Urban Domain Research Articles

Bracing urban governance against climate crises: How to integrate high reliability into strategic decision‐making?

AbstractTurning cities socio‐ecologically resilient is one of the pressing challenges in the face of ongoing climate change and accompanying extreme weather events. Despite concentrated efforts within specific urban domains, there exists a necessity for a coordinating mechanism that can concurrently monitor signals of slowly maturing long‐term crises, such as global warming and swiftly intervene to mitigate urgent threats, such as catastrophic floods. This article explores the potential of high reliability principles to inform such a governance mechanism through a novel policy operations room (POR) framework, conceptualizing urban strategic goals as critical infrastructure. We analyze the conditions for integrating elements from top‐down crisis management with bottom‐up participatory scenario exercises and policy simulations in urban governance. Based on pre‐ and post‐POR interviews and meeting transcripts in three Finnish cities we examine the regulative, normative, and cognitive aspects of integration. The analysis indicates that the implementation of a high reliability framework in urban settings can provide valuable support for addressing challenges induced by climate change.

Implementation of a Temperature Monitoring and Measurement Network in the Urban Context: A Case Study of Kasba Tadla, Morocco, 2022.

Abstract In the context of climate change, this study focuses on the impact of heatwaves, which have become the dominant meteorological phenomenon in terms of duration and intensity. The objective is to understand the temporal variation of temperatures in the urban domain, highlighting thermal differences on an hourly scale. The city of Kasba Tadla, located in the Tadla plain in Morocco, is at the core of this research. This rapidly expanding urban area is traversed by the Oum Er-rbia River. The selection of this region allows for a specific analysis of the climate challenges a rapidly growing city may face. The methodology relies on a network of four fixed meteorological stations installed in the city of Kasba Tadla. Temperature measurements were taken on an hourly timescale during the summer of 2022. This approach enables a detailed analysis of temperature variation based on building density and the presence of vegetation in different neighborhoods. The results highlight a significant temperature variation within the city, emphasizing the impact of building density and vegetation on this phenomenon.

Unveiling urbanization effects on trees outside forests along the urban-rural gradient in megacity Bengaluru

Rapid urbanization has caused significant changes along the urban-rural gradient, leading to a variety of landscapes that are mainly shaped by human activities. This dynamic interplay also influences the distribution and characteristics of trees outside forests (TOF). Understanding the pattern of these trees will support informed decision-making in urban planning, in conservation strategies, and altogether in sustainable land management practices in the urban context. In this study, we employed a deep learning-based object detection model and high resolution satellite imagery to identify 1.3 million trees with bounding boxes within a 250 ​km2 research transect spanning the urban-rural gradient of Bengaluru, a megacity in Southern India. Additionally, we developed an allometric equation to estimate diameter at breast height (DBH) from the tree crown diameter (CD) derived from the detected bounding boxes. Our study focused on analyzing variations in tree density and tree size along this gradient. The findings revealed distinct patterns: the urban domain displayed larger tree crown diameters (mean: 8.87 ​m) and DBH (mean: 43.78 ​cm) but having relatively low tree density (32 trees per hectare). Furthermore, with increasing distance from the city center, tree density increased, while the mean tree crown diameter and mean tree basal area decreased, showing clear differences of tree density and size between the urban and rural domains in Bengaluru. This study offers an efficient methodology that helps generating instructive insights into the dynamics of TOF along the urban-rural gradient. This may inform urban planning and management strategies for enhancing green infrastructure and biodiversity conservation in rapidly urbanizing cities like Bengaluru.

Saigon as a landscape palimpsest: the hybrid identity of Saigon’s urban area in the opening period through Tran Anh Hung’s Cyclo (1995)

The film Cyclo (1995), by diasporic Vietnamese director Tran Anh Hung, positions Saigon city as an endless overwriting and creation of cultural, political, and cultural currents – what I call a landscape palimpsest. In the movie, ‘Saigon’ is a site of clashing post-war traumas, modern lifestyles driven by consumerism, traditional identities, and globalisation. The superimposition of landscapes creates the city’s hybrid identity, revealing a complex and multi-faceted urban domain. Aesthetically, Cyclo also overlays the feel of ‘romantic cinema’ and the raw, documentary aesthetic of ‘everyday cinema’. Therefore, the film opens the door for the presence of contemporary, independent, everyday cinematic aesthetics. Cyclo is an intersection that can connect the cinematic and historical events of the city.

Harmonizing Urban Futures: Integrating Smart and Sustainable City Principles

In an era marked by rapid urbanization and evolving urban challenges, understanding the intricate relationship between sustainable and smart city principles is paramount for shaping resilient and future- ready cities. This study delves into the integration of sustainable and smart city principles, aiming to illuminate their interconnectedness in contemporary urban contexts. By analyzing the latest academic understanding of this integration, the research contributes to the development of comprehensive frameworks guiding urban development strategies. Through bibliometric analysis using VOSviewer, key factors such as air quality, intelligent transportation systems, internet connectivity, urban growth, solar energy, and learning processes emerge as central to understanding the interplay between smart and sustainable cities. This analysis informs efforts towards integrated urban development and resilience. The study hypothesizes that smart city principles build upon sustainable city foundations, as evidenced by interrelated indicators across urban domains. Recognizing the significance of this integration, urban planners and policymakers can craft strategies that prioritize sustainability, innovation, and inclusivity, thus shaping resilient and future-ready cities. By elucidating the symbiotic relationship between smart and sustainable city concepts, this research offers insights crucial for addressing contemporary urban challenges and fostering sustainable urban development globally.

Understanding urban green spaces through lenses of sensory experience: a case study of neighborhood parks in Dhaka city

ABSTRACT Physical, psychological, and emotional stress are common in today’s Dhaka city, which can be intense or sensory excruciating. Urban green space is considered a healthy environment for mental repair and well-being in urban domains. The senses (vision, touch, sound, smell, and taste) are essential in interpreting and experiencing the place and city. Therefore, the sensory experience is a multimodal awareness of environment that can impact users’ health, pleasure, and emotions. This paper aims to methodically explore the intricate sensory fabric and spatial components responsible for users’ sensory experiences that are necessary for planning and designing healthier neighborhood parks. This paper outlines the methods and findings of the study conducted in two parks in Dhaka city’s distinct neighborhoods at different times of the day and week to record users’ activity patterns and sensory experiences. Justice Shahabuddin Park in Gulshan and Tajmahal Road Park, Mohammadpur, were chosen as the study locations to be investigated. The analysis comprised a combination of qualitative and quantitative methodologies, such as ethnographic research and on-site observation, geographical mapping, surveys, and walk-along interviews to capture subjective and objective sensory data and daily rhythms of neighborhood park users. The results suggest that all senses are essential in building healthy, inclusive urban green spaces.

Integrating Underground Space into the Groundscape Resilience Concept

Underground space has always been used as a resilient solution in addressing the need for safety in terms of climate conditions and defense purposes. This research seeks to recognize the potential of the underground space in the city as a significant urban resilience strategy, with the aim of revealing how contemporary underground architecture is integrated with the public spaces on the surface and how this groundscape integration contributes to the quality of the use of the public spaces to achieve urban resilience. Public spaces have a crucial role in the environmental, social, and sustainable context of the city and are considered urban domains for spatial urban intervention that contribute to urban resilience in its broader understanding. Based on the review of underground space research and the comparative analysis of selected contemporary design projects, the research explores the integration of underground space in correlation with its utilization model based on contemporary design projects. The research results in the systematization of underground utilization among underground infrastructure, underground living settlements, and urban development to offer insights into the enhancement of resilience planning through the contemporary multifunctional usage of underground space. The contribution of this research is reflected in the methodology of developing the criteria for a groundscape resilience concept, in terms of perceiving underground space as an integral urban layer, its multifunctional utilization, and in terms of achieving urban resilience.

When AIs become oracles: generative artificial intelligence, anticipatory urban governance, and the future of cities

Abstract Generative Artificial Intelligence (AI) is boosting anticipatory forms of governance, through which state actors seek to predict the future and strategically intervene in the present. In this context, city brains represent an emerging type of generative AI currently employed in urban governance and public policy in a growing number of cities. City brains are large-scale AIs residing in vast digital urban platforms, which manage multiple urban domains including transport, safety, health, and environmental monitoring. They use Large Language Models (LLMs) to generate visions of urban futures: visions that are in turn used by policymakers to generate new urban policies. In this paper, we advance a twofold contribution. Theoretically, we develop a critical theory of anticipatory governance in the age of generative AI. More specifically, we focus on technocratic approaches to anticipatory governance, to explain how the act of governing extends into the future by means of predictive AI technology. Our approach is critical in order to expose the dangers that the use of AI (generative AI, in particular) in urban governance poses, and to identify their causes. These dangers include the formation of a policy process that, under the influence of unintelligible LLMs, risks losing transparency and thus accountability, and the marginalization of human stakeholders (citizens, in particular) as the role of AI in the management of cities keeps growing and governance begins to turn posthuman. Empirically, we critically examine an existing city brain project under development in China and ground our critical theory in a real-life example.

Simulation and evaluation of ecosystem service value along the Yellow River in Henan Province, China

The unprecedented growth in population and swift industrial advancements exert considerable strains on the ecosystem, particularly within medium-sized and large urban landscapes. The critical investigation into the intricate links between current and prospective land utilization, as well as the ecosystem service value (ESV), holds considerable empirical relevance for the calibration of land usage frameworks, thereby contributing to the sustainable evolution of extensive urban zones. Utilizing GlobeLand 30 data, the present research probes into the pattern of land transformation and the spatial-temporal dispersal of ESV in Henan’s Yellow River vicinity over a span from 2000 to 2020. For the enhancement of land usage alignment, a Markov-PLUS fusion model was devised to gauge three disparate ESV transition scenarios slated for 2030, namely, natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). The principal determinants of land transformation within the 2000–2020 period were recognized as elevation, populace concentration, and atmospheric temperature. Amid the rapid accretion of construction land engulfing substantial cropland and grassland areas, there was an ESV diminution to the tune of 1.432 billion RMB between 2000 and 2020. The ESV’s high-value regions were discerned within relatively undisturbed ecosystem zones, with the lower-value sections identified in cropland and constructed areas, where human interventions exerted pronounced effects on the ecosystem. In accordance with the 2030 land usage simulations and analyses, in contrast to alternative scenarios, the EPS exhibited the least fluctuation in land type alterations in 2030, demonstrated the most pronounced escalation in cold spot concentration, and reached a peak agglomeration level. This underscores that the EPS not only offers a refinement in land utilization configuration but also mediates the equilibrium between economic and ecological considerations. The insights derived from this investigation afford innovative evaluative methods for spatial planning, ecological recompense, and sustainable land exploitation within large- and medium-scale urban domains.

Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions

Abstract. Atmospheric transport inversions are a powerful tool for independently estimating surface CO2 fluxes from atmospheric CO2 concentration measurements. However, additional tracers are needed to separate the fossil fuel CO2 (ffCO2) emissions from non-fossil CO2 fluxes. In this study, we focus on radiocarbon (14C), the most direct tracer of ffCO2, and the continuously measured surrogate tracer carbon monoxide (CO), which is co-emitted with ffCO2 during incomplete combustion. In the companion paper by Maier et al. (2024), we determined discrete 14C-based and continuous ΔCO-based estimates of the ffCO2 excess concentration (ΔffCO2) compared with a clean-air reference for the urban Heidelberg observation site in southwestern Germany. The ΔCO-based ΔffCO2 concentration was calculated by dividing the continuously measured ΔCO excess concentration by an average 14C-basedΔCO/ΔffCO2 ratio. Here, we use the CarboScope inversion framework adapted for the urban domain around Heidelberg to assess the potential of both types of ΔffCO2 observations to investigate ffCO2 emissions and their seasonal cycle. We find that, although they are more precise, 14C-based ΔffCO2 observations from almost 100 afternoon flask samples collected in the 2 years of 2019 and 2020 are not well suited for estimating robust ffCO2 emissions in the main footprint of this urban area, which has a very heterogeneous distribution of sources including several point sources. The benefit of the continuous ΔCO-based ΔffCO2 estimates is that they can be averaged to reduce the impact of individual hours with an inadequate model performance. We show that the weekly averaged ΔCO-based ΔffCO2 observations allow for a robust reconstruction of the seasonal cycle of the area source ffCO2 emissions from temporally flat a priori emissions. In particular, the distinct COVID-19 signal – with a steep drop in emissions in spring 2020 – is clearly present in these data-driven a posteriori results. Moreover, our top-down results show a shift in the seasonality of the area source ffCO2 emissions around Heidelberg in 2019 compared with the bottom-up estimates from the Netherlands Organization for Applied Scientific Research (TNO). This highlights the huge potential of ΔCO-based ΔffCO2 to validate bottom-up ffCO2 emissions at urban stations if the ΔCO/ΔffCO2 ratios can be determined without biases.

A Review of IoT-Based Smart City Development and Management

Smart city initiatives aim to enhance urban domains such as healthcare, transportation, energy, education, environment, and logistics by leveraging advanced information and communication technologies, particularly the Internet of Things (IoT). While IoT integration offers significant benefits, it also introduces unique challenges. This paper provides a comprehensive review of IoT-based management in smart cities. It includes a discussion of a generalized architecture for IoT in smart cities, evaluates various metrics to assess the success of smart city projects, explores standards pertinent to these initiatives, and delves into the challenges encountered in implementing smart cities. Furthermore, the paper examines real-world applications of IoT in urban management, highlighting their advantages, practical impacts, and associated challenges. The research methodology involves addressing six key questions to explore IoT architecture, impacts on efficiency and sustainability, insights from global examples, critical standards, success metrics, and major deployment challenges. These findings offer valuable guidance for practitioners and policymakers in developing effective and sustainable smart city initiatives. The study significantly contributes to academia by enhancing knowledge, offering practical insights, and highlighting the importance of interdisciplinary research for urban innovation and sustainability, guiding future initiatives towards more effective smart city solutions.

Navigating urban complexity: The transformative role of digital twins in smart city development

This research systematically explores the burgeoning field of Digital Twins (DTs) within smart cities’ framework and urban development. Anchored by three research questions, the study delineates the theoretical underpinnings and practical implications of DTs at a city scale. It delves into the structure, operational dynamics, and diverse applications in various urban domains supported by case studies. Through a structured methodology employing the PRISMA framework, it includes an analysis of 64 pertinent studies from an initial pool of 519. The research synthesis highlights the dynamic nature of DTs, their multifaceted technological layers, and their instrumental role in shaping sustainable urban futures. Despite the promising outlook, the study also highlights several technological and real-world hurdles that need to be addressed to fully unlock the capabilities of DTs within urban environments.

The State of the Art in Visual Analytics for 3D Urban Data

AbstractUrbanization has amplified the importance of three‐dimensional structures in urban environments for a wide range of phenomena that are of significant interest to diverse stakeholders. With the growing availability of 3D urban data, numerous studies have focused on developing visual analysis techniques tailored to the unique characteristics of urban environments. However, incorporating the third dimension into visual analytics introduces additional challenges in designing effective visual tools to tackle urban data's diverse complexities. In this paper, we present a survey on visual analytics of 3D urban data. Our work characterizes published works along three main dimensions (why, what, and how), considering use cases, analysis tasks, data, visualizations, and interactions. We provide a fine‐grained categorization of published works from visualization journals and conferences, as well as from a myriad of urban domains, including urban planning, architecture, and engineering. By incorporating perspectives from both urban and visualization experts, we identify literature gaps, motivate visualization researchers to understand challenges and opportunities, and indicate future research directions.

Racist dogs and classist rats?

In cities across the world, animals reflect, reproduce and transform urban inequalities – yet their role in mediating social hierarchies remains undertheorized. Urban scholars have begun to highlight the importance of infrastructures and technologies in configuring access to essential goods and services. While this research provides key insights into how non-human entities mediate unequal relations, it has largely overlooked how certain animals – „political animals“ – also co-produce inequalities. This article focuses on two critical urban domains, security and public health, that are often characterized by stark inequalities, and takes the role of key animals within these domains – dogs and rats, respectively – as a new analytical entry-point. Security dogs are socialized to identify threatening individuals on the basis of classed and raced markers. Rats thrive in upscale neighborhoods with historical architecture and abundant green space – yet the public health risks and the stigma associated with these rodents may disproportionately affect low-income residents. Drawing on research on security dogs in Kingston, Jamaica and rats in Amsterdam, this talk discusses the role of animals in the formation of sociospatial boundaries, and the distribution of resources and risks across urban spaces and populations. Focusing on the interactions these two types of „political animals“ have with both humans and infrastructure, it sets out a research agenda for studying how animals’ everyday encounters with their cultural and material environments combine to result in (in-)equitable social outcomes.

Effects of land surface temperatures on vegetation phenology along urban–rural local climate zone gradients

ContextUrbanization and local urban climate have multiple impacts on vegetation phenology in urban and suburban areas. Understanding these effects and their interactions with the surface urban heating effect remains limited.ObjectiveWe employed a time series of Earth observation data to analyze land surface phenology (LSP) dynamics and related environmental drivers in the highly urbanized Pearl River Delta (PRD) region.MethodsFirst, local climate zone (LCZ) maps were generated from Earth observation datasets of 2000 and 2019. Second, LSP (i.e., start, end, and length of season) were extracted from vegetation indices for 2000–2019. Thirdly, land surface temperature (LST) was used as an explanatory variable based on the LCZ of cities. Finally, interannual trends of LSP and their association with LST were analyzed, depending on the distance gradient of vegetation to compact high-rise buildings.ResultsUrban surface characteristics showed that LSP in regions dominated by compact and high-rise urban areas presented significant spatiotemporal variation at the start and end of season than those dominated by open, mid-rise, and low-rise areas. The impacts of spring and autumn LST in the daytime on LSP were slightly more substantial than those in the nighttime. The association of decreasing spring LST in the daytime with a delayed start of season is especially pronounced in urban domains.ConclusionsThe results indicate that vegetated areas adjacent to urban domains presented greater spatiotemporal dynamics than suburban and rural regions. Our study emphasizes the dependence of spatiotemporal changes in vegetation phenology on the effects of urban surface warming.

Human population density and blue carbon stocks in mangroves soils

Mangrove soils provide many important ecosystem services such as carbon sequestration, yet they are vulnerable to the negative impacts brought on by anthropogenic activities. Research in recent decades has shown a progressive loss of blue carbon in mangrove forests as they are converted to aquaculture, agriculture, and urban development. We seek to study the relationship between human population density and soil carbon stocks in urban mangrove forests to quantify their role in the global carbon budget. To this end, we conducted a global analysis, collecting mangrove soil carbon data from previous studies and calculating population density for each study location utilizing a recent database from the European Commission. Results indicate population density has a negative association with mangrove soil carbon stocks. When human population density reaches 300 people km−2, which is defined as ‘urban domains’ in the European Commission database, mangrove soil carbon is estimated to be lower than isolated mangrove forests by 37%. Nonetheless, after accounting for climatic factors in the model, we see the negative relationship between population density and soil carbon is reduced and is even non-significant in mixed effects models. This suggests population density is not a good measure for the direct effects of humans on mangrove ecosystems and further implies mangrove ecosystems in close proximity to very high population density can still possess valuable carbon stocks. Our work provides a better understanding of how soil carbon stocks in existing mangrove forests correlate with different levels of population density, underscores the importance of protecting existing mangroves and especially those in areas with high human population density, and calls for further studies on the association between human activities and mangrove forest carbon stocks.

Reconstructing Long-Term Synthetic Aperture Radar Backscatter in Urban Domains Using Landsat Time Series Data: A Case Study of Jing–Jin–Ji Region

Synthetic aperture radar (SAR) records important information about the interaction of electromagnetic waves with the Earth’s surface. However, long-term and high-resolution backscatter coefficient data are still lacking in many urban studies (e.g., building height estimation). Here, we proposed a framework to reconstruct the 1-km backscatter coefficient in 1990–2022 utilizing the Sentinel-1 Ground Range Detected data and Landsat time series data in the Jing–Jin–Ji (JJJ) region. First, we developed a regression model to convert the optical signals from Landsat into backscatter coefficients as the Sentinel-1 data, using observations from 2015 to 2022. Then, we reconstructed backscatter coefficients from 1990 to 2022 using the long-term Landsat data. Using the reconstructed backscatter coefficients, we analyzed the dynamic patterns of building height over the past decades. The proposed approach performs well on estimating the backscatter coefficient and its spatial pattern, with the annual mean absolute error, root mean square error, and R 2 of 1.10 dB, 1.50 dB, and 0.64, respectively. The temporal trends revealed from the reconstructed backscatter data are reliable compared with satellite observations at a relatively coarse resolution, with Pearson’s coefficients above 0.92 in 6 sample cities. The derived building height from the reconstructed SAR data indicates that the JJJ region experienced a noticeable upward expansion in 1990–2022, e.g., Beijing has the fastest growth rate of 0.420 km 3 /decade regarding the total building volumes. The proposed framework of reconstructing SAR data from optical satellite images provides a new insight to complement the long-term and high-resolution backscatter from local to global scales.

Impact of Urban Representation on Simulation of Hurricane Rainfall

AbstractTaking the examples of Hurricane Florence (2018) over the Carolinas and Hurricane Harvey (2017) over the Texas Gulf Coast, the study attempts to understand the performance of slab, single‐layer Urban Canopy Model (UCM), and Building Environment Parameterization (BEP) in simulating hurricane rainfall using the Weather Research and Forecasting (WRF) model. The WRF model simulations showed that for an intense, large‐scale event such as a hurricane, the model quantitative precipitation forecast over the urban domain was sensitive to the model urban physics. The spatial and temporal verification using the modified Kling‐Gupta efficiency and Method for Object based Diagnostic and Evaluation in Time Domain suggests that UCM performance is superior to the BEP scheme. Additionally, using the BEP urban physics scheme over UCM for landfalling hurricane rainfall simulations has helped simulate heavy rainfall hotspots.

Residential preferences, place alienation, and neighborhood satisfaction: A conjoint survey experiment in Toronto’s inner suburbs

ABSTRACT In this article, we study neighborhood preferences among residents of highly diverse, lower income suburban neighborhoods in Toronto, Ontario. By extending the typical application of conjoint designs to the urban domain, we show techniques for measuring place alienation—a sense of disconnection from place—and its impact on neighborhood satisfaction. We find that residents in lower SES neighborhoods share many of the same priorities as residents in higher SES neighborhoods when it comes to safety, transit, school quality, neighborliness, public spaces, and building types. However, differences appear across a range of preferences including bike usage, local commercial spaces, and cultural and recreation facilities. When considering place alienation and neighborhood satisfaction, we find a consistent, robust inverted relationship—as place alienation decreases, neighborhood satisfaction increases. Moreover, this relationship is not mitigated by socioeconomic factors, neighborhood conditions, or even attitudinal and experiential factors. We end with suggestions for future research.

The rise of military capital in Pakistan: Military neoliberalism, authoritarianism and urbanization

This article develops the concept of military neoliberalism that allows us to trace the historical development of Pakistani military capital with the expansion of market-led reforms and its mode of operation in the urban domain. Military neoliberalism signifies the double role of the military; firstly, using authoritarianism, the military has extended neoliberal reforms in collaboration with local and foreign capitalist classes over the decades. Secondly, the military has expanded its reach and operations in the economy at a large scale, transitioning into a sovereign capitalist power that operates independently from the rest of the state apparatuses and utilizes its powers for economic, political, and territorial objectives. Such dynamics are leading to new class transformations and producing seismic shifts within the state apparatuses because, along with a revitalized capitalist class, a class of military capitalists has emerged in different sectors of the economy, most prominently in industrial production, urban real estate, and infrastructure development. The category of sovereign capitalist power gestures towards the twin dynamics; firstly, the military can use violence for its strategic political and economic goals. Secondly, the military can operate above the law for the advantage of military capital. As a result, the increasing militarization of the economy, and the corporatization of the military, have produced a new system of socioeconomic and political control that relies upon repeated interventions of the military in politics to resolve class antagonisms, strengthen the power of local capital, and intensify the reach of global financial capital in different markets of Pakistan.