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The needs of decision makers in China are being used to develop climate science and climate services through the Climate Science for Services Partnership. Focusing on examples of work for the energy and urban sectors, this paper outlines the approach taken and gives case studies of climate service development. We find that there is great opportunity for climate service development within the existing China Framework for Climate Services, and for enhancing the science that underpins such services. We also find challenges unique to the socio-economic and cultural environment in China, which must be taken into account when developing climate services here, as well as challenges common to all climate service development.

In recent decades, the cooling energy demand in urban areas is increasing ever faster due to the global warming and the growth of developing economies. In this perspective, the urban building energy modelling community is focusing its research activities on innovative tools and policy actions to improve cities’ sustainability. This work aims to present a novel module of the EUReCA (Energy Urban Resistance Capacitance Approach) platform for evaluating the effects of the interaction between district’s buildings in the cooling season. EUReCA predicts the urban energy demand using a bottom-up approach and low computational resources. The new module allows us to evaluate the mutual shading between buildings and the urban heat island effects, and it is well integrated with the calculation of the energy demand of buildings. The analysis was carried out considering a real case study in Padua (Italy). Results show that the urban heat island causes an average increase of 2.2 °C in the external air temperature mainly caused by the waste heat rejected from cooling systems. This involves an increase in urban cooling energy and electricity demand, which can be affected between 6 and 8%. The latter is the most affected by the urban heat island (UHI), due to the degradation it causes on the HVAC systems’ efficiency.

This paper presents a new framework for automatically creating compact building models from aerial LiDAR point clouds, where each point is known to belong to the class building. The approach addresses the issues of non-uniform point density and outlier detection to extract and refine semantic roof structures by a sequence of operations on a label map. We first partition the points into some coarse regions based on a region growing method over the Triangulated Irregular Network (TIN) model. The region label IDs are then projected to a 2D grid map, which is used to refine the roof regions and their boundaries. We design an energy optimization approach on the label map to optimize the region labels. In order to regularize the contours of roof regions extracted from the label map, we propose a new method for refining contour segment vertices, which iteratively filters the normals of contour segments and uses them to guide the update of contour vertices. The effectiveness of this method is evaluated on LiDAR point clouds from different scenes, and its performance is validated by extensive comparisons to state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Greenspaces at the city scale, like greenbelts, green-wedges or green-grids, have become well-known instruments for shaping urban economic activity and land use. The economic impacts of such instruments are complex and hard to measure. This article addresses one of the rarely studied problems of measuring the economic impacts of alternative greenspace configurations in fast growing cities. In such cities, there is an uncertain basis for making such greenspace related decisions, for example the assumptions about the cities' total population and economic activity. Decision makers have few tools to measure and predict the potential economic costs and benefits of alternative greenspace configurations. We present a new model that allows tracking over time of both non-divisible land use decisions and a multitude of gradual adaptations made by businesses and consumers. The model is applied to Greater Beijing, one of the fast growing cities that is actively exploring alternative greenspace configurations to control urban expansion. The modelling results suggest that compared with the trend-development scenario of no greenspace intervention, a strict greenbelt would decrease the overall consumer surplus in Beijing by US$3.3 billion, while an adaptive mix of green-wedges and green-grid would increase consumer surplus by US$3.6 billion per year in 2030. The adaptive configuration also reduces car journeys by 11% in Beijing. More generally, modelling results show that a flexible design of strategic greenspaces and careful siting of new development around metro stations within the designated greenspaces could benefit consumers and promote sustainable travel. [ABSTRACT FROM AUTHOR]

To model urban airflow and dispersion near buildings and in street canyons, several Gaussian diffusion models, and diagnostic urban models and methods based on computational fluid dynamics (CFD), are developed to provide a fast and adequate response when hazardous material is released. The ESTE CBRN software tool computes the urban atmospheric variables using the Reynolds-averaged Navier–Stokes equations with the k–ε closure model. The dispersion is modelled by an Eulerian model linked to the calculated flow field. The ESTE CBRN results are compared with the Joint Urban 2003 Street Canyon Experiment for the instantaneous puff releases conducted within the Urban Dispersion International Evaluation Exercise project. Urban airflow is simulated with a steady-state approach where the time-averaged velocity is evaluated from local measurements conducted outside downtown Oklahoma City, USA. Twenty anemometer measurements inside the downtown area are used to verify the CFD calculation, after which 22 individual puff releases are considered. The modelled velocity and sampler responses are in moderate agreement with the measurements. Many compared variables, such as the mean wind speed and puff arrival time, are generally well reproduced, and fulfil the urban modelling criteria. The turbulent kinetic energy is, in general, underestimated by 30–40%. The modelled time series of sampler responses fulfil many, but not all, of the urban criteria, mainly due to differences in puff trajectories and a lower dispersion intensity. Additionally, the impact of applying various three-dimensional meshes on the predicted sampler responses is tested. [ABSTRACT FROM AUTHOR]

The exterior geometry of an urban project is defined at its early stages. The interior design and architectural details are not yet defined and indicators such as the "Daylight Autonomy" (DA) or the "Useful Daylight Indicator" (UDI) cannot be used. In this article, a link is established between both these indicators and the outside light sources luminances. The concepts of "sufficient, excessive and useful luminances" are introduced. In an unobstructed context, the DA and UDI inside a typical office room in Paris are estimated on the basis of the sufficient and useful luminances of the light sources visible from the window with differences inferior to 10% up to mid-depth. Considering an urban context, the differences reach 25% at mid-depth and the DA and UDI inside the room therefore cannot be estimated on the basis of these indicators. Meanwhile, they allow identifying the directions which are the most appropriate for daylighting, and therefore allow a better consideration of this aspect at early stages of an urban project. [ABSTRACT FROM AUTHOR]

Highlights • Climate change adaptation strategies are applied to the city of Berlin. • Enhanced compactness is evaluated as a measure to create more living space. • The micro scale urban climate model MUKLIMO_3 is used for simulations. • Increasing the albedo can decrease the 2 m-temperature effectively. • At daytime enhanced vertical compactness decreases the air temperature but increases wind speed at 2 m height. Abstract This study evaluates the effectiveness of climate change adaptation strategies in Berlin, Germany, on a summer day by using the urban climate model MUKLIMO_3. White coating, green roofs and a combination of both are analysed regarding their cooling ability on the 2 m-temperature. Additionally, horizontal and vertical compactness are evaluated in terms of their respective impact on the micro climate. An enhanced albedo of the urban surfaces leads to the highest cooling ability with a significant daily average cooling of 0.2 K per 0.1 increase of albedo, while green roofs have only a small cooling effect at pedestrian level. An increased vertical compactness has a cooling ability due to the higher amount of shading, enhanced horizontal compactness shows a negative impact on the micro climate due to the raised percentage of sealed surfaces and the additional urban structures that can emit additional heat during the night. All strategies show a higher effect on the daytime and a smaller influence on the nocturnal temperature. [ABSTRACT FROM AUTHOR]

Any urban land-use system is a non-linear, complex and dynamic phenomenon. Dynamic change within a land-use system will be affected by social, cultural, economic, political and natural factors. In many developing countries, like Egypt, uncontrolled urban sprawl and land-use change (US-LUCs), has resulted in an unsustainable urbanization model. This paper employs an integrated model to monitor and analyse the cause of US-LUCs, within a metropolitan region, as a means of projecting future change that can act as a stimulus and catalyst for action. This integrated model is built by combining Markov Chain, Cellular Automata and Logistic Regression. It has been designed to address the weakness of these existing models working on their own, thereby improving the quality of spatio-temporal simulations and predictions of US-LUCs. This integrated model is applied to the monitoring, evaluation and prediction of US-LUCs in the Greater Cairo Metropolitan Region (GCMR) up to 2035. [ABSTRACT FROM AUTHOR]

This study develops an agent-based and spatial genetic algorithm framework called Population-driven Urban Land Development (PDULD) to simulate urban land development and population dynamics. In the model, household-life cycles promote their location and relocation desires and, thus, form local housing market demand. Land developers and local governments make optimal use of current land reserves to meet housing demands. Land development in an area is treated as a multi-goal optimization activity. Community cohesion theory is introduced into the model to illustrate the influence of the population on the spatial structure of urban land use. The study uses the Spatial Genetic Algorithm to help find the best land development choices to achieve social, economic, and environmental goals. The results show that the model simulates population distribution quite well and interprets the real land use at a neighborhood level with a reasonable accuracy. A historic data comparison indicates that government policies and increasing land prices have dominated the process of land development in Shanghai based on a case study of Jiading New City. [ABSTRACT FROM AUTHOR]

The future of urban modelling is viewed first against a background of its fifty-decade history. The effects of increased computing power and the availability of new data sources are explored, particularly through a wider range of scales and applications - illustrated by global scales and applications as wide-ranging as defence and security and history and archaeology. The challenges of making models fully dynamic are articulated along with a recent development which introduces uncertainty into dynamic urban models through a potential function. Finally, the potential for more effective deployment of models in city planning is shown with a system that combines data assembly, modelling and interactive planning. [ABSTRACT FROM AUTHOR]

We propose a non-equilibrium framework for modelling the evolution of cities, which describes intra-urban migration as an irreversible diffusive process. We validate this framework using the actual migration data for the Australian capital cities. With respect to the residential relocation, the population is shown to be composed of two distinct groups, exhibiting different relocation frequencies. In the context of the developed framework, these groups can be interpreted as two components of a binary fluid mixture, each with its own diffusive relaxation time. Using this approach, we obtain long-term predictions of the cities’ spatial structures, which define their equilibrium population distribution.

Continuously growing cities significantly modify the entire environment through air pollution and modification of land surface, resulting altered energy budget and land-atmosphere exchange processes over built-up areas. These effects mainly appear in cities or metropolitan areas, leading to the Urban Heat Island (UHI) phenomenon, which occurs due to the temperature difference between the built-up areas and their cooler surroundings. The Weather Research and Forecasting (WRF) mesoscale model coupled to multilayer urban canopy parameterisation is used to investigate this phenomenon for Budapest and its surroundings with actual land surface properties. In this paper the basic ideas of our research and the methodology in brief are presented. The simulation is completed for one week in summer 2015 with initial meteorological fields from Global Forecasting System (GFS) outputs, under atmospheric conditions of weak wind and clear sky for the Pannonian Basin. Then, to improve the WRF model and its settings, the calculated skin temperature is compared to the remotely sensed measurements derived from satellites Aqua and Terra, and the temporal and spatial bias values are estimated.

Dissipative structures known from non-equilibrium thermodynamics can form patterns. Cities are regarded as open, dissipative structures due to their self-organisation and thus in theory are also capable of pattern formation. In a first step to understand similarities between nonlinear pattern formation and inter-urban systems, we investigate how inter-urban structures are arranged. We use data from the Global Urban Footprint to identify spatial regularities in seven regions (Argentina, China, Egypt, France, India, Ghana and USA) and to quantitatively describe settlement patterns by number of objects and density. We find that small areas of the examined data sets show a regular arrangement, the density and number of settlements differ widely between the different regions and the portion of regular areas within this regions strongly correlates with these two parameters. The results can be used to develop mathematical models that describe inter-urban pattern formation on the one hand and to investigate to what extent the respective settlement patterns are related to infrastructural, economic or political boundary conditions on the other.

Urban transformations within large and growing metropolitan areas often generate critical dynamics affecting social interactions, transport connectivity and income flow distribution. We develop a statistical–mechanical model of urban transformations, exemplified for Greater Sydney, and derive a thermodynamic description highlighting critical regimes. We consider urban dynamics at two time scales: fast dynamics for the distribution of population and income, modelled via the maximum entropy principle, and slower dynamics evolving the urban structure under spatially distributed competition. We identify phase transitions between dispersed and polycentric phases, induced by varying the social disposition—a factor balancing the suburbs’ attractiveness—in contrast with the travel impedance. Using the Fisher information, we identify critical thresholds and quantify the thermodynamic cost of urban transformation, as the minimal work required to vary the underlying parameter. Finally, we introduce the notion of thermodynamic efficiency of urban transformation, as the ratio of the order gained during a change to the amount of required work, showing that this measure is maximized at criticality.

Small cities in developing countries are under a set of transitions that imperil their sustainability and whose repercussions can reach the international level. Therefore, local decision-makers need specific geoprospective urban models to seek alternative pathways. This paper presents a housing allocation model, designed to meet the context of small cities in developing countries. It is a multi-level Cellular Automata that relies on a new apprehension of urbanisation process, implemented through raster irregular grid with time-step variation. The model application to reconstruct housing dynamics in Kasba-Tadla city in Morocco, between 1999 and 2016, confirmed its ability to mimic well the spatio-temporal allocation of housing settlements. The obtained results showed that the spatial allocation of informal settlements is not anarchic, but driven by flexible rules, and also revealed Kasba-Tadla city could have better negotiated the after ‘Arab Spring’ urban transformations if local decision-makers had foreknowledge. [ABSTRACT FROM AUTHOR]

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias 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.)

This paper presents an integrated bottom-up approach aimed at helping those dealing with strategical analysis of installation of Building Integrated Photo Voltaic (BIPV) to estimate the electricity production potential along with the energy needs of urban buildings at the district scale. On the demand side, hourly energy profiles are generated using dynamic building simulation taking into account actual urban morphologies. On the supply side, electricity generated from the system is predicted considering both the direct and indirect components of solar radiation as well as local climate variables. Python-based Algorithm editor Grasshopper is used to interlink four types of modelling and simulation tools as 1) generation of 3-D model, 2) solar radiation analysis, 3) formatting weather files (TMY data set) and 4) dynamic energy demand. The method has been demonstrated for a cluster of 20 buildings located in the Yasar University in Izmir (Turkey), for which it is found the BIPV system could achieve an annual renewable share of 23%, in line with the Renewable Energy Directive target of 20%. Quantitatively-compared demand and supply information at hourly time step shows that only some energy needs can be met by BIPV, so there is a need for an appropriate matching strategy to better exploit the renewable energy potential. [ABSTRACT FROM AUTHOR]

The building of mathematical and computer models of cities has a long history. The core elements are models of flows (spatial interaction) and the dynamics of structural evolution. In this article, we develop a stochastic model of urban structure to formally account for uncertainty arising from less predictable events. Standard practice has been to calibrate the spatial interaction models independently and to explore the dynamics through simulation. We present two significant results that will be transformative for both elements. First, we represent the structural variables through a single potential function and develop stochastic differential equations to model the evolution. Second, we show that the parameters of the spatial interaction model can be estimated from the structure alone, independently of flow data, using the Bayesian inferential framework. The posterior distribution is doubly intractable and poses significant computational challenges that we overcome using Markov chain Monte Carlo methods. We demonstrate our methodology with a case study on the London, UK, retail system. [ABSTRACT FROM AUTHOR]

This paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection. [ABSTRACT FROM AUTHOR]

WorldView-3 satellite is providing images with an unprecedented combination of high spatial and spectral resolution. The stereo capabilities and the very high resolution of the panchromatic band (0.31 m) have been fostering new applications in urban areas, where the complexity of the morphology requires a higher level of detail. The present technical note aims to test the accuracy of digital elevation models that can be obtained by WorldView-3 stereo-pairs in these particular contexts, with an operational state-of-the-art algorithm. Validation is performed using check points and existing models of the area (from LiDAR data and oblique aerial images). The experiments, conducted over the city of Bologna (Italy) with six images, proved that roof surfaces and open spaces can be reconstructed with an average error of 1–2 pixels, but severe discrepancies frequently occur in narrow roads and urban canyons (up to several metres in average). The level of completeness achievable with only one pair is extremely variable (ranging from 50% to 90%), due to the combined effect of the geometry of acquisition and the specific urban texture. Better results can be obtained by using more than one pair. Furthermore, smaller convergence angles can be beneficial for the reconstruction of specific urban structures, such as soaring towers.

The development of Urban-Scale Energy Modelling (USEM) at the district or city level is currently the goal of many research groups due to the increased interest in evaluating the impact of energy efficiency measures in city environments. Because USEM comprises a great variety of analysis areas, the simulation programs that are able to model urban-scale energy systems actually consist of an assemblage of different particular sub-models. In order to simulate each of the sub-models in USEM, one can choose to use either existing specific simulation engines or tailor-made models. Engines or tools for simulation of urban-scale energy systems have already been overviewed in previous existing literature, however the distinction and classification of tools according to their functionalities within each analysis area in USEM has not been clearly presented. Therefore, the present work aims at reviewing the existing tools while classifying them according to their capabilities. The ultimate goal of this classification is to expose the available resources for implementing new co-simulation approaches in USEM, which may reduce the modelling effort and increase reliability as a result of using established and validated simulation engines.

Copyright of Regional Studies is the property of Routledge 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.)

Visibility modelling calculates what an observer could theoretically see in the surrounding region based on a digital model of the landscape. In some cases, it is not necessary, nor desirable, to compute the visibility of an entire region (i.e. a viewshed), but instead it is sufficient and more efficient to calculate the visibility from point to point, or from a point to a small set of points, such as computing the intervisibility of predators and prey in an agent-based simulation. This paper explores how different line-of-sight (LoS) sample ordering strategies increase the number of early target rejections, where the target is considered to be obscured from view, thereby improving the computational efficiency of the LoS algorithm. This is of particular importance in dynamic environments where the locations of the observers, targets and other surface objects are being frequently updated. Trials were conducted in three UK cities, demonstrating a robust fivefold increase in performance for two strategies (hop, divide and conquer). The paper concludes that sample ordering methods do impact overall efficiency, and that approaches which disperse samples along the LoS perform better in urban regions than incremental scan methods. The divide and conquer method minimises elevation interception queries, making it suitable when elevation models are held on disk rather than in memory, while the hopping strategy was equally fast, algorithmically simpler, with minimal overhead for visible target cases. [ABSTRACT FROM AUTHOR]

The necessary simplification of building stock models to perform energy studies in cities can impact their accuracy. This paper assesses the impact of considering different levels of detail in the characterization of the building stock, by varying the number of archetypes considered, using a neighborhood in Lisbon as case-study. Each archetype represents a share of buildings and is defined by the most representative construction parameters and average geometrical characteristics. The results show that while oversimplification might lead to large differences, there is also no need to consider a very detailed characterization of the building stock to obtained consistent results. [ABSTRACT FROM AUTHOR]

Low carbon energy supply technologies are increasingly used at the building and community scale and are an important part of the government decarbonisation strategy. However, with their present state of development and costs, many of these decentralised technologies rely on public subsidies to be financially viable. It is questionable whether they are cost effective compared to other ways of reducing carbon emissions, such as decarbonisation of conventional supply and improving the energy efficiency of dwellings. Previous studies have found it difficult to reliably estimate the future potential of decentralised supply because this depends on the available residential space which varies greatly within a city region. To address this problem, we used an integrated modelling framework that converted the residential density forecasts of a regional model into a representation of the building dimensions and land of the future housing stock. This included a method of estimating the variability of the dwellings and residential land. We present the findings of a case study of the wider south east regions of England that forecasted the impacts of energy efficiency and decentralised supply scenarios to year 2031. Our novel and innovative method substantially improves the spatial estimates of energy consumption compared to building energy models that only use standard dwelling typologies. We tested the impact of an alternative spatial planning policy on the future potential of decentralised energy supply and showed how lower density development would be more suitable for ground source heat pumps. Our findings are important because this method would help to improve the evidence base for strategies on achieving carbon budgets by taking into account how future residential space constraints would affect the suitability and uptakes of these technologies. [ABSTRACT FROM AUTHOR]

The intensification of anti-modernist ideas at the end of the XX c. encouraged a more active interest in the historic urban nucleus, the search for distinctive characteristics and modelling tools. Lithuanian urban designers have been forming their own view of cities and their modelling that is closely related to those of their Western European counterparts. The influence of Western Europe became even more significant after Lithuania regained its Independence. Consequently, in order to understand urban modelling in Lithuania one must understand Western context as well. The article discusses the most significant Lithuanian and Western European urban designers, examines their most important ideas on city modelling. Santrauka XX a. pabaiga Europos miestams itin svarbi dėl suaktyvėjusių antimodernistinių idėjų, kurios paskatino atsigręžti į miestų istorinius branduolius, miesto savitumo ir modeliavimo priemonių paieškas. Lietuvos architektai urbanistai formuoja savą požiūrį į miestus ir jų modeliavimą, kuris turi glaudžių sąlyčio taškų su Vakarų Europos atstovų mintimis. Lietuvoje Vakarų įtaka urbanistinei raidai tapo ypač reikšminga po nepriklausomybės atgavimo, todėl formuojant miestų modeliavimo sampratą mūsų šalyje svarbu suprasti ir vakarietišką kontekstą. Straipsnyje apžvelgiami ryškiausių Lietuvos ir Vakarų Europos architektų urbanistų miestų ir jų modeliavimo sampratos išskirtiniai bruožai. Reikšminiai žodžiai: miestas, miesto modeliavimas, kompozicija, architektas urbanistas.

The nowadays applied different macro models or parts ofthose, which describe the urban environment, can originate in afour-step modelling process. The paper focuses on the trip distributionprocess (the 2"d step) because of its significant calibrationrequirements. Therefore, it is possible to make the entiremodelling process more reliable (dependent upon the reliabilityof the available databases ).

To effectuate a consistent methodology for urban planning taking into consideration the viewpoints of land use and transportation, we need to approach the subject and consider complex social and economical aspects. To handle both of the above mentioned urban planning areas, we shall develop models able to pay attention to all of their restrictive factors within temporal properties.

The intensification of anti-modernist ideas at the end of the XX c. encouraged a more active interest in the historic urban nucleus, the search for distinctive characteristics and modelling tools. Lithuanian urban designers have been forming their own view of cities and their modelling that is closely related to those of their Western European counterparts. The influence of Western Europe became even more significant after Lithuania regained its Independence. Consequently, in order to understand urban modelling in Lithuania one must understand Western context as well. The article discusses the most significant Lithuanian and Western European urban designers, examines their most important ideas on city modelling. [ABSTRACT FROM AUTHOR]

While planners have long been aware that the world they act upon is complex, there is now growing interest in using concepts from the complexity sciences - such as self-organisation - to explain cities and urban change. Agent-based models (ABMs) can be invaluable tools in this quest, but they are often met with mistrust, and face some valid objections. This paper attempts to address some of the criticism, namely that ABMs offer simplistic, individualist and trivial explanations for urban processes, that they cannot be validated and that they represent the view that top-down planning is unnecessary. The paper argues that if ABMs are to be used in a new science of cities they need to be designed as part of a conversation between practitioners, policy-makers and academics. [ABSTRACT FROM AUTHOR]

Continuously growing cities significantly modify the entire environment through air pollution and modification of land surface, resulting altered energy budget and land-atmosphere exchange processes over built-up areas. These effects mainly appear in cities or metropolitan areas, leading to the Urban Heat Island (UHI) phenomenon, which occurs due to the temperature difference between the built-up areas and their cooler surroundings. The Weather Research and Forecasting (WRF) mesoscale model coupled to multilayer urban canopy parameterisation is used to investigate this phenomenon for Budapest and its surroundings with actual land surface properties. In this paper the basic ideas of our research and the methodology in brief are presented. The simulation is completed for one week in summer 2015 with initial meteorological fields from Global Forecasting System (GFS) outputs, under atmospheric conditions of weak wind and clear sky for the Pannonian Basin. Then, to improve the WRF model and its settings, the calculated skin temperature is compared to the remotely sensed measurements derived from satellites Aqua and Terra, and the temporal and spatial bias values are estimated. [ABSTRACT FROM AUTHOR]