Complex Urban Systems Research Articles

On the Edge - future adaptation challenges: The role of futurology, scenario planning methodology and off grid design in architectural and urban teaching

Abstract The article describes the role of thinking about the future and its importance in architectural and urban education. The first part deals with the scientific discipline of futurology and the possibilities of its use in architectural and urban practice. It covers topics that futurology makes available to architecture and their influence on the urbanized environment. It relates the creation of strategic visions for urban development with the UN 2030 Agenda for Sustainable Development and the UN Habitat III initiative. The second part is dedicated to introducing the futurological method of scenario planning, and its origin and use. It mentions so-called megatrends as the driving forces of future scenarios, effecting future challenges and threats that cities will have to deal with. Further, it provides insight into how this method can benefit architectural and urban work and represents the way it was used during architectural teaching. It reflects on the advantages of creating visions in the educational process. In the last part, it shows the off-grid design as a suitable simulator of structural and system thinking, leading to a better understanding of how complex architectural and urban systems function. It highlights the contribution of space architecture projects as a source of innovative thinking. It anticipates that working on space projects where self-sufficiency is a necessity can also benefit thinking about ecology, self-sufficiency, and the sustainability of settlements on Earth.

Complex Resilience and entropic Risks in Urban Megaprojects

This paper explores issues of urban resilience and risk and presents some key conceptual and analytical elements to apply the notion of entropic risk to the analysis of urban megaprojects. The paper claims that the concept of risk needs to be understood together with that of resilience, and thus the paper starts by defining both urban resilience and risk. Entropic risks are defined as the disruptive and disorderly impacts of megaprojects in urban areas. The project management literature has been concerned with risks affecting megaprojects and has neglected the many kinds of risks and negative outcomes produced by them. This is due to their modeling of megaprojects as closed systems and to their focus on providing insights to contribute to megaproject performance improvement. The purpose of the paper is to shift attention from risks affecting megaprojects to risks produced by them for a better understanding of the damage produced by megaprojects.Urban systems and megaprojects are defined as complex adaptive innovation ecosystems, or networks of people in close proximity exchanging information and opinions, creating new knowledge and interacting, in actor-networks, with matter as well as other forms of human and non-human life. Megaprojects can be characterized as complex systems (organizationally and scale-wise) embedded in complex urban, political and socio-economic systems.

Exploring spatiotemporal patterns of geosocial media data for urban functional zone identification

Urban Functional Zones (UFZs) can be identified by measuring the spatiotemporal patterns of activities that occur within them. Geosocial media data possesses abundant spatial and temporal information for activity mining. Identifying UFZs from geosocial media data aids urban planning, infrastructure, resource allocation, and transportation modernization in the complex urban system. In this work, we proposed an integrated approach by combining the spatiotemporal clustering method with a machine learning classifier. The spatiotemporal clustering method was used to mine the spatiotemporal patterns of activities, of which the distinctive features were extracted as inputs into a machine learning classifier for UFZ identification. The results show that more than 80% of the UFZs can be correctly identified by our proposed method. It reveals that this work serves as a functional groundwork for future studies, facilitating the understanding of urban systems as well as promoting sustainable urban development.

Virtuous cycles and research for a regenerative urban ecology: The case of urban wood systems in Baltimore

The field of urban ecology has progressed since the mid-1990s through four major phases: an ecology in, of, for, and with cities. This progression reflects an interest to address the complexity of urban systems with social-ecological approaches. Further, this progression signifies an interest to address societal issues by co-designing and co-producing research in collaboration with diverse stakeholders from government, non-governmental organizations (NGOs), businesses, and community associations. What remains unaddressed in this progression is a research mission orientation. While there may be a range of goals for an ecology with cities, a focus on regenerative urban ecologies is crucial. Regenerative ecologies may be seen as an endpoint along a continuum from degenerative ecologies to sustainability to regenerative ecologies. Regenerative ecologies rely upon feedback loops, similar to coral reefs and climax forests. In urban systems, these feedbacks in social-ecological systems may be considered virtuous cycles that create reinforcing, positive benefits for people and nature over time. Virtuous cycles or feedbacks are often conceived as a singular, positive feedback loop. However, virtuous cycles may be most impactful, adaptive, and resilient when they contain multiple positive and negative feedbacks and synergies. Research has several important roles in advancing virtuous cycles and regenerative urban ecologies. In this paper, we use our urban wood systems project in Baltimore as both a case study and model to illustrate an approach and lessons learned for regenerative ecologies, virtuous cycles, and the role of research. We conclude with lessons learned and consider opportunities and constraints for virtuous cycles, research, and regenerative urban ecologies in Baltimore and to other urban systems.

Restored quality of life-based approach (REQUALIFE) for urban seismic resilience assessment: Quantitative method

With rapid urbanization, today's cities are increasingly vulnerable to unpredictable and catastrophic environmental hazards such as earthquakes. A quantitative approach for seismic resilience assessment at the urban scale is still a challenging task because of the extreme complexity of urban systems. This study proposes a Restored Quality of Life-based Approach to evaluate urban seismic resilience. First, extensive literature is reviewed and analyzed to determine the mathematical definition of urban seismic resilience. Performance-based methods are selected, and urban seismic resilience is calculated by comparing desired city performance with actual city performance after an earthquake. Second, the concept of post-disaster quality of life is applied to indicate the city performance. A set of indicators is constructed preliminarily based on literature to measure the quality of life and is then validated by a Delphi survey. Finally, a framework is recommended to apply the proposed approach. The Restored Quality of Life-based Approach offers an effective tool for evaluating and improving the urban seismic resilience of a city and lays a theoretical and methodological foundation for better insights into and analysis of the urban seismic resilience in the future.

Opportunities and barriers to net-zero cities

Today, more than 700 cities worldwide have made net-zero pledges. Managing these bold targets, however, is not easy given the complexity of urban systems. Although holistic mitigation efforts are vital, individual sectors are likely to face their own challenges and require tailor-made solutions. This Voices asks: what are the challenges and opportunities in transforming cities toward net-zero carbon emissions? Today, more than 700 cities worldwide have made net-zero pledges. Managing these bold targets, however, is not easy given the complexity of urban systems. Although holistic mitigation efforts are vital, individual sectors are likely to face their own challenges and require tailor-made solutions. This Voices asks: what are the challenges and opportunities in transforming cities toward net-zero carbon emissions?

Identifying and assessing the main categories of key performance indicators for nature-based solutions project monitoring

As the number of people living in urban areas is firmly increasing, more innovative solutions are needed to tackle the accompanying effects of climate change there, such as heatwaves, stormwater concerns or pollution. As these projects are continually developed and their effects are yet to be fully tapped, there is a lack of a coherent monitoring system. This study presents a systematic and comprehensive overview of three of the most recent studies of Sari et al. (2021), Connop (2020) and Elagiry et al. (2019), which list key-performance indicators (KPIs) for nature-based solutions. These indicators are grouped into six major categories, which are further divided into sub-categories. The results of the paper highlight the importance of a general and widely implementable monitoring tool system which is scalable and localizable for different urban settings, making it possible for individual nature-based projects as well as complex urban ecological systems to be well-monitored.

Comprehensive Resilience Assessment of Complex Urban Public Spaces: A Perspective of Promoting Sustainability

Complex urban systems, such as multi-floor rail transit stations and integrated railway transport hubs, are termed “complex urban public spaces” (CUPSs). These CUPSs facilitate people’s lives, but, at the same time, are threatened by various risks due to their multi-floor structure, dense crowds, high correlation in multi-function, complex facilities, and space openness. The risk events of CUPSs could have a negative influence on public safety and further influence sustainable development. Increasing the resilience of CUPSs is an effective way to respond to risks and guarantee public safety. Therefore, it is necessary to first assess the resilience of CUPSs. In this paper, a six-level comprehensive resilience indicator system was established based on aspects of the essence of resilience. Used in combination with the methods of resilience impact score and fuzzy analytical hierarchy process, the resilience value could be calculated. The Shenzhen North Railway Station (SZ) and the Guangzhou South Railway Station (GZ) were used to validate the proposed methodology. The established resilience indicator system was shown to be comprehensive and innovative, and, regarding practicality, the proposed assessment methodology is convenient to use. This research can help policymakers to assess the resilience of CUPSs and develop relevant policies to improve the resilience of buildings, which can further enhance urban sustainability.

A novel unsupervised deep learning method for the generalization of urban form

ABSTRACT Accurate delineation of urban form is essential to understand the impacts that urbanization has on the environment and regional climate. Conventional supervised classification of urban form requires a rigidly defined scheme and high-quality sample data with class labels. Due to the complexity of urban systems, it is challenging to consistently define urban form types and collect metadata to describe them. Therefore, in this study, we propose a novel unsupervised deep learning method for urban form delineation while avoiding the limitations of conventional supervised urban form classification methods. The novelty of the proposed method is the Multiscale Residual Convolutional Autoencoder (MRCAE), which can learn the latent representation of different urban form types. These vectors can be further used to generalize urban form types by using Self-Organizing Map (SOM) and the Gaussian Mixture Model (GMM). The proposed method is applied in the metropolitan area of Guangzhou-Foshan, China. The MRCAE model along with SOM and GMM is used to generalize the urban form types from satellite images. The physical and functional properties of each urban form type are also analyzed using several auxiliary datasets, including building footprints, Points-of-Interests (POIs) and Tencent User Density (TUD) data. The results reveal that the urban form map generated based on the MRCAE can explain 55% of the building height distribution and 55% of the building area distribution, which are 2.1% and 3.3% higher than those derived from the conventional convolutional autoencoder. As the information of urban form is essential to urban climate models, the results presented in this study can become a basis to refine the quantification of urban climate parameters, thereby introducing the urban heterogeneity to help understand the climate response of future urbanization.

Improving estimation of urban land cover fractions with rigorous spatial endmember modeling

The spatial information has been widely utilized in Spectral Mixture Analysis (SMA) studies over the years. However, the spatial autocorrelation, as a prerequisite of these studies, was seldomly examined. In the complex urban systems, it remains largely unknown whether and how land cover spectra at different locations are spatially autocorrelated and to which extent spatial autocorrelation can explain the great spectral variability. This study proposed an SMA method with Spatial Endmember Modeling (SEMSMA) to improve the fraction estimation of major urban land cover types. SEMSMA used the Incremental Spatial Autocorrelation (ISA) analysis to quantify spatial autocorrelation patterns in broadband reflectance. With the patterns, SEMSMA predicted endmember signatures that incorporated both spatial (location-oriented) and non-spatial spectral variability via the Restricted Maximum Likelihood-Empirical Best Linear Unbiased Predictor (REML-EBLUP) and Monte Carlo sampling. The spectral variabilities were then addressed in pixel unmixing by an iterative mixture analysis method. Results of ISA demonstrated diverse spatial autocorrelation patterns in reflectance of urban land covers. These patterns can be related to the pathways that spatial processes acted on land cover properties. The predicted endmember signatures explained most of the spectral variability for all land cover types. Subpixel fraction estimates showed that SEMSMA outperformed multiple endmember SMA (MESMA) and spatially adaptive SMA (SASMA), based on the root mean square error (0.04–0.15), the mean absolute error (0.01–0.09), and the Systematic Error (SE) (−80.00–0.01). The low SE of SEMSMA revealed unbiased estimation of land cover fractions. Results of this study underscored the necessity of spatial autocorrelation examination and the advantage of rigorous spatial endmember modeling when incorporating spatial information into SMA.

Decision support for sustainable urban mobility: A case study of the Rhine-Ruhr area

• A framework for integrated innovation policy of sustainable urban mobility is set. • A multi-actor and multi-level approach is considered. • Transformation process is step-wise guided. • An interactive scenario-simulation tool for the decision makers is developed. • Mobility demand and supply must be balanced to transform sustainable urban future. Sustainable urban governance considers the simultaneous reduction of traffic-related pollution, social equity for mobility access, healthy market competition among the service providers, and convenient use of multi-modal transportation enabled by digital technologies. However, the rise of more complex urban systems challenges decision-making processes to design and implement environmentally sustainable, economically viable, and socially acceptable urban mobility systems. The paper sets an innovative and collaborative decision-making framework for integrated sustainable urban policy design. Firstly, schematic integration of urban flows from disintegrated operation systems toward fully integrated, inclusive, and sustainable urban systems is conceptualized. Based on this concept a multi-level decision-making process within urban mobility policies is designed relying on a Multi-Criteria Decision Aid (MCDA) for resource allocation decisions at the micro, meso, and macro levels. Thereby, a range of urban futures is adequately addressed, be it smart, sustainable city concepts, peri-urbanization, and business as usual scenarios. The integrated model for a pilot case of the metropolitan region of Rhine-Ruhr is tested in this paper. If Sustainable City scenario is the desired one, push and pull measures should be equally weighted. Based on MCDA sensitivity analysis, policy recommendations and a practical hands-on tool for urban planning are derived.

GENETIC CODE OF THE CITY

Advances in genetics as a science have led the authors to believe that its methods and approaches can be used in urban research and in justifying decisions on spatial organization and urban development. Using the theoretical and methodological tools of genetics revealed the content of the phenomenon of "genetic top" in urban planning and urban development: understood the key provisions of genetics as a science of heredity – the origin and evolution of organisms, substantiated their feasibility for research on urban history and modern cities; the peculiarities of the genetic method for the study of cities and the role of the phenomenon of heredity for their future are determined. The genetic method is presented as a kind of genetic and aimed at studying the phenomena of development not only in time but also in space, determining the transitions from lower forms of organization of territories (places, settlements) to higher – extremely complex urban systems. It covers: the establishment of initial conditions and the origin of the organism, its main stages, main trends and lines (mutations, modifications) of development. On the example of the city of Lviv the application of certain tools for in-depth understanding of the processes of origin and evolution of the city is revealed. The set of "genes" of the city – spiritual-religious, behavioral-activity and psychological-mental in their various combinations, which form the genotype of the city as connections "man–territory–space–time". It has been confirmed that the city’s genetics (genetic space) is rooted in the past, connected with people, the energy of the Earth and the Universe. "Genetic" research shows that inherited urban differences are a factor that determines urban individuality throughout development, should be taken into account in both research and spatial organization and development of urban systems. The article only initiates certain provisions to substantiate the theory of urban genetics. Future research will determine the evidence in support of the formulated provisions or refute them as false.

Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges.

With ever more people living in cities worldwide, it becomes increasingly important to understand and improve the impact of the urban habitat on livability, health behaviors, and health outcomes. However, implementing interventions that tackle the exposome in complex urban systems can be costly and have long-term, sometimes unforeseen, impacts. Hence, it is crucial to assess the health impact, cost-effectiveness, and social distributional impacts of possible urban exposome interventions (UEIs) before implementing them. Spatial agent-based modeling (ABM) can capture complex behavior-environment interactions, exposure dynamics, and social outcomes in a spatial context. This article discusses model architectures and methodological challenges for successfully modeling UEIs using spatial ABM. We review the potential and limitations of the method; model components required to capture active and passive exposure and intervention effects; human-environment interactions and their integration into the macro-level health impact assessment and social costs benefit analysis; and strategies for model calibration. Major challenges for a successful application of ABM to UEI assessment are (1) the design of realistic behavioral models that can capture different types of exposure and that respond to urban interventions, (2) the mismatch between the possible granularity of exposure estimates and the evidence for corresponding exposure-response functions, (3) the scalability issues that emerge when aiming to estimate long-term effects such as health and social impacts based on high-resolution models of human-environment interactions, (4) as well as the data- and computational complexity of calibrating the resulting agent-based model. Although challenges exist, strategies are proposed to improve the implementation of ABM in exposome research.

Earthquake and flood resilience through spatial Planning in the complex urban system

Urban Communities are exposed to different disaster risks. The paper aims at understanding the interrelation of spatial planning and the resilience of the urban communities for earthquakes and floods. Various spatial planning components were used to evaluate the community resilience to earthquake and flood in the city of Pune of Maharashtra state in India. It has been identified that spatial planning contributes to a greater extent in determining community resilience. Spatial planning results in differential resilience among communities. In the study area, economically weaker households are found to be more vulnerable to disaster risk due to their spatial locations and limited accessibility to share the resources. These factors are found to be contributing to reduced resilience in the city.

Research on urban comprehensive energy planning system based on hierarchical framework and CAS theory

The innovation of the city’s integrated energy system has become the key to China’s realization of “carbon peaks by 2030 and carbon neutrality by 2060”. At present, urban energy planning lacks the guidance and theoretical support of the planning system, and the planning practice lacks coordination with urban planning. In view of this, this article starts from the perspective of planning system and planning theory, and establishes a comprehensive urban energy planning work management system and a hierarchical structure system; Demonstrated the compatibility of CAS theory with urban systems and urban integrated energy systems; By exploring the definition of the main body of the urban complex system and the urban integrated energy complex system, the urban complex adaptive system diagram and the urban integrated energy complex adaptive system diagram are formed; Combining CAS theory and the content of the hierarchical structure system to form a comprehensive urban energy planning system. At the same time, on the basis of the above research, using various planning documents of the Lin-gang Special Area as materials to form a comprehensive district-level urban comprehensive energy planning method, realize the synergy of the urban comprehensive energy planning inside and outside, and provides new ideas for the research and actual planning of urban comprehensive energy planning.

INVERSE MODEL USING LAND AND PROPERTY SUB-SYSTEMS FOR PLANNING FUTURE CITIES: A GENERAL FRAMEWORK

This paper suggests, based on literature review, the use of the inverse model coupled with land and property systems to support urban decision-making. The inverse model is to be used for planning decisions today to achieve the desired tomorrow. This approach has been used previously in urban planning with a property system. The use of a property system alone is insufficient in dealing with the complexity of urban systems. Complex systems are made up of sub-systems that interact with each other; the integration of two sub-systems offers a first and simple alternative to address the complexity of urban systems. We suggest the use of two parametric approaches, logistic regression and house price, to model land and property sub-systems, respectively. Finally, we stress that further studies are needed to integrate the inverse model with other statistical techniques that also deal with complexity, such as cellular automata (CA) or agent-based models.

Conservation of Beirut’s Urban Heritage Values Through the Historic Urban Landscape Approach

Cities are complex urban systems with dynamic transformations in their socio-economic and environmental dimensions. Several studies have shed light on the fragility of the urban heritage and the strategies of its conservation. The historic urban landscape (HUL) approach is a new framework adopted by UNESCO to deal with urban heritage. This article aims to apply the HUL approach to the rehabilitation and management of Beirut historic neighbourhoods impacted by the massive Beirut port explosion, focusing on Armenia Street in the Mar Mikhael neighbourhood as a case study. The application of the HUL framework allows for the re-evaluation of heritage not as an individual physical form but as an urban fabric interconnected to the city, inclusive of its cultural, social, architectural, and urban layers. The article investigates the application of the four tools identified within HUL recommendations—(1) regulatory systems, (2) community engagement, (3) planning, and (4) financial tools—by proposing implementation strategies in the assessment of urban heritage to mitigate major risks. The result reveals that cooperative efforts among private and public stakeholders can play a vital role in the development of Beirut heritage, acting as catalysts for urban heritage conservation. Strategies for establishing a new legislative framework that is focused on protecting Lebanese cultural heritage and ensuring sustainable adaptation planning are highlighted.

Building-Level Urban Functional Area Identification Based on Multi-Attribute Aggregated Data from Cell Phones—A Method Combining Multidimensional Time Series with a SOM Neural Network

Portraying functional urban areas provides useful insights for understanding complex urban systems and formulating rational urban plans. Mobile phone user trajectory data are often used to infer the individual activity patterns of people and for functional area identification, but they are difficult to obtain because of personal privacy issues and have the drawback of a sparse spatial and temporal distribution. Deep learning models have been widely utilized in functional area recognition but are limited by the difficulty of acquiring training samples with large data volumes. This paper aims to achieve a fast and automatic identification of large-scale urban functional areas without prior knowledge. This paper uses Nanjing city as a test area, and a self-organizing map (SOM) neural network model based on an improved dynamic time warping (Ndim-DTW) distance is used to automatically identify the function of each building using mobile phone aggregated data containing work and residence attributes. The results show that the recognition accuracy reaches 88.7%, which is 12.4% higher than that of the K-medoids method based on the DTW distance using a single attribute and 7.8% higher than that of the K-medoids method based on the Ndim-DTW distance with multiple attributes, confirming the effectiveness of the multi-attribute mobile phone aggregated data and the SOM model based on the Ndim-DTW distance. Furthermore, at the traffic analysis zone (TAZ) level, this paper detects that Nanjing has seven functional area hotspots with a high degree of mixing. The results can provide a data basis for urban studies on, for example, the urban spatial structure, the separation of occupations and residences, and environmental suitability evaluation.

Choosing a holistic urban resilience assessment tool

Those involved in making resilience strategies and planning are struggling to understand the dynamic and complexity of urban areas and should be presented with a systematic tool, both in assessment and planning, to help them make important choices about which actions, plans, and policies to implement. Therefore, it is crucial to ensure that these methods are based on sound theory and are simple and comprehensible. Proper and accurate measurement of resilience are the steppingstones in developing effective resilience plan. Recently, there has been efforts to create tools to measure resilience in urban areas. Several tools have been created, however, there is a lack of evidence-based analysis into these assessment tools. This study is going to address this gap by finding a systemic and holistic approach to assess resilience. The aim is to determine the criteria required for assessing the resilience of the urban complex system by asking series of questions. Furthermore, existing urban resilience assessment tools evaluated to determine whether they can measure urban resilience holistically. Any method to assess resiliency in complex urban systems has to take a holistic approach. The whole urban system needs to be studied to be able to determine the overall behaviour of the system. The Auckland region was chosen to demonstrate how the study's concepts can be applied. Following consideration of specific resiliency criteria, 28 questions were developed evaluate the assessment tools. The Disaster Resilience Scorecard was chosen as the best measuring tool for the determined criteria to be ran within a city.

Evaluating the suitability of urban road networks to facilitate autonomous buses

The present paper intends to develop a method for evaluating the suitability of urban road networks to accommodate the movement of autonomous buses (ABs). The output of this process is the production of a detailed map indicating the score of each road segment in the network. To this end we follow a five-step methodological approach. The first step includes the examination of the current street classification, in order to identify functionality of the road network. The next step deals with investigating specific road network features such as slope, angle degrees in intersections, road surface width (excluding sidewalk) and existence or absence of medians in two-direction roads. After that we map the critical urban spaces or clusters in the study area and calculate their 250m isodistance zones, in order to detect clusters with high urban significance. The final step includes the process of evaluation. More specifically, the road network segments are evaluated through a simple formula, which is the suitability indicator that displays the appropriateness of the segments. The method is applied to the municipality of Kallithea which is a densely populated suburb in the southern part of Athens, therefore a favourable area for enhancing public transport. The suggested method describes a planning tool that can be utilised by policy makers and planners in order to promote sustainable mobility and the use of public transport in particular, improve travel conditions, enhance social equity and augment smartness in a long-term period. Lastly, the method can provide an adequate background for the potential integration of autonomous shuttle buses into the street classification system. This fact will facilitate their movement in the complex urban transport systems and will be a driver for shifting from conventional to smart cities.