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The concept of digital twin has acquired attention in urban planning and design for its potential to revolutionize city understanding, planning, and management. This article explores the contributions of digital twin technology to smart city planning and development, aiming to understand its functionalities, benefits, and limitations. An overview of digital twin definition and functionalities is provided, emphasizing their ability to create virtual city replicas and simulate different scenarios. Case studies from London, Zürich, and Athens exemplify digital twin applications, and a comparative analysis reveals diverse objectives, technology deployments, user interaction levels, outcomes, and funding sources. Findings demonstrate digital twins as powerful tools for improved decision-making, resource allocation, and infrastructure management. They also facilitate stakeholder collaboration, community engagement, and evidence-based policy design. However, challenges related to data integration, privacy, and scalability exist. Nonetheless, results underscore the relevance and transformative potential of digital twins in shaping smart cities and fostering sustainable urban environments.

Prediction and monitoring of urban sprawl is a significant urban issue for planners, decision makers, and local authorities in terms of spatial data, strategies, and prediction models. Egyptian cities have expanded rapidly in the last 40 years. This uncontrolled urban growth requires a review of Egyptian urban policies and regulations. The Greater Cairo Region (GCR) is Egypt's economic capital and a significant industrial and commercial city. This study uses spatio-temporal data to suggest an approach based on integrating cellular automata (CA) and multicriteria evaluation (MCE) like analytical hierarchy process (AHP) and running it within the geographical information system (GIS) for monitoring, analyzing, and allocating informal growth in the context of unplanned regions like the GCR. At first, the weights of influencing growth factors were determined and calculated using AHP. Next, the probability map was created according to AHP weights. The historical probability map was then generated based on the historical development. Then a standalone CA macro was developed based on AHP weights to calculate the proximity index for existing urban and transportation features using Moore's extended neighborhood matrix. Finally, the general suitability map was created to identify the most sensitive areas for growth over the next two decades. The prediction process was performed based on the 2012 urban boundary. Then, the prediction accuracy was verified using the Kappa coefficient based on actual urban extents in 2017. The results showed that 676 km2 (35%) of the study area was not sensitive, 386.5 km2 (20%) was slightly sensitive, 522 km2 (27%) was almost sensitive, and 348 km2 (18%) was extremely sensitive to urban sprawl. Finally, we predicted the urban growth for the period from 2022 to 2052 for every 5 years. The outcomes showed a linear scattered sprawl pattern along transportation features and an annular pattern around existing urban spaces. Therefore, fertile farming land and natural resources in the GCR are set to become almost extinct over the next two decades, threatening food production and security. These results indicate the necessity to modify the region's urban policies to protect the agricultural areas and control the unplanned urban sprawl. [ABSTRACT FROM AUTHOR]

Urban models are fundamental in the theoretical and empirical discussions about cities. However, the Latin American city models proposed by German geographers have not been questioned much despite their use, and there are few studies outside the large metropolitan areas. Therefore, this article, using geodemography, seeks to identify whether there is a residential structure pattern in the intermediate cities of Mexico’s National Urban System. This methodological proposal looks to use new spatial analysis tools focused on lifestyles and the study of one of the great layers that urban models have: their residential structure. The results show that, firstly, using the models and their temporalities as a kaleidoscope, it is possible to identify the multiple patterns of cities and not just a single model. Secondly, a new disintegrated pattern appears where the classical models of the Chicago School are unrecognizable, and the fragmented city is left disintegrated. [ABSTRACT FROM AUTHOR]

On a global scale, the urban design of city centers is a topic of discussion concerning various aspects such development and its impact on public health. This research examines the health effects of urban agglomeration in city centers with compact, close development. In this work, the potentially toxic metals in street dust were studied by collecting and measuring street dust samples, measuring trace metal concentrations, and using index assessment, spatial analysis, correlation analysis, and health risk assessment models. Eskişehir, located in the part of Central Anatolia close to the Aegean region, west Türkiye, has been widely recognized as one of the most popular, known for having many narrow and old buildings in urban environments. The present paper investigates the atmospheric dust-related chemical speciation, urban environmental pollution, and human health risks in Eskişehir City by studying 66 dust samples collected at 11 points in the selected streets in August 2023. the study found that the concentrations of trace elements followed the order Cr > Ni > Pb > Cd > Cu. The primary source of these high levels is believed to be traffic-related contamination involving Cd, Pb, and Ni. The assessment of non-carcinogenic health risks has shown that the significant sources of potential toxic metals exposure for both children and adults are i) through ingestion and ii) dermal contact. The Hazard index (HI) for selected metals decreased in the order Cr > Pb > Ni > Cd > Cu for both children and adults without imposing possible non-carcinogenic risk (HI<1). On the contrary, Cr posed cancer risks above the safety threshold (> 10-4) through ingestion. Based on the available findings, Eskişehir still suffers from considerable environmental and ecological degradation and severe health risks due to street dust contamination. However, while high pollution was detected in the city center, where there is commercial land use, low values were observed in the region, rich with the water surface, bicycle paths, landscape design, and where traffic is slowed down. [ABSTRACT FROM AUTHOR]

Abstract Due to their importance in weather and climate assessments, there is significant interest to represent cities in numerical prediction models. However, getting high resolution multi-faceted data about a city has been a challenge. Further, even when the data were available the integration into a model is even more of a challenge due to the parametric needs, and the data volumes. Further, even if this is achieved, the cities themselves continually evolve rendering the data obsolete, thus necessitating a fast and repeatable data capture mechanism. We have shown that by using AI/graphics community advances we can create a seamless opportunity for high resolution models. Instead of assuming every physical and behavioral detail is sensed, a generative and procedural approach seeks to computationally infer a fully detailed 3D fit-for-purpose model of an urban space. We present a perspective building on recent success results of this generative approach applied to urban design and planning at different scales, for different components of the urban landscape, and related applications. The opportunities now possible with such a generative model for urban modeling open a wide range of opportunities as this becomes mainstream.

Due to their importance in weather and climate assessments, there is significant interest to represent cities in numerical prediction models. However, getting high resolution multi-faceted data about a city has been a challenge. Further, even when the data were available the integration into a model is even more of a challenge due to the parametric needs, and the data volumes. Further, even if this is achieved, the cities themselves continually evolve rendering the data obsolete, thus necessitating a fast and repeatable data capture mechanism. We have shown that by using AI/graphics community advances we can create a seamless opportunity for high resolution models. Instead of assuming every physical and behavioral detail is sensed, a generative and procedural approach seeks to computationally infer a fully detailed 3D fit-for-purpose model of an urban space. We present a perspective building on recent success results of this generative approach applied to urban design and planning at different scales, for different components of the urban landscape, and related applications. The opportunities now possible with such a generative model for urban modeling open a wide range of opportunities as this becomes mainstream. [ABSTRACT FROM AUTHOR]

Heat waves and extreme weather events caused by climate change increase people's need for predictable, healthy, and appropriate thermal thresholds in urban areas. The Mediterranean region, where alarming effects are expected, poses a danger to many species and threatens the quality of human life. In the research, predictions were made according to SSP 245 and SSP 585 scenarios from CNRM-CM6-1 climate models using the data of meteorological stations for 2020 in the Eastern Mediterranean region via CMIP6 and WorldClim database. The study aims to predict the change in the bioclimatic comfort situation of the region at 20-year intervals until 2100, depending on the periods. The highest annual temperatures seen in the area are 18–20 °C. In the 2100 estimations, areas with a value of 22–24 °C according to SSP 245 and 24–26 °C according to SSP 585 are modeled spatially. While the largest area in the basin today is the area with a humidity range of 62–64%, according to SSP 245, in 2100 predictions, the largest area will be 23% with a humidity level of 56–58%. While the wind speed in the area is currently 0.5–1 m/s, it decreases to 0–0.5 m/s in 36% of the area, according to SSP 585. According to the ETv index, quite cool areas are effective on a 36% area surface. However, in the 2100, compared to the SSP 245, the most comprehensive range is the slightly cool areas with 40%. According to SSP 585, mild areas will have a share of 42%. Warm areas, the most critical class of the index, will begin to form. According to DI, the field has a 58% share in the cold class. According to SSP 585, hot areas have a rate of 26%, and comfortable areas have a rate of 52%. Findings of thermal disturbance variation can help develop solutions to conditions in the context of the climatic values of the region. [ABSTRACT FROM AUTHOR]

The concept of digital twin has acquired attention in urban planning and design for its potential to revolutionize city understanding, planning, and management. This article explores the contributions of digital twin technology to smart city planning and development, aiming to understand its functionalities, benefits, and limitations. An overview of digital twin definition and functionalities is provided, emphasizing their ability to create virtual city replicas and simulate different scenarios. Case studies from London, Zürich, and Athens exemplify digital twin applications, and a comparative analysis reveals diverse objectives, technology deployments, user interaction levels, outcomes, and funding sources. Findings demonstrate digital twins as powerful tools for improved decision-making, resource allocation, and infrastructure management. They also facilitate stakeholder collaboration, community engagement, and evidence-based policy design. However, challenges related to data integration, privacy, and scalability exist. Nonetheless, results underscore the relevance and transformative potential of digital twins in shaping smart cities and fostering sustainable urban environments. [ABSTRACT FROM AUTHOR]

Sustainability of resources and combating global climate change are on the agenda at the beginning of the most fundamental problems based on nature worldwide. Although they cover a small area of the world's surface, urban growth and its accompanying efiects are the main culprits of these problems. Against these problems, blue-green areas are accepted as a fundamental tool of sustainable urban development in the context of nature-based solutions. The research primarily used CORINE land data; classi$cation was made under five primary headings: land cover, urban areas, industrial and commercial areas, forest areas, agricultural areas, and water surfaces. The 2030-year estimation of the fields was made using the cellular automata-Markov chain modeling method. As a result of the research, it has been determined that blue-green spaces are under severe construction pressure from 2006 to 2030. The suitability of the research model has been proven by the kappa-based method using kappa coeffcients (Klocation: 0.9338). [ABSTRACT FROM AUTHOR]

Population growth is inevitable in urban areas responsible for climate crises worldwide, and urban development is affected by processes fed by many dynamics. Predicting and planning the growth limits of the city effectively is a critical issue for achieving sustainable urban growth and managing climate risks. The study used the cellular automata-Markov chain method to define development areas regarding natural structure and land use/land cover. It aimed to present a method that can be applied to different urban areas by focusing on effective urban growth management with a climate-sensitive approach. It offered a climate-sensitive approach to determining growth limits according to scenarios. The boundaries of 2030 have been determined for the city of Bursa, which exhibited an increased average summer value of the land surface temperature from 24°C to 45°C between 2012 and 2021, stands out with its natural riches, and shows a rapid urban growth trend. The proposed method modeled the limits of urban growth with a climate-sensitive approach, and the model's suitability was demonstrated by Kappa statistics (Klocation = 0.8884). The determined urban boundary will reduce the rate of the urban built-up area from 86% to 70% by 2030. While the climate crisis threatens all life, urban activities, urban growth, and sprawl continue to increase rapidly. However, the growth of urban areas within certain limits is a critical need for engineering and urban planning. For decision makers, spatially determining the limits of human intervention in nature is an important guideline. Extreme weather events and disasters such as floods, tsunamis, and changes in water levels brought about by climate change can potentially cause chaotic crises. Loss of life and economic crises may occur in possible processes. Therefore, measures must be taken on behalf of humanity and life to adapt to climate effects and keep the level of impact under control. Spatial models based on a wide range of temporal contexts have a structure that broadens our perspective. The study provides an approach that can be implemented in various fields with models produced based on scenarios. [ABSTRACT FROM AUTHOR]

To understand urbanization across the Global South, it is indispensable to consider situated heterogeneous urban situations shaped by global and local forces and their intersections. In the case of Mexico, the political and economic desire for globalization has extended beyond the great metropolis of Mexico City to mid-size cities triggering the formulation of their own urban strategies to become global. This paper explores the connections between neoliberal public policy, globalization, urban modeling, and socio-territorial sustainability in the territorial binomial of the city of Puebla and the municipality of San Andrés Cholula in the period of 2011–2017 and its current consequences, addressed by the local planning route map, and informed by the Orange Economy-guide of the Inter-American Development Bank (IDB), using relevant bibliographical sources, mapping, interviews of stakeholders, and fieldwork. The ultimate purpose of the research project described herein is to provide a multi-dimensional analysis of the development of the territorial situation of the Puebla-San Andrés Cholula-urban binomial, and of its current and potential future consequences, offering supporting information for its urban planning. The research results exposed here reveal urban modeling processes informed by the Global North urban globalization theory, development of global cities in the Global South, local socio-territorial dynamics characterized by economic and political interests imprinted in the public policy, and socio-territorial patterns inherited from the colonial past, resulting in socio-economic and racial discrimination, population displacements, real estate speculation, and risking ecological and environmental sustainability. [ABSTRACT FROM AUTHOR]

In today's world, where the effects of climate change can be easily monitored, determining the resilience of cities and regions against climate crisis is a fundamental research area in terms of planning approaches. While producing spatial planning decisions, the effects of climate change should be analyzed in terms of time and integrated into the process. While the research reveals the change of spatial bioclimatic comfort zones according to climate change scenarios, it criticizes the position of planning practice within the framework of planning theory and a comprehensive planning approach. The research is carried out on the scale of the Western Mediterranean basin, one of the hot climate regions of Türkiye. The change between 2020 and 2100 is spatially revealed via the climate change scenarios. SSP 245 and SSP 585 are selected for this purpose. Discomfort Index (DI) and Effective Temperature-Taking Wind Velocity (ETv) techniques were used to classify bioclimatic comfort zones. As a result of the research, while the most common (20%) areas are between 16 and 18 °C, the most common temperature range rises to between 25% and 22–24 °C, according to SSP 585. According to DI simulations, 43% of the area is comfortable, and 38% is in cold areas. According to SSP 245, in 2100 forecasts, cold areas decrease to 9%, and hot areas that were not previously present occupy 13%. According to SSP 585, on the other hand, cold areas decrease to 2%, while hot areas reach 41%. With a more optimistic approach, the ETv index changes from a character dominated by slightly cool areas (35%) to mild (43%) and comfortable (26%) areas compared to SSP 585. However, some warm (7%) and quite hot (1%) areas do not exist. The increase in hot areas in the country, including coastal settlements with high tourism potential, is striking. While the research reveals the change of spatial bioclimatic comfort zones according to climate change scenarios, it criticizes the position of planning practice within the framework of planning theory and a comprehensive planning approach. Today, the position of spatial planning decisions based on long-term decisions in the country's legislation is discussed in the context of the climate crisis. [ABSTRACT FROM AUTHOR]

IntroductionIs Paris a 15-min city, where inhabitants can access essential amenities such as schools and shops with a 15-min walk or bike ride? The concept of a 15-min (more generally, X-minute) city was launched in the French capital and was part of the current mayor's plan in her latest re-election campaign. Yet, its fit with the existing urban structure had not been previously assessed.MethodsThis article combines open map data from a large participatory project and geo-localized socio-economic data from official statistics to fill this gap.ResultsWe show that, while the city of Paris is rather homogeneous, it is nonetheless characterized by remarkable inequalities between a highly accessible city center (though with some internal differences in terms of types of amenities) and a less well-equipped periphery, where lower-income neighborhoods are more often found. The heterogeneity increases if we consider Paris together with its immediate surroundings, the "Petite Couronne," where large numbers of daily commuters and other users of city facilities live.DiscussionWe thus conclude that successful implementation of the X-minute-city concept requires addressing existing socio-economic inequalities, and that especially in big cities, it should be extended beyond the narrow boundaries of the municipality itself to encompass the larger area around it.

The concentration of human activities in urban areas, increasing greenhouse gas emissions, and high global temperature values in urban areas have accelerated the research on global warming. They are the most widely used bioclimatic indices to describe the level of thermal sensation experienced by a person due to the changing climatic conditions of an urban area. Thermal comfort is an interdisciplinary spatial issue and a parameter directly affecting urban outdoor land uses. Thom's discomfort index was used to simulate two different climate change scenarios. This study aimed to predict the temporal and spatial changes of surface temperature, relative humidity, and bioclimatic comfort zones of Kocaeli province in terms of climate comfort in the context of SSP 245 and SSP 585 scenarios of IPCC. The current bioclimatic comfort areas throughout the region and their possible situations in 2040, 2060, 2080, and 2100 were modeled using ArcGIS 10.8 software. In the current map, 79.6% of the city consists of cool areas, 18.6% of cold, and 1.8% of comfortable regions. According to the SSP 245 scenario for the year 2100, it is observed that the cool and cold areas warm up, and the comfortable areas increase to 23.5%. According to the SSP 585 scenario, it was determined that comfortable areas reached 82.6%, and hot areas were formed in the province. The geographical structure's effect on the regions' heating draws attention. [ABSTRACT FROM AUTHOR]

Natural disasters have been increased in areas, where people live densely, day by day. Istanbul 1999, Van 2011, and Izmir 2020 earthquakes were just some of the tragic events in the near past in Turkiye. The aim of this study was to define Van 2011 earthquakes effects as a sample on urban development by using land use/land cover projecting techniques. In this case, Van urban development (in urban macroform scale) was simulated without Van 2011 earthquakes based on existing urban development using the Cellular Automata Markov Chain (CA-MARKOV) approach for the year 2018. Effects of the earthquake were determined on urban development by comparing modeling results with observed 2018 built up areas. So that significant physical and social driving factors were evaluated including road distance, slope, hillshade, ground stability, and land use ability, and weighting values on urban development were calculated under the influence of the natural disaster. Van urban built up areas were mapped using high-spatial resolution remote sensing instruments such as SPOT, ASTER, RapidEye, and Göktürk 2 satellite dataset for 1988—2002—2011, and 2018 images applying an object-based classification approach (OBC). First of all, the model was validated using 1988, 2002, and 2011 urban development maps. The Kappa accuracy was found to be 0.85, respectively, for the model. Defined urbanization drivers were applied to the 2002–2011 time period to simulate 2018 urban areas without any earthquake. The results indicated that urban areas were affected by earthquakes. If there was no earthquake, urban development to the periphery would be 30% less. Additionally, 10% more built up areas would be constructed on ground sensitive areas, and only 2% of the new constructions would be established on suitable lands. Today this ratio is around 8%. As a result, urban development has been a trend to move from flat land to slight slopes and has been moved away from roads and settlements. It was determined that the spread into the city was accelerated as well as spread toward the periphery due to the earthquake. [ABSTRACT FROM AUTHOR]

The impact of urbanization on local weather patterns affects over half the global population. Global numerical weather prediction systems have reached a resolution at which urban conurbations can be spatially resolved, justifying their representation within land surface parameterizations with the aim of improving local predictions. Additionally, real‐time atmospheric monitoring of trace gas emissions can utilize weather variables relevant for urban areas. We investigated whether a simple single‐layer urban canopy scheme can be used within a global forecast model to jointly improve predictions of near‐surface weather variables and residential CO2 emissions. The scheme has been implemented in the Integrated Forecast System used operationally at the European Centre for Medium‐Range Weather Forecasts running at ∼9 km horizontal resolution. First, we selected a suitable urban land cover map (ECOCLIMAP‐SG) based on comparisons with regional data and land surface temperature MODIS retrievals. The urban scheme is verified by providing improved 2 m temperature (∼10%) and 10 m wind (∼17%) RMSE values for both summer and winter months around urban environments. The influence of the scheme was most noticeable at night. Additionally, we have implemented a simple temperature‐dependent residential emissions model to calculate real‐time CO2 heating emissions. These were validated against existing offline products, national reporting and by comparing atmospheric simulations with total column CO2 observations. The results show an improved temporal variability of emissions, which arise from synoptic scale temperature changes. Given the improved predictability from the urban scheme for both weather and emissions, it will be operationally implemented in an upcoming model cycle. Plain Language Summary: In urban areas, temperatures are often elevated due to an effect known as the urban heat island. Although global weather forecasts, generated using computer models, typically include a representation of land surface processes, they often do not include the urban environment. We implemented a relatively simple urban scheme in the model of the European Centre for Medium‐Range Weather Forecasts and selected an appropriate urban cover map to use by comparing forecast land temperatures with satellite observations. We then compared this scheme with observations from urban sites around the globe and found improved temperature and wind forecasts. Furthermore, we used information from the urban scheme to generate a global forecast of residential CO2 emissions from heating. We find that by forecasting these emissions using the weather model we improve our prediction of atmospheric CO2 concentrations around urban environments. Key Points: Several urban land cover maps were evaluated using satellite land‐surface temperature retrievals and independent dataAt ∼9 km horizontal resolution, an urban scheme improves modeled 2 m temperature and 10 m wind forecasts over urban areas of varying sizeAn online residential heating CO2 emissions model (Modeling Emissions from Heating in Near‐real‐time Driven by the Integrated Forecasting System) using model variables improves forecasts of atmospheric concentrations [ABSTRACT FROM AUTHOR]

To understand urbanization across the Global South, it is indispensable to consider situated heterogeneous urban situations shaped by global and local forces and their intersections. In the case of Mexico, the political and economic desire for globalization has extended beyond the great metropolis of Mexico City to mid-size cities triggering the formulation of their own urban strategies to become global. This paper explores the connections between neoliberal public policy, globalization, urban modeling, and socio-territorial sustainability in the territorial binomial of the city of Puebla and the municipality of San Andrés Cholula in the period of 2011–2017 and its current consequences, addressed by the local planning route map, and informed by the Orange Economy-guide of the Inter-American Development Bank (IDB), using relevant bibliographical sources, mapping, interviews of stakeholders, and fieldwork. The ultimate purpose of the research project described herein is to provide a multi-dimensional analysis of the development of the territorial situation of the Puebla-San Andrés Cholula-urban binomial, and of its current and potential future consequences, offering supporting information for its urban planning. The research results exposed here reveal urban modeling processes informed by the Global North urban globalization theory, development of global cities in the Global South, local socio-territorial dynamics characterized by economic and political interests imprinted in the public policy, and socio-territorial patterns inherited from the colonial past, resulting in socio-economic and racial discrimination, population displacements, real estate speculation, and risking ecological and environmental sustainability.

With the expansion of model scale and the improvement of model accuracy, the real-time rendering and displaying of 3D mesh models remain infeasible. To relieve such pressure, mesh simplification methods have been proposed to reduce the structural complexity while preserving the appearance. This work introduces a shape-preserving simplification method for urban building models. Compared to traditional simplification methods that only consider preserving local geometric features, we also consider the overall shapes of building models to avoid collapse with an increased simplification rate. The proposed method works in four steps. First, we filter mesh models to yield planar structures while preserving sharp features. Second, we detect the shapes of planar regions. Third, we simplify the planar and non-planar regions constrained by the overall shapes and local geometric features. Finally, we remap the texture. Experiments show the effectiveness of this method by evaluating it on various building models and comparing its performance with the original QEM algorithms. Furthermore, we maintain better spatial consistency in building models with different levels of detail (LOD) than traditional methods. [ABSTRACT FROM AUTHOR]

Due to extensive population growth, urbanization increases urban development and sprawl in the world's cities. Urban sprawl is a socioeconomic phenomenon that has not extensively incorporated socioeconomic factors in the prediction of most of the urban sprawl models. This study aimed to predict the urban sprawl pattern in 2030 by integrating socioeconomic and biophysical factors. NDBI, Cramer's V, logistic regression, and CA-Markov analyses were used to classify and predict built-up patterns. The built-up area is the dominant land use, which had a gradual growth from 1990 to 2020. A total of 20 socioeconomic and biophysical factors were identified as potentials in the municipality, affecting the urban sprawl. Policy regulation was the most attractive driver with a positive association, and land value had a high inverse association. Three prediction scenarios for urban sprawl were achieved for 2030. Higher sprawling growth is expected in scenario 3, compared with scenarios 1 and 2. Scenario 3 was simulated with biophysical and socioeconomic factors. This study aids in addressing urban sprawl at different spatial and temporal scales and helps urban planners and decision makers enhance the development strategies in the municipality. Predicted maps with different scenarios can support evaluating future sprawling growth and be used to develop sustainable planning for the city. [ABSTRACT FROM AUTHOR]

More than half a century has passed since the first use of models in urban planning. Most urban planners have agreed on using models either to simplify complicated systems or to make simulations of such systems in order to predict their future. There is, however, disagreement on how far such simplifications and simulations have worked toward the planners' goals and objectives. In this paper, through historical analysis, we placed the model-theory interaction into the broader scope of scientific modeling to develop guidelines applicable to the narrow field of urban modeling. Here, we developed an argument that models' applicability and meaningfulness in urban planning are primarily dependent on planning theories, that is, models and theories should move parallel to achieve all the functions and capabilities claimed by models. Thus, an interactive process shapes the model as the mediator between the theory and the phenomenon: (a) the theory explains an abstract phenomenon, (b) the model provides an understanding of that phenomenon, and (c) the original abstract explanation is revisited and made more practical. This evolutionary process is our view of the "mediator model," that is, a new definition of the urban model. [ABSTRACT FROM AUTHOR]

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Intersections appear where one street crosses another, acting as fundamental nodes embedded in the network of urban public space. Though discussed in configurational and perceptive studies, limited attention has been paid to the morphological aspects of intersections. This study proposes and tested a new approach to modeling the urban intersection form. First, effective cylinder was introduced to define the related space for each intersection based on its scale. Second, a set of morphological indicators were presented to measure the physical properties of the intersection form. Third, the affinity propagation algorithm was used to examine the patterns of intersection form.Using the Old City of Nanjing, China as the study area, 844 intersections were analyzed to test this new method. As a result, we were able to classify the intersections into eight types. This study shows that the intersection can be modelled as a volumetric and integral spatial unit of urban form, which may demand more attention from urban designers and architects in the future for shaping the built environment. The quantitative nature of our method could also open more possibilities for intersection-based studies.

• A pipeline is formulated to extract window to wall ratios from building façades. • A grammar based and learning based method are compared for performance efficacy. • The learning-based method shows higher accuracy than the grammar-based method. • A hybrid method combining the strengths of the methods achieves higher accuracy. • An algorithm utilizing the learning-based method extracts detailed building heights. Urban feature extraction methods have presented multiple opportunities in the field of environmental building performance studies, and urban assessments. With reference to façade features, window size and position are key parameters that influence occupant perception and environmental performance of indoor spaces. A myriad of methods have been proposed to automatically detect façade window layouts from street view images yet it is still unclear how to assess the strengths and limitations of these methods or how they can be combined for higher detection performance. This paper aims to add clarity for those aiming to use computer vision techniques for façade layout extraction for urban level sustainability assessments. An automated pipeline to enable the extraction and detection of WWRs (Window to Wall ratios) is introduced that is based on two fundamentally different computational approaches; a grammar-based edge detection framework (Method 1) and a learning-based method (Method 2) that utilizes CNNs (Convolutional Neural Networks). The paper then compares the detection efficacy of both methods, focusing on WWR accuracy, in New York and Lisbon, including their ability to extract more detailed façade properties such as floor-to-floor heights. The study finds that the learning-based method shows lower error scores across the two cities. In Lisbon, 69 % of conditions were detected within the 10 % error range and 91 % were within the 20 % range under Method 1. Under Method 2, 82.5 % of conditions were within the 10 % error range and 95 % were within the 20 % range. In New York, 66 % of conditions were within the 10 % error range and 90 % were within the 20 % range under Method 1 while 77.5 % of conditions were within the 10 % error range and 93 % were within the 20 % range under Method 2. Finally, a hybrid method is proposed to leverage the strengths of the two models, and higher accuracies are obtained in both the New York and Lisbon dataset. In New York, 96.5 % are now detected within the 20 % error range and 81.5 % within the 10 % error range. In Lisbon, 96 % are now detected within the 20 % error range and 83.5 % within the 10 % error range. With reference to the total building height extraction formulated under Method 2, the results show a relative error of 3.5 % in height estimation in the sample set. [ABSTRACT FROM AUTHOR]

We present a system to extract architectural assets from large-scale collections of panoramic imagery. We automatically rectify and crop parts of the panoramic image that contain dominant planes, and then use object detection to extract assets such as façades and windows. We also provide various tools to identify attributes of the assets to determine the asset quality and index the assets for search. In addition, we propose a User Interface (UI) to visualize and query assets. Finally, we present applications for urban modeling and texture synthesis. [ABSTRACT FROM AUTHOR]

This study evaluates the impact of land surface models (LSMs) and urban heterogeneity [using local climate zones (LCZs)] on air temperature simulated by the Weather Research and Forecasting model (WRF) during a regional extreme event. We simulated the 2017 heatwave over Europe considering four scenarios, using WRF coupled with two LSMs (i.e., Noah and Noah‐MP) with default land use/land cover (LULC) and with LCZs from the World Urban Database and Access Portal Tools (WUDAPT). The results showed that implementing the LCZs significantly improves the WRF simulations of the daily temperature regardless of the LSMs. Implementing the LCZs altered the surface energy balance partitioning in the simulations (i.e., the sensible heat flux was reduced and latent heat flux was increased) primarily due to a higher vegetation feedback in the LCZs. The changes in the surface flux translated into an increase in the simulated 2‐m relative humidity and 10‐m wind speed as well as changed air temperature within cities section and generated a temperature gradient that affected the temperatures beyond the urban regions. Despite these changes, the factor separation analysis indicated that the impact of LSM selection was more significant than the inclusion of LCZs. Interestingly, the lowest bias in temperature simulations was achieved when WRF was coupled with the Noah as the LSM and used WUDAPT as the LULC/urban representation. Key Points: Sensitivity of weather research and forecasting model (WRF) heatwave simulation to surface parameterization and urban heterogeneityFirst results to show the use of local climate zones improves large‐scale WRF simulationUrban representation can affect temperatures beyond the urban grids regionally [ABSTRACT FROM AUTHOR]

The advancements in Information and Communication Technologies (ICT) made the concept of Smart Cities into reality. In a smart city several Internet of Things (IoT) sensors are deployed across several locations to collect the data about traffic, drainage, mobility of citizens etc. and the insights gained from these data are used to manage resources, assets etc. effectively. Deep Learning has been used extensively on the data generated by IoT sensors in a smart city by several researchers. In this article an attempt is made to survey several state‐of‐the art on usage of Deep Learning on Smart City data. Several future research directions are suggested at the end of the article. [ABSTRACT FROM AUTHOR]

Spatial experience in historical street corridors is essential to encourage a continuously satisfying experience of a historical aesthetic leading to a better quality of the historic urban landscape, which is significant for making precious memory of the city's history. 3D spatial formation along the historic street corridor fosters the generation of historical memory of the urban space. Both tangible and intangible aspects attached to the historic street corridors' spatial configuration have significant meaning that forms the integrity of the valuable historical urban space. The research area is in Kayutangan street as one of the historical street corridors in Malang City, East Java, Indonesia. The study aims to develop the historical spatial data system of the Kayutangan corridor to construct an online digital spatial database and enforce it as a policy decision reference by the government in managing the urban development in historical areas, especially in the Kayutangan street corridors. The 3D spatial development of historic urban landscape performed the combination of 3D modeling software, 3D visualization software, and 3D spatial multimedia application authoring platforms. The collaboration of three systems generated three spatial data types, namely a 3D spatial-passive observation data, a 3D spatial-active observation data, and 3D spatial-interactive simulation data. As a result, this study produces 3D spatial multimedia contained the 3D spatial of historical data of Kayutangan streetscape, which performs as a historical spatial data system to reference the smart development of cultural tourism and heritage cities in Malang.

Objective:The worn out tissues are one of the most problematic parts of the city, which is not a prerequisite for healthy living for the residents, and it is necessary to pay attention to the principles and standards of the world as a healthy city. The purpose of the present study was to evaluate and evaluate the quality of life of the city with the healthy city approach in the corrosive tissues of Kashan city. Method: The method of this research is descriptive-analytic using field survey. The sample size was calculated using Sample Power software with a 95% confidence level and a potential error of 5% of 200 people. Results:Structural equation modeling in AMOS software was used to explain and model the effects. The results of t-test indicated that the effective factors of urban quality of life in the healthy city in the worn out tissues are significant. The analysis of the results from structural equation modeling show s that among the indexed indicators, the environmental index has the highest factor load with the factor weight (-0.93) with the standards of the healthy city. After that, the safety and security index were ranked second with factor weight (0.88), urban infrastructure and facilities (0.83), social trust (0.63), social hope (0.57), material strength ( 0.38), accessibility (0.37), health and health (0.30), economic (0.27), physical area (0.26) and recreation and leisure (-0.21) are in the next stages. Conclusion: The results of the t-test and structural equation show that the effective factors of urban quality of life in urban contexts are significantly affected by a healthy city approach and by confirming the research hypotheses, it is clear that Kashan neighborhoods are far from healthy city standards.

There is an increasing availability of geospatial data describing patterns of human settlement and population such as various global remote-sensing based built-up land layers, fine-grained census-based population estimates, and publicly available cadastral and building footprint data. This development constitutes new integrative modeling opportunities to characterize the continuum of urban, peri-urban, and rural settlements and populations. However, little research has been done regarding the agreement between such data products in measuring human presence which is measured by different proxy variables (i.e. presence of built-up structures derived from different remote sensors, census-derived population counts, or cadastral land parcels). In this work, we quantitatively evaluate and cross-compare the ability of such data to model the urban continuum, using a unique, integrated validation database of cadastral and building footprint data, U.S. census data, and three different versions of the Global Human Settlement Layer (GHSL) derived from remotely sensed data. We identify advantages and shortcomings of these data types across different geographic settings in the U.S., which will inform future data users on implications of data accuracy and suitability for a given application, even in data-poor regions of the world.

With the expansion of model scale and the improvement of model accuracy, the real-time rendering and displaying of 3D mesh models remain infeasible. To relieve such pressure, mesh simplification methods have been proposed to reduce the structural complexity while preserving the appearance. This work introduces a shape-preserving simplification method for urban building models. Compared to traditional simplification methods that only consider preserving local geometric features, we also consider the overall shapes of building models to avoid collapse with an increased simplification rate. The proposed method works in four steps. First, we filter mesh models to yield planar structures while preserving sharp features. Second, we detect the shapes of planar regions. Third, we simplify the planar and non-planar regions constrained by the overall shapes and local geometric features. Finally, we remap the texture. Experiments show the effectiveness of this method by evaluating it on various building models and comparing its performance with the original QEM algorithms. Furthermore, we maintain better spatial consistency in building models with different levels of detail (LOD) than traditional methods.

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Copyright of Journal of The Planner & Development is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to extensive population growth, urbanization increases urban development and sprawl in the world’s cities. Urban sprawl is a socioeconomic phenomenon that has not extensively incorporated socioeconomic factors in the prediction of most of the urban sprawl models. This study aimed to predict the urban sprawl pattern in 2030 by integrating socioeconomic and biophysical factors. NDBI, Cramer’s V, logistic regression, and CA-Markov analyses were used to classify and predict built-up patterns. The built-up area is the dominant land use, which had a gradual growth from 1990 to 2020. A total of 20 socioeconomic and biophysical factors were identified as potentials in the municipality, affecting the urban sprawl. Policy regulation was the most attractive driver with a positive association, and land value had a high inverse association. Three prediction scenarios for urban sprawl were achieved for 2030. Higher sprawling growth is expected in scenario 3, compared with scenarios 1 and 2. Scenario 3 was simulated with biophysical and socioeconomic factors. This study aids in addressing urban sprawl at different spatial and temporal scales and helps urban planners and decision makers enhance the development strategies in the municipality. Predicted maps with different scenarios can support evaluating future sprawling growth and be used to develop sustainable planning for the city.

Abstract The societal benefits of numerical weather prediction (NWP) forecasts are most evident in populated areas. An urban representation within NWP models should provide improved forecast accuracy. Here, we present the preliminary implementation of an urban scheme within the Integrated Forecasting System (IFS) using a simplified single‐layer urban canopy model. The scheme makes assumptions of canyon geometry and considers fluxes from roads, walls, and roofs. Temperature observations were used to optimize single‐column model (SCM) parameters using the Gauss‐Newton method. Observation comparisons over six European cities, show a 2‐m temperature root‐mean‐squared error reduction from 1.85 to 1.75 K with the urban scheme. Optimized parameters were used globally at kilometric scale in a land surface model. A sensitivity experiment assuming a 100% urban world showed spatially averaged northern hemisphere 2‐m temperatures increased by 0.54 K (January) and 0.42 K (July) at night caused by changes in the albedo, emissivity, roughness, and thermal and hydrological properties. Global ∼1‐km resolution simulations using ancillary urban mapping information produce an urban heat island effect over major and minor conurbations. Only major conurbations were well represented at ∼9‐km resolution. Results from SCM simulations show a heightening of the planetary boundary layer over city sites, with the largest enhancements occurring at night in July (84 ± 48 m) caused by an increased sensible heat flux. These initial developments show the importance of a high‐resolution urban representation within NWP models. Improved parameterization and mapping will enable an online representation of energy, water, and trace gas fluxes over residential areas.

The societal benefits of numerical weather prediction (NWP) forecasts are most evident in populated areas. An urban representation within NWP models should provide improved forecast accuracy. Here, we present the preliminary implementation of an urban scheme within the Integrated Forecasting System (IFS) using a simplified single‐layer urban canopy model. The scheme makes assumptions of canyon geometry and considers fluxes from roads, walls, and roofs. Temperature observations were used to optimize single‐column model (SCM) parameters using the Gauss‐Newton method. Observation comparisons over six European cities, show a 2‐m temperature root‐mean‐squared error reduction from 1.85 to 1.75 K with the urban scheme. Optimized parameters were used globally at kilometric scale in a land surface model. A sensitivity experiment assuming a 100% urban world showed spatially averaged northern hemisphere 2‐m temperatures increased by 0.54 K (January) and 0.42 K (July) at night caused by changes in the albedo, emissivity, roughness, and thermal and hydrological properties. Global ∼1‐km resolution simulations using ancillary urban mapping information produce an urban heat island effect over major and minor conurbations. Only major conurbations were well represented at ∼9‐km resolution. Results from SCM simulations show a heightening of the planetary boundary layer over city sites, with the largest enhancements occurring at night in July (84 ± 48 m) caused by an increased sensible heat flux. These initial developments show the importance of a high‐resolution urban representation within NWP models. Improved parameterization and mapping will enable an online representation of energy, water, and trace gas fluxes over residential areas. Plain Language Summary: Urban areas make up only a small fraction of the Earth's surface; however, they are home to over 50% of the world's population. In these areas a phenomenon known as the urban heat island effect causes increased temperatures due to human activities, an effect often missing in weather forecasts. Forecasts, generated using computer models, consider not only the atmosphere but also the role of the land surface on the weather above. Typically these models do not include an urban map, so they miss key urban processes. We introduced a representation of urban areas to the model of the European Center for Medium‐Range Weather Forecasts. We considered several ways in which the urban environment interacts with the weather, including through changes in heat storage and treatment of rainfall. We find these developments result in a more accurate model forecast over six European cities. The model accurately predicts the increased heating observed over cities at night and some of the observed changes in the atmosphere. Future work should continue to improve the urban representation in weather and air quality/greenhouse gas models by implementing an urban scheme in operational forecasts. Key Points: An urban scheme has been introduced and optimized within the ECMWF IFS single‐column and surface‐only modelAssuming an urban world, average nighttime 2‐m temperatures increased for January (0.54 K) and July (0.42 K) in a surface only simulationUsing realistic urban cover for eight cities, PBL height in July increases by an average of 66 and 84 m for the day and night, respectively [ABSTRACT FROM AUTHOR]

This paper studies the important factor of sector-based time variable, which is critical to urban mobility patterns in an urban environment. In particular, this study analyzes urban traffic optimization based on modeling analysis of a simulated urban environment. In doing so, we develop and assess the urban traffic model based on three key components of agents, urban map, and mobility pattern. We develop an urban sample based on a medium-to-large city in China, which is represented by Manhattan grid pattern layout. By developing a homogeneous urban layout, we distribute the urban blocks of various sectors across the sample model. Through simulation studies, we model urban traffic based on “conventional operation hours” and “proposed operation hours” of all sectors. This urban traffic model is used to study the impact of the proposed approach on urban traffic based on two measured metrics of end-to-end delay (ETE) and Agent queue count (AQC). By suggesting a new sector-based time variable, we then evaluate the urban traffic model based on multiple active agent ratio. The findings from this simulation uncover the importance of sector-based time variable in optimizing urban traffic.

Intersections appear where one street crosses another, acting as fundamental nodes embedded in the network of urban public space. Though discussed in configurational and perceptive studies, limited attention has been paid to the morphological aspects of intersections. This study proposes and tested a new approach to modeling the urban intersection form. First, effective cylinder was introduced to define the related space for each intersection based on its scale. Second, a set of morphological indicators were presented to measure the physical properties of the intersection form. Third, the affinity propagation algorithm was used to examine the patterns of intersection form. Using the Old City of Nanjing, China as the study area, 844 intersections were analyzed to test this new method. As a result, we were able to classify the intersections into eight types. This study shows that the intersection can be modelled as a volumetric and integral spatial unit of urban form, which may demand more attention from urban designers and architects in the future for shaping the built environment. The quantitative nature of our method could also open more possibilities for intersection-based studies. [ABSTRACT FROM AUTHOR]

This paper demonstrates that a shift from a purely technical to a more socio-technical perspective has significant implications for the conceptualization, design, and implementation of smart city technologies. Such implications are discussed and illustrated through the case of an emerging urban analytics tool, the City-scale Digital Twin. Based on interdisciplinary insights and a participatory knowledge co-production and tool co-development process, including both researchers and prospective users, we conclude that in order to move beyond a mere "hype technology," City-Scale Digital Twins must reflect the specifics of the urban and socio-political context. [ABSTRACT FROM AUTHOR]

Introduction: Is Paris a 15-min city, where inhabitants can access essential amenities such as schools and shops with a 15-min walk or bike ride? The concept of a 15-min (more generally, X-minute) city was launched in the French capital and was part of the current mayor's plan in her latest re-election campaign. Yet, its fit with the existing urban structure had not been previously assessed., Methods: This article combines open map data from a large participatory project and geo-localized socio-economic data from official statistics to fill this gap., Results: We show that, while the city of Paris is rather homogeneous, it is nonetheless characterized by remarkable inequalities between a highly accessible city center (though with some internal differences in terms of types of amenities) and a less well-equipped periphery, where lower-income neighborhoods are more often found. The heterogeneity increases if we consider Paris together with its immediate surroundings, the "Petite Couronne," where large numbers of daily commuters and other users of city facilities live., Discussion: We thus conclude that successful implementation of the X-minute-city concept requires addressing existing socio-economic inequalities, and that especially in big cities, it should be extended beyond the narrow boundaries of the municipality itself to encompass the larger area around it., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Thaury, Genet, Maurice, Tubaro and Berkemer.)

Across the world, cities are spending billions of dollars to manage urban runoff through decentralized green infrastructure (GI). This research uses an agent‐based model to explore some of the physical, social, and economic consequences of one such urban GI programs. Using the Bronx, NY, as a case study, two alternative approaches to GI application are compared. The first (Model 1) mimics NYC's current GI program by opportunistically selecting sites for GI within the city's priority combined sewer watersheds; the second (Model 2) features a more spatially flexible approach to GI siting, in which the city attempts to maximize opportunities for co‐benefits within the geographic areas considered in Model 1. The effects of both approaches, measured in terms of stormwater captured and co‐benefits (e.g., carbon sequestered) provided, are tracked over 20‐year simulations. While both models suggest it will be difficult to meet the citywide stormwater capture goals (managing the first 2.5 cm of rainfall from 10% of impervious surfaces) in the Bronx solely through public investment in GI, Model 2 shows that by integrating GI with other city initiatives (e.g., sustainability goals and resilience planning), synergistic outcomes are possible. Specifically, Model 2 produces stormwater capture rates comparable to those obtained under Model 1, but these rates are accompanied by elevated co‐benefits for Bronx communities. The results are discussed in the context of future GI policy development in NYC. Key Points: An agent model explores the impacts of NYC's current green infrastructure policy and an alternative that prioritizes socioeconomic goalsNYC can manage more stormwater if GI siting decisions align with broader community preferences and aren't confined by sewershed boundariesMultifunctional GI siting captures more stormwater and provides more socioeconomic value than siting based on stormwater capture rates alone [ABSTRACT FROM AUTHOR]

In an era of rapid urbanization, there is a need for data-driven tools to guide long-term strategic planning. Online What If? (OWI) is a planning support system (PSS) that helps inform strategic planners about the impact of population growth and other socioeconomic factors will have on the future growth of cities. This research presents its application in metropolitan Perth with a two-part case study, demonstrating a first comprehensive application of the tool. First, OWI tests five scenarios for urban growth through the year 2050, allocating residential land use. Next, OWI alters land use allocations to align residential development with high frequency public transit, while also allocating commercial land use to support higher residential densities. Together, these data-driven scenarios inform city planners and policy makers in guiding the long-term, sustainable growth of Perth. The paper concludes with a review of OWI's strengths, weaknesses and possibilities for continual development. [ABSTRACT FROM AUTHOR]

There is an increasing availability of geospatial data describing patterns of human settlement and population such as various global remote-sensing based built-up land layers, fine-grained census-based population estimates, and publicly available cadastral and building footprint data. This development constitutes new integrative modeling opportunities to characterize the continuum of urban, peri-urban, and rural settlements and populations. However, little research has been done regarding the agreement between such data products in measuring human presence which is measured by different proxy variables (i.e. presence of built-up structures derived from different remote sensors, census-derived population counts, or cadastral land parcels). In this work, we quantitatively evaluate and cross-compare the ability of such data to model the urban continuum, using a unique, integrated validation database of cadastral and building footprint data, U.S. census data, and three different versions of the Global Human Settlement Layer (GHSL) derived from remotely sensed data. We identify advantages and shortcomings of these data types across different geographic settings in the U.S., which will inform future data users on implications of data accuracy and suitability for a given application, even in data-poor regions of the world. [ABSTRACT FROM AUTHOR]