to other high-density urban thermal environment studies and guide policymakers on street construction and urban design.

Spatiotemporal assessment of the nexus between urban sprawl and land surface temperature as microclimatic effect: implications for urban planning.

Rapid urbanisation has led to significant environmental and climatic changes worldwide, especially in urban heat islands where increased land surface temperature (LST) poses a major challenge to sustainable urban living. In the city of Abha in southwestern Saudi Arabia, a region experiencing rapid urban growth, the impact of such expansion on LST and the resulting microclimatic changes are still poorly understood. This study aims to explore the dynamics of urban sprawl and its direct impact on LST to provide important insights for urban planning and climate change mitigation strategies. Using the random forest (RF) algorithm optimised for land use and land cover (LULC) mapping, LULC models were derived that had an overall accuracy of 87.70%, 86.27% and 93.53% for 1990, 2000 and 2020, respectively. The mono-window algorithm facilitated the derivation of LST, while Markovian transition matrices and spatial linear regression models assessed LULC dynamics and LST trends. Notably, built-up areas grew from 69.40 km2 in 1990 to 338.74 km2 in 2020, while LST in urban areas showed a pronounced warming trend, with temperatures increasing from an average of 43.71 °C in 1990 to 50.46 °C in 2020. Six landscape fragmentation indices were then calculated for urban areas over three decades. The results show that the Largest Patch Index (LPI) increases from 22.78 in 1990 to 65.24 in 2020, and the number of patches (NP) escalates from 2,531 in 1990 to an impressive 10,710 in 2020. Further regression analyses highlighted the morphological changes in the cities and attributed almost 97% of the LST variability to these urban patch dynamics. In addition, water bodies showed a cooling trend with a temperature decrease from 33.76 °C in 2000 to 29.69 °C in 2020, suggesting an anthropogenic influence. The conclusion emphasises the urgent need for sustainable urban planning to counteract the warming trends associated with urban sprawl and promote climate resilience.

Reimagining Urban Spaces: Green Spaces, Obesity, and Health Resilience in an Era of Extreme Heat.

Record-breaking heat waves intensified by climate change pose both environmental and health threats, necessitating a balance between urban sustainability and well-being. Extreme heat and limited green space access are drivers of obesity prevalence, with decreased proximity to green spaces correlating with higher rates of obesity in nearby communities. In contrast, access to such green spaces fosters physical activity, well-being, and community cohesion, especially crucial in marginalized communities facing health disparities due to historical policies like redlining and underinvestment in social gathering spaces. Despite challenges, green space investment offers healthcare savings and environmental gains, necessitating a shift in perception towards viewing green spaces as essential for urban living. As heat waves persist, integrating health and sustainability in urban planning is paramount. Health and medical communities must play an active role in advocating for equitable access to urban green spaces, as they possess influential positions to address climate-related health disparities through localized advocacy.

Effects of urban green space landscape pattern on flood retention efficiency from "urban-block" scale perspective.

Under the background of frequent flood disasters and stock planning challenges, clarifying the relationship and mechanism of urban green space landscape patterns and flood retention efficiency at multiple spatial scales has become a critical scientific issue in realizing the maximum flood retention efficiency of limited urban green spaces and improving the capabilities of urban flood control. We reviewed and summarized the factors, mechanisms, and scale differences in the influence of green space landscape patterns on flood retention efficacy at the urban and block scales. Based on the causes for differences in conclusions and research deficiencies, we suggested that future studies should focus on watershed-scale research and expand the investigation into three-dimensional green space landscape patterns. Additionally, attention should be paid to urban and suburban areas separately, and a set of research indices with indicative significance for the flooding process should be established for different flood-sensitive areas and block structures. These measures will help quantitatively reveal how green space landscape patterns of urban and block scales affect flooding process, providing theoretical guidance for urban planning and establishing urban flood safety patterns.

Disappearing cities on US coasts.

The sea level along the US coastlines is projected to rise by 0.25-0.3 m by 2050, increasing the probability of more destructive flooding and inundation in major cities1-3. However, these impacts may be exacerbated by coastal subsidence-the sinking of coastal land areas4-a factor that is often underrepresented in coastal-management policies and long-term urban planning2,5. In this study, we combine high-resolution vertical land motion (that is, raising or lowering of land) and elevation datasets with projections of sea-level rise to quantify the potential inundated areas in 32 major US coastal cities. Here we show that, even when considering the current coastal-defence structures, further land area of between 1,006 and 1,389 km2 is threatened by relative sea-level rise by 2050, posing a threat to a population of 55,000-273,000 people and 31,000-171,000 properties. Our analysis shows that not accounting for spatially variable land subsidence within the cities may lead to inaccurate projections of expected exposure. These potential consequences show the scale of the adaptation challenge, which is not appreciated in most US coastal cities.

Tool for fast assessment of stormwater flood volumes for urban catchment: A machine learning approach.

Specific flood volume is an important criterion for evaluating the performance of sewer networks. Currently, mechanistic models - MCMs (e.g., SWMM) are usually used for its prediction, but they require the collection of detailed information about the characteristics of the catchment and sewer network, which can be difficult to obtain, and the process of model calibration is a complex task. This paper presents a methodology for developing simulators to predict specific flood volume using machine learning methods (DNN - Deep Neural Network, GAM - Generalized Additive Model). The results of Sobol index calculations using the GSA method were used to select the ML model as an alternative to the MCM model. It was shown that the DNN model can be used for flood prediction, for which high agreement was obtained between the results of GSA calculations for rainfall data, catchment and sewer network characteristics, and calibrated SWMM parameters describing land use and sewer retention. Regression relationships (polynomials and exponential functions) were determined between Sobol indices (retention depth of impervious area, correction factor of impervious area, Manning's roughness coefficient of sewers) and sewer network characteristics (unit density of sewers, retention factor - the downstream and upstream of retention ratio) obtaining R2 = 0. 55-0.78. The feasibility of predicting sewer network flooding and modernization with the DNN model using a limited range of input data compared to the SWMM was shown. The developed model can be applied to the management of urban catchments with limited access to data and at the stage of urban planning.

Making cities mental health friendly for adolescents and young adults.

Urban life shapes the mental health of city dwellers, and although cities provide access to health, education and economic gain, urban environments are often detrimental to mental health1,2. Increasing urbanization over the next three decades will be accompanied by a growing population of children and adolescents living in cities3. Shaping the aspects of urban life that influence youth mental health could have an enormous impact on adolescent well-being and adult trajectories4. We invited a multidisciplinary, global group of researchers, practitioners, advocates and young people to complete sequential surveys to identify and prioritize the characteristics of a mental health-friendly city for young people. Here we show a set of ranked characteristic statements, grouped by personal, interpersonal, community, organizational, policy and environmental domains of intervention. Life skills for personal development, valuing and accepting young people's ideas and choices, providing safe public space for social connection, employment and job security, centring youth input in urban planning and design, and addressing adverse social determinants were priorities by domain. We report the adversities that COVID-19 generated and link relevant actions to these data. Our findings highlight the need for intersectoral, multilevel intervention and for inclusive, equitable, participatory design of cities that support youth mental health.

Study of medium and long-term free flow capacity and queue discharge rates on roads.

With the rise in vehicle ownership, traffic congestion has emerged as a major barrier to urban progress, making the study and optimization of urban road capacity exceedingly crucial. The research on the medium and long-term free-flowing capacity and queue emission rate of roads takes an in-depth exploration of this issue from a cutting-edge perspective, aiming to find solutions adaptable to the progression of the times. The purpose of this study is to understand and predict the road capacity and queue emission rate more accurately, thus improving the urban traffic condition. Existing literature primarily focuses on short-term forecasts of road capacity, leaving a notable void in the research of medium and long-term road capacity and queue emission rate. This gap often results in a lack of sufficient foresight when urban traffic planning faces practical issues. To fill this void, this study undertook an in-depth examination of the road capacity and queue emission rate over the medium and long term (10 years) based on big data analysis and artificial intelligence theories. This paper employs a Radial Basis Function (RBF) neural network, combined with twelve other parameters that could potentially impact road capacity, such as traffic volume, road width, number of lanes, traffic signal control methods, etc., to analyze the relationship between each parameter and free-flow traffic and queue emission rate. These analyses are grounded in extensive road data, encompassing not only the city's main roads but also secondary roads and community roads. The study results show a continuous downward trend in the free-flowing capacity of roads and a slight upward trend in the queue emission rate over the past decade. Further analysis reveals the extent of impact each factor has on the free-flow traffic and queue emission rate, providing a scientific basis for future urban traffic planning.