Improving the WRF/urban modeling system in China by developing a national urban dataset

Accurate modeling of urban climate is essential to predict potential environmental risks in cities.Urban datasets,such as urban land use and urban canopy parameters(UCPs),are key input data for urban climate models and largely affect their performance.However,access to reliable urban datasets is a challenge,especially in fast urbanizing countries.In this study,we developed a high-resolution national urban dataset in China(NUDC)for the WRF/urban modeling system and evaluated its effect on urban climate modeling.Specifically,an optimization method based on building morphology was proposed to classify urban land use types.The key UCPs,including building height and width,street width,surface imperviousness,and anthropogenic heat flux,were calculated for both single-layer Urban Canopy Model(UCM)and multiple-layer Building Energy Parameterization(BEP).The results show that the derived morphological-based urban land use classification could better reflect the urban characteristics,compared to the socioeconomic-function-based classification.The UCPs varied largely in spatial within and across the cities.The integration of the developed urban land use and UCPs datasets significantly improved the representation of urban canopy characteristics,contributing to a more accurate modeling of near-surface air temperature,humidity,and wind in urban areas.The UCM performed better in the modeling of air temperature and humidity,while the BEP performed better in the modeling of wind speed.The newly developed NUDC can advance the study of urban climate and improve the prediction of potential urban environmental risks in China.

Modeling urban land use dynamics using Markov-chain and cellular automata in Gondar City,Northwest Ethiopia

Modeling urban land-use dynamics is critical for urban experts’and infrastructure managers’planning.This study attempts to explore the land-use/land-cover(LULC)dynamics of Gondar using satellite images from 1984 to 2020.Markov-Chain and Cellular Automata(MC-CA)models have been recognized as performing well in predicting urban land-use change.However,only a few models work in Ethiopia in general,and no study in Gondar has applied this approach to study urban land-use patterns.Therefore,Gondar land-use/land cover changes of Gondar were predicted using the MC-CA model in IDRISI.The built-up area in Gondar city covered 1413 ha(3%of the total area)in 1984 and increased to 2380 ha(5%)in 1994;21153 ha(45.5%)in 2004;22622 ha(48.7%)in 2014;and 23427 ha(50.5%)in 2020.The area has been predicted to reach 57.5%in the 2050s,showing a faster increase that will cause a very vast loss of farmland.This will increase urban sprawl challenges as well as overall environmental disequilibrium in the preceding decade.Thus,innovative and careful structures and systems in urban planning are required to secure a sustainable urban future and to make our cities livable and competitive in the paradigm of sustainable cities.

基于DRIVE-Urban模型的长沙市区暴雨内涝灾害研究

以城市内涝模型DRIVE-Urban为基础,对长沙市区内的两次典型内涝事件进了街道尺度(10 m分辨率)和6个不同重现期(5年、10年、20年、30年、50年和100年)下的模拟,并根据模拟结果确定了内涝风险等级和风险区划。结果显示DRIVE-Urban模型能够很好地反映市区内街道积水的淹没情况,两次内涝点命中率(POD)分别达到了64%和67%,且随着重现期增大,积水面积也逐渐增大,积水面积最高占比甚至达到了市区总面积的8.2%,约96.51 km~2。内涝的风险等级分为低风险、中风险、较高风险和高风险。高风险和较高风险区域主要集中在岳麓区东部、天心区北部、芙蓉区、开福区南部、雨花区北部以及高新区南部,而高新区北部、岳麓区西部和雨花区南部风险等级较低。

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

Development of an Accurate Urban Modeling System Using CAD/GIS Data for Atmosphere Environmental Simulation

This paper presents an urban modeling system using CAD/GIS data for atmosphere environmental simulation, such as wind flow and contaminant spread in urban area. The CAD data is used for the shape modeling for the high-storied buildings and civil structures with complicated shape since the data for that is not included in the 3D-GIS data accurately. The unstructured mesh based on the tetrahedron element is employed in order to express the urban structures with complicated shape accurately. It is difficult to understand the quality of shape model and mesh by the conventional visualization technique. In this paper, the stereoscopic visualization using virtual reality (VR) technology is employed for the verification of the quality of shape model and mesh. The present system is applied to the atmosphere environmental simulation in urban area and is shown to be an useful planning and design tool to investigate the atmosphere environmental problem.

A review of computer graphics approaches to urban modeling from a machine learning perspective

Urban modeling facilitates the generation of virtual environments for various scenarios about cities.It requires expertise and consideration,and therefore consumes massive time and computation resources.Nevertheless,related tasks sometimes result in dissatisfaction or even failure.These challenges have received significant attention from researchers in the area of computer graphics.Meanwhile,the burgeoning development of artificial intelligence motivates people to exploit machine learning,and hence improves the conventional solutions.In this paper,we present a review of approaches to urban modeling in computer graphics using machine learning in the literature published between 2010 and 2019.This serves as an overview of the current state of research on urban modeling from a machine learning perspective.

A Retrospect and Prospect of Urban Models: Reflections after Interviewing Michael Batty

Based on an interview with Prof. Michael Batty, a leading scholar in urban modeling, this paper reviews the history of urban models, comments on their present developments and pictures their prospects. The first section briefly overviews the family tree of urban models and then looks further into the causes for their failure in planning application in the first upsurge of related research in the 1960 s and 1970 s. The second section summarizes the current development of urban models, which can be counted as the second upsurge of related research. It is estimated that more research attention will be paid to building dynamic, disaggregate, micro and problem-oriented models, with a combination of top-down and bottomup modeling methods. This can be more capable of tackling the growing urban complexity and uncertainty. Meanwhile, the "big data era" also poses more opportunities for the development of urban models. The last section introduces three new trends in the theoretical, educational and research development of urban models, which compose the idea of "new science of cities" from Michael Batty, the start-up of quantitative urban research education and the establishment of Beijing City Lab.

Joint shape and color descriptors for 3D urban model retrieval

With the rapid development of photogrammetry,computer vision and three-dimensional(3D)modeling technologies,it is possible to efficiently construct detailed 3D urban models.Accordingly,large corpora of 3D models,such as the Google 3D Warehouse,are now becoming freely available on the web.How to find the proper 3D urban models is a challenging research issue.In this paper,we join shape descriptors and color descriptors for 3D urban model retrieval.The query objects are localized and segmented automatically from the input images by using a new selective search voting algorithm.Through combining the normalization with the light field descriptor,the Horizontal Light Descriptor is introduced to measure the shape similarity among the normalized urban models.The color descriptors are used to represent the color information of the urban models.The two types of descriptors are joined to search 3D urban models similar to the query objects.Experimental results have shown the effectiveness of our approach.

Urban Growth Prediction: A Review of Computational Models and Human Perceptions

Human population continues to aggregate in urban centers. This inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have been extensively studied with the overarching goal to assist in sustainable management of urban centers. Despite the extensive body of research, these models are not frequently included in the decision making process. This review aims on bringing this gap by analyzing results from a survey investigating developer and user perceptions from the modeling and planning communities, respectively. An overview of existing models, including advantages and limitations, is also provided. A total of 156 manuscripts is identified. Analysis of aggregated statistics indicates that cellular automata are the prevailing modeling technique, present in the majority of published works. There is also a strong preference for local or regional studies, a choice possibly related to data availability. The survey found a strong recognition of the models’ potential in decision making, but also limited agreement that these models actually reach that potential in practice. Collaboration between planning and modeling communities is deemed essential for transitioning models into practice. Data availability is considered a stronger restraining factor by respondents with limited algorithmic experience, which may indicate that model input data are becoming more specialized, thus significantly limiting wide-spread applicability. This review assesses developer and user perceptions and critically discusses existing urban growth prediction models, acting as a reference for future model development. Specific guidelines are provided to facilitate transition of this relatively mature science into decision making

The Multi-Scale Numerical Modeling System for Research on the Relationship between Urban Planning and Meteorological Environment

Considering the urban characteristics, a customized multi-scale numerical modeling system is established to simulate the urban meteorological environment. The system mainly involves three spatial scales: the urban scale, urban sub-domain scale, and single to few buildings scale. In it, different underlying surface types are employed, the building drag factor is used to replace its roughness in the influence on the urban wind field, the effects of building distribution, azimuth and screening of shortwave radiation are added, and the influence of anthropogenic heating is also taken into account. All the numerical tests indicate that the simulated results are reasonably in agreement with the observational data, so the system can be used to simulate the urban meteorological environment. Making use of it, the characteristics of the meteorological environment from the urban to urban sub-domain scales, even the among-buildings scale, can be recognized. As long as the urban planning scheme is given, the corresponding simulated results can be obtained so as to meet the need of optimizing urban planning.

Modelling of Nature-Based Solutions (NBS) for Urban Water Management—Investment and Outscaling Implications at Basin and Regional Levels

This manuscript is an attempt to demonstrate effectiveness of nature-based solutions (NBS) and measures to reduce risk of flooding and environmental impact in urban settings. The nature-based solutions (NBS) were assessed as scenarios from experience of urban storm drainage and sewerage systems based on practices that improve urban water management through modelling using urban stormwater management model (SWMM). The model has been applied in a typical urban environment in the second city in Botswana, the City of Francistown, which has a population of more than one hundred thousand. By considering the 2-yr and 10-year storm events in a calibrated SWMM, NBS scenarios from a mix of low impact and drainage measures were considered. The considered NBS scenarios were used to determine their effectiveness in terms of reducing and controlling peak runoff, flood volumes, infiltration and evapotranspiration in the study area, which are vital in assessing the opportunity and challenge for sustainable management of water resources and associated tradeoff of investments in the urban contexts. The study demonstrates the usefulness of implementing effective measures for achieving NBS in urban context and possibility of outscaling at basin and regional levels.

How Unique is ′China Model′: A Review of Theoretical Perspectives on China′s Urbanization in Anglophone Literature

As a major aspect of the ′China Model′, urbanization in China is being heatedly discussed in the Anglophone literature in the last two decades. By considering China′s urbanization as a ′testing ground′ of ′western′ theories, these studies are important for the understanding of China′s ongoing urban restructuring and exchanging knowledge with ′western′ insights. Based on a survey of existing studies, this paper identifies various endogenous and exogenous concepts and explanations of China′s urbanization. It is suggested that China′s urbanization is mainly driven by a combination of political decentralization and neoliberalization with various forms of social stratification and mobility. However, it is argued that the distinctness of the ′China Model′, which is usually used to support the legitimacy of studies of China′s urbanization, has led to many controversial arguments and diminished the due contributions of Chinese scholars in the knowledge production of China′s urbanization. To consolidate the legitimacy of studies on China′s urbanization and enhance the roles of Chinese scholars, we suggest future studies to pay more attentions to the fundamental theories with looser constraints and ′true questions′ on China′s urbanization.

A Microscale Model for Air Pollutant Dispersion Simulation in Urban Areas： Presentation of the Model and Performance over a Single Building

A microscale air pollutant dispersion model system is developed for emergency response purposes. The model includes a diagnostic wind field model to simulate the wind field and a random-walk air pollutant dispersion model to simulate the pollutant concentration through consideration of the influence of urban buildings. Numerical experiments are designed to evaluate the model＇s performance, using CEDVAL （Compilation of Experimental Data for Validation of Microscale Disper- sion Models） wind tunnel experiment data, including wind fields and air pollutant dispersion around a single building. The results show that the wind model can reproduce the vortexes triggered by urban buildings and the dispersion model simulates the pollutant concentration around buildings well. Typically, the simulation errors come from the determination of the key zones around a building or building cluster. This model has the potential for multiple applications; for example, the prediction of air pollutant dispersion and the evaluation of environmental impacts in emergency situations; urban planning scenarios; and the assessment of microscale air quality in urban areas.

A Spatially Heterogeneous Expert Based (SHEB) Urban Growth Model using Model Regionalization

Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban growth models. Instead of applying a single method to the entire study area, we segment the study area into different regions and apply targeted algorithms in each subregion. The working hypothesis is that the integration of appropriately selected region-specific models will outperform a globally applied model as it will incorporate further spatial heterogeneity. We examine urban land use changes in Denver, Colorado. Two land use maps from different time snapshots (1977 and 1997) are used to detect the urban land use changes, and 23 explanatory factors are produced to model urbanization. The proposed Spatially Heterogeneous Expert Based (SHEB) model tested decision trees as the underlying modeling algorithm, applying them in different subregions. In this paper the segmentation tested is the division of the entire area into interior and exterior urban areas. Interior urban areas are those situated within dense urbanized structures, while exterior urban areas are outside of these structures. Obtained results on this model regionalization technique indicate that targeted local models produce improved results in terms of Kappa, accuracy percentage and multi-scale performance. The model superiority is also confirmed by model pairwise comparisons using t-tests. The segmentation criterion of interior/exterior selection may not only capture specific characteristics on spatial and morphological properties, but also socioeconomic factors which may implicitly be present in these spatial representations. The usage of interior and exterior subregions in the present study acts as a proof of concept. Other spatial heterogeneity indicators, for example landscape, socioeconomic and political boundaries could act as the basis for improved local segmentations.

An interactive simulation model of urban ecosystem and its implementation

An interactive simulation model is established based on the methodology of 'sensitivity model' (SM) during the cooperative research process between the founders of SM and the authors. And the conceptual framework of SM is developed into the interactively qualitative and quantitative simulation model presented in this paper, which makes it possible to break down a complex urban ecosystem into simple and visual quantitative or qualitative relationships between the factors. By studying the dynamic responses of the system to the changes of the inputs and parameters of the model, future trends in urban development can be predicted and strategies formulated. The whole process is realized on micro-computer in the course of man-computer interaction. Its potential use is shown in a case of Tianjin City.

SCENARIOS SIMULATION OF COUPLING SYSTEM BETWEEN URBANIZATION AND ECO-ENVIRONMENT IN JIANGSU PROVINCE BASED ON SYSTEM DYNAMICS MODEL

By means of ISM (Interpretative Structural Modeling) and SD (System Dynamics) methods, this paper made a system dynamics model of urbanization and eco-environment coupling in Jiangsu Province according to the implication and PSR (Pressure State Response) framework of urbanization and eco-environment coupling. Moreover, five typical scenarios during 2000-2015 have been simulated and analyzed based on the time serial statistical data during 1990-2003 in Jiangsu, which indicates: firstly, there are significant differences between the results and the scenarios, and the five coupling models all have comparative advantages and drawbacks; secondly, in terms of the characteristics and regional development disparities of Jiangsu and the general rule of world urbanization process, this paper reveals that only when either population urbanization model or social urbanization model to be correspondingly adopted, the sustainable development among population, economy, urbanization and eco-environment can be realized.

Unified Data Model of Urban Air Pollution Dispersion and 3D Spatial City Model:Groundwork Assessment towards Sustainable Urban Development for Malaysia

Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution is one of the indicators headed towards it. At present monitoring and managing air pollution in urban areas encompasses sophisticated air quality modeling and data acquisition. However, rapid developments in major cities cause difficulties in acquiring the city geometries. The existing method in acquiring city geometries data via ground or space measurement inspection such as field survey, photogrammetry, laser scanning, remote sensing or using architectural plans appears not to be practical because of its cost and efforts. Moreover, air monitoring stations deployed are intended for regional to global scale model whereby it is not accurate for urban areas with typical resolution of less than 2 km. Furthermore in urban areas, the pollutant dispersion movements are trapped between buildings initiating it to move vertically causing visualization complications which imply the limitations of existing visualization scheme that is based on two-dimensional (2D) framework. Therefore this paper aims is to perform groundwork assessment and discuss on the current scenario in Malaysia in the aspect of current policies towards SUD, air quality monitoring stations, scale model and detail discussion on air pollution dispersion model used called the Operational Street Pollution Model (OSPM). This research proposed the implementation of three-dimensional (3D) spatial city model as a new physical data input for OSPM. The five Level of Details (LOD) of 3D spatial city model shows the scale applicability for the dispersion model implementtation. Subsequently 3D spatial city model data commonly available on the web, by having a unified data model shows the advantages in easy data acquisition, 3D visualization of air pollution dispersion and improves visual analysis of air quality monitoring in urban areas.

Influences of Limited Ammonium Nitrogen and Water Temperature on the Urban Stream Restoration Using Bacterial Technology – View from the Perspective of Numerical Modelling

To complete the previously information issued on the feasibility study and some technical challenges identi-fied from the application of bacterial technology, this study presents another characteristics of numerical output as the bacterial growth is now also limited to ammonium nitrogen and water temperature. Based on the results obtained, it is found that the degradation of readily biodegradable COD will be much slower be-cause of lower bacterial growth. At certain period, the COD concentration will increase and be plotted higher later on compared to the model which is limited only to substrate and oxygen. Besides the ammonium nitro-gen, other parameters i.e. particulate products from COD decay and particulate degradable organic nitrogen will also increase soon after certain time. Considering the increase of ammonium nitrogen as it is also con-verted to nitrate nitrogen, it can be predicted that some algae may show up during the treatment processes. When the model is simulated under different water temperature, slower biodegradation process is presented at lower water temperature. Because the bacteria grow better at higher water temperature, more oxygen is then required. Finally, from this study, it is also identified that the artificial mixing and addition of oxygen at initial stage of treatment will considerably influence the restoration.

A Framework of Environmental Modelling and Information Sharing for Urban Air Pollution Control and Management

More effective environmental pollution control and management are needed due to the increasing environ-mental impacts from a range of human activities and the growing public demands for a better living environment. Urban air pollution is a serious environmental issue that poses adverse impacts on the health of people and the environment in most metropolitan areas. In this paper,we propose a geoinformatics augmented framework of environmental modelling and information sharing for supporting effective urban air pollution control and management. This framework is out-lined in terms of its key components and processes including: 1) an integrated,adaptive network of sensors for envi-ronmental monitoring; 2) a set of distributed,interoperable databases for data management; 3) a set of intelligent,robust algorithms and models for environmental modelling; 4) a set of flexible,efficient user interfaces for data access and in-formation sharing; and 5) a reliable,high capacity,high performance computing and communication infrastructure for integrating and supporting other framework components and processes.

Urban Metabolism Based on Emergy and Slack Based Model: A Case Study of Beijing, China

The key to studying urban sustainable development depends on quantifying stores, efficiencies of urban metabolisms and capturing urban metabolisms′ mechanisms. This paper builds up the metabolic emergy account and quantifies some important concepts of emergy stores. Emphasis is placed on the urban metabolic model based on the slack based model(SBM) method to measure urban metabolic efficiencies. Urban metabolic mechanisms are discussed by using the regression method. By integrating these models, this paper analyzes the urban metabolic development in Beijing from 2001 to 2010. We conclude that the metabolic emergy stores of Beijing increased significantly from 2001 to 2010, with the emergy imported accounting for most of the increase. The metabolic efficiencies in Beijing have improved since the 2008 Olympic Games. The population, economic growth, industrial structures, and environmental governance positively affect the overall urban metabolism, while the land expansion, urbanization and environmentally technical levels hinder the improving of urban metabolic efficiencies. The SBM metabolic method and the regression model based on the emergy analysis provide insights into the urban metabolic efficiencies and the mechanism. They can promote to integrate such concepts into their sustainability analyses and policy decisions.