Dense Urban Areas Research Articles

Cross-Scaling Approach for Water-Flow-Regulating Ecosystem Services: A Trial in Bochum, Germany

Water-flow-regulating ecosystem services (ESs) determine the regulation of hydrological flows on the ground’s surface. A lack of water-flow-regulating ESs would cause environmental problems such as heavy rainfall runoff and urban water logging, leading to floods affecting well-being, especially in dense urban areas. Research on water-flow-regulating ES supply–demand relationships in urban areas is urgently needed to better support the management of urban surface runoff. However, matching the supply–demand relationships of water-flow-regulating ESs remains challenging. In this contribution, a cross-scale approach linking the supply–demand assessment of water-flow-regulating ESs on a macroscale and the evaluation of the constructed urban environment on a microscale was developed. The approach was applied in the city of Bochum, Germany, as a trial of bridging the “science–practice gap”. Our findings show that the supply–demand budget of water-flow-regulating ESs in Bochum exhibits an urban–rural difference and is also partially influenced by land cover transformations such as vegetation degradation. In addition, further assessment of the constructed urban environment confirmed the result from the assessment of water-flow-regulating ESs based on the understanding of the urban hydrological cycle in Bochum. To account for the mismatch in the supply–demand budget, we classified the typical superior and inferior forms of urban water-flow-regulating ESs through field research on the same extreme areas to summarize the operable optimization, enhancement, and protection suggestions for urban construction decision makers. Finally, the cross-scale approach was approved as a possible way to bridge the “science–practice” gap for water-flow-regulating ES research in urban areas.

Application of Multi-Channel Convolutional Neural Network to Improve DEM Data in Urban Cities

A digital elevation model (DEM) represents the topographic surface of the Earth and is an indispensable source of data in many applications, such as flood modeling, infrastructure design and land management. DEM data at high spatial resolution and high accuracy of elevation data are not only costly and time-consuming to acquire but also often confidential. In this paper, we explore a cost-effective approach to derive good quality DEM data by applying a multi-channel convolutional neural network (CNN) to enhance free resources of available DEM data. Shuttle Radar Topography Mission (SRTM) data, multi-spectral imaging Sentinel-2, as well as Google satellite imagery were used as inputs to the CNN model. The CNN model was first trained using high-quality reference DEM data in a dense urban city—Nice, France—then validated on another site in Nice and finally tested in the Orchard Road area (Singapore), which is also an equally dense urban area in Singapore. The CNN model not only shows an impressive reduction in the root mean square error (RMSE) of 50% at validation site in Nice and 30% at the test site in Singapore, but also results in much clearer profiles of the land surface than input SRTM data. A comparison between CNN performance and that of an earlier conducted study using artificial neural networks (ANN) was conducted as well. The comparison within this limited study shows that CNN yields a more accurate DEM.

Microclimatic and Environmental Improvement in a Mediterranean City through the Regeneration of an Area with Nature-Based Solutions: A Case Study

Dense urban areas are facing relevant issues related to their high vulnerability to the impacts of climate change and ecosystem health. The study presents a case study of a regeneration project with Nature-based Solutions in the city of Genoa (Italy) and, more specifically, in a neighbourhood characterised by relevant health and well-being issues. The performances of three design scenarios for a city hotspot, including plant species selected with a systemic approach and light pavements, are analysed in terms of improved microclimate by means of the ENVI-met software V4.4.5. The results show different benefits on the microclimate compared to the current state depending on the different scenarios: A UTCI decrease from 4.1 °C to 5.4 °C, a reduction of mean radiant temperature from 12.3 °C to 17.3 °C, a relative humidity increase from 3.8% to 5.6%, and a progressive decrease in wind speed are detected in a directly proportional way to the gradual increase in greenery inside the scenarios. In reverse, better results for air temperatures are detected for the scenario with less greening (Δt = 1.8 °C). The study relies on the re-parametrisation of plant species characteristics in the ENVI-met database to reach a high level of accuracy.

The effect of different road pavement typologies on urban heat island: a case study

ABSTRACT The Urban Heat Island (UHI) phenomenon is commonly solved by implementing materials with optimal thermic and evapotranspiration properties which help decreasing the air temperature in dense urban areas. This approach has been applied in this study, testing six different materials (replacing the current Macadam) in one parking area in Bari (Italy), which provides a large-scale testbed, by means of a thermal three-dimensional non-hydrostatic simulation: impervious asphalt pavement (IAP), asphalt permeable pavement (APP), green pavement (GP), green pavement-asphalt permeable pavement (GP+APP), grey porous concrete blocks (GCB), and light concrete permeable pavement (LCPP). The highest-performance pavements in terms of potential air temperature (PAT) reduction were the GP (−1.22°C), GCB (−1.26°C) and LCPP (−1.22°C), which also showed a constant relative humidity, suggesting their UHI mitigation benefits. A comparison of the structural properties as well as the construction and maintenance costs of such pavements is also provided, finding the best mitigation strategy (GCB).

GNSS NLOS Signal Classification Based on Machine Learning and Pseudorange Residual Check.

Global navigation satellite system (GNSS) positioning has recently garnered attention for autonomous driving, machine control, and construction sites. With the development of low-cost multi-GNSS receivers and the advent of new types of GNSS, such as Japan’s Quasi-Zenith Satellite System, the potential of GNSS positioning has increased. New types of GNSS directly increase the number of line-of-sight (LOS) signals in dense urban areas and improve positioning accuracy. However, GNSS receivers can observe both LOS and non-line-of-sight (NLOS) signals in dense urban areas, and more NLOS signals are observed under static conditions than under dynamic conditions. The classification of LOS and NLOS signals is important, and various methods have been proposed, such as C/N0, using three-dimensional maps, fish-eye view, and GNSS/inertial navigation system integration. Multipath detection based on machine learning has also been reported in recent years. In this study, we propose a method for detecting NLOS signals using a support vector machine (SVM) classifier modeled with unique features that are calculated by receiver independent exchange format-based information and GNSS pseudorange residual check. We found that using both the SVM classifier and GNSS pseudorange residual check effectively reduced the error due to NLOS signals. Several static tests were conducted near high-rise buildings that are likely to receive some NLOS signals in downtown Tokyo. For all static tests, the percentage of positioning errors within 10 m in the horizontal positioning error was improved by >80% by detecting and eliminating satellites receiving NLOS signals.

Mental health in smart cities: The role of technology during COVID-19 pandemic

COVID-19 has changed the daily lives of citizens around the world and exposed the vulnerability of life and the functioning of cities. The pandemic has forced citizens to adapt to new models of remote work during quarantine and access to smart technology-based services. The article aims to assess citizens' perceptions of the technological solutions provided by smart cities and, in particular, the municipality of Paphos before and after the Covid-19 pandemic, as well as to evaluate their impact on citizens' mental health. The results of the study contribute to the understanding of the mental health benefits for citizens living in smart cities compared to people living in low-tech areas, revealing the potential positive effects of smart technologies, as well as the change in people's digital decision-making before and after the pandemic

Associations of public open space attributes with active and sedentary behaviors in dense urban areas: A systematic review of observational studies.

In the context of rapid urbanization, public open spaces in dense urban areas are critical built environment elements to support active lifestyles. Several reviews have explored the associations of public open space attributes with physically active and sedentary behavior. However, few reviews have included studies from Asia, and no studies have focused on dense urban areas. This systematic review analyzed 18 observational studies investigating associations between public open space attributes with physical activity and sedentary behavior in dense urban areas of East Asian countries, including Japan, Taiwan, China, and Hong Kong. We found that closer distance to and a greater number of public open spaces and features within them were positively associated with leisure-time physical activity. Places near water features and corridors within public open spaces were associated with more sedentary behavior. These findings inform landscape and urban design guidelines for (re)designing public open spaces to support active lifestyles in high dense urban areas.

The Design Challenges for Dog Ownership and Dog Walking in Dense Urban Areas: The Case of Japan.

There has been growing interest in the role of pet ownership, particularly dog ownership, in managing noncommunicable diseases. The built environment can act as a facilitator or barrier to owning a dog or dog walking. Nevertheless, limited studies conducted in different geographical contexts have examined how the built environment can influence dog ownership and dog walking. In this interdisciplinary article, using Japan as a case study, we identify key design challenges to owning and walking dogs in dense urban areas as a means of promoting health and wellbeing.

A new construction method for metro stations in dense urban areas in Shanghai soft ground: Open-cut shafts combined with quasi-rectangular jacking boxes

At present, the metro station constructions in dense urban areas face significant challenges during the rapid urban metro network expansion. The repeating disturbances to city traffic, commerce, and residents' daily life induced by conventional open-cut metro station constructions can no longer be accepted in dense urban areas. To solve these problems, some underground excavation methods, such as enlarging shield tunnels, shallow tunnelling method and pipe-roof mining method, have been attempted, but it is difficult for them to be adapted to the strict limitation of urban space in soft ground. In this paper, the planning, construction, challenges, and relevant key techniques of an innovative type of metro station – open-cut shafts combined with quasi-rectangular jacking boxes (SCJB) were introduced and investigated. The main conclusions are as follows: (1) For the advantages of efficient underground space utilization and little impact on traffic and environment, the SCJB method is recommended for the constructions of metro stations that need to traverse the heavy traffic roads and express-way viaducts. The flexible combinations of open-cut shafts and jacking boxes can form various layouts of underground space to adapt to various complex surrounding environment. (2) Steel-concrete composite lining was designed for jacking boxes considering the transportation convenience and bearing capacity enhancement, and the corresponding earth pressure balanced box jacking machines were developed. (3) By applying thick thixotropic slurry with small filtration loss, the jacking resistance of the large-section box culverts was effectively reduced to 4–6 kPa and the total jacking force was kept at 30,000 kN. (4) By surveying with laser guiding system and performing timely rectifications, the trajectory deviations induced by two large adjacent box jacking were controlled within ±50 mm. The horizontal convergence of east line box segments caused by the west line jacking was controlled within 1.5 mm, through strict trajectory control. The surface settlement induced by the crossing of three box jacking tunnels was effectively controlled within 15 mm. The experiences learnt from this project can provide valuable references for the planning and construction of metro stations in dense urban areas in soft ground.

Locating Urban Consolidation Centers under Shipper Rationality

An urban consolidation center (UCC) is a logistics facility used to combine deliveries of multiple shippers for reducing freight traffic in dense urban areas. Despite their benefits, such as reducing less-than-truckload deliveries, former applications of UUCs have faced backlash from shippers that were forced to use them even though they did not experience any cost savings. Such failures are often due to an unsuitable location of the UCC and the additional costs of facility operation and maintenance that are unfairly divided between the shippers. This paper introduces shipper rationality to measure the willingness of shippers to use an optimally located UCC. We use a continuum approximation approach to derive the routing costs of the shippers as closed-form expressions. We present three objective functions depending on the preference of the regulatory agency that chooses the location of the UCC, allowing rational shippers to join only if they experience cost savings from the UCC. We discuss influential factors in the optimal location of a UCC, including the customer density of each shipper, the establishment cost of the UCC, and the location of each shipper’s fulfillment center.

Rapid Vehicle Detection in Aerial Images under the Complex Background of Dense Urban Areas

Vehicle detection on aerial remote sensing images under the complex background of urban areas has always received great attention in the field of remote sensing; however, the view of remote sensing images usually covers a large area, and the size of the vehicle is small and the background is complex. Therefore, compared with object detection in the ground view images, vehicle detection in aerial images remains a challenging problem. In this paper, we propose a single-scale rapid convolutional neural network (SSRD-Net). In the proposed framework, we design a global relational (GR) block to enhance the fusion of local and global features; moreover, we adjust the image segmentation method to unify the vehicle size in the input image, thus simplifying the model structure and improving the detection speed. We further introduce an aerial remote sensing image dataset with rotating bounding boxes (RO-ARS), which has complex backgrounds such as snow, clouds, and fog scenes. We also design a data augmentation method to get more images with clouds and fog. Finally, we evaluate the performance of the proposed model on several datasets, and the experimental results show that the recall and precision are improved compared with existing methods.

Energy efficiency in large office buildings post-COVID-19 in Europe's top five economies

Since the World Health Organization announced the COVID-19 pandemic, indoor airflows became a synonym for virus super-spreaders and the focus point for the scientific community and professional associations across the globe, disrupting all daily life dimensions. Europe's quick response to control the disease led the REHVA board to address mitigation guidelines, reassessed by each member association's following national specifics. The present study aims to quantify the energy consumption and CO2 emissions of “large office” buildings in top-five European economies under the COVID-19 guidelines under the post-pandemic telework forecast. Methodology resorted to a standard model under Building Energy Simulation assessment to compare prior and posterior scenarios. The latter displays a tendency to increase energy and CO2 emissions in all locations, in the first form 10.18% (Rome) to 69.48% (Paris); and second 5.80% (Rome) and 120.61% (Paris), which will affect national energy production and imports, urban pollution and business competitiveness. On a different scope, future HVAC guidelines need to address the incoming figures, particularly in highly dense urban areas. Also, to comply with the goals set by the Paris Accord.

Power couples, cities, and wages

Power couples, defined as pairs of highly educated partners, tend to cluster in cities to take advantage of more developed labor markets, better jobs, and higher wages. This research examines to what extent being a partner in a power couple brings additional wage income benefits. We examine what the effects of power couple partnering is on wage income. Furthermore, we examine how the results are affected by gender and place of residence. To determine this, the research uses detailed Swedish micro data on power couples 23–39 years of age over the period 2007–2016. Our analysis finds positive and significant results from being in a power couple on wage income after controlling for individual, workplace, and geographical characteristics. This is the case for both men and women in power couple households without children, but for women only when children are present. For power couples in denser urban areas, we find a positive effect for men in power couples with or without children. We suggest this effect is due to a more equal “balance of power” between partners in highly educated power couples located in bigger cities, where norms and values may favor a relatively greater sharing of household duties between men and women, and where men face a different competitive situation in the labor market.

Influence of building-site resonance and building properties on site-city interaction: A numerical investigation

Recently, the concept of ground motions within dense urban areas being significantly affected by upper building clusters has been widely accepted. However, multiple interactions between upper buildings and underlain soil layer have increased the complexity of the problem. In this study, we focused on the analysis of ground motion changes with respect to free-field motion caused by upper building clusters, and the seismic interaction between building clusters and underlain soil, named site-city interaction (SCI). Emphasis was placed on the influence of building-site resonance and building properties on SCI effects. Hence, a two-dimensional (2D) numerical finite element model coupled with a non-linear elastic-plastic soil model and a linear multiple degree-of-freedom building model was developed in the OpenSees framework.Numerical results showed that the SCI effects were strongly influenced by the building-site resonance effects and building properties. For special cases, the ground motion was reduced by more than 60% with respect to the free-field motion. Furthermore, the SCI effects decreased as the degree of soil non-linearity increased, whereas the ground motion caused by SCI effects reduced by more than 20% of the free-field motion. However, owing to the non-linear effects, several unexpected amplifications were observed at certain frequency bands.Overall, the results of this study present an insight into the relationship between building properties, building-site resonance effects and SCI effects, and provide a reference for further SCI analysis of real-life applications.

(Re-)Imagining Neighbourhood Spaces from a Transdisciplinary, Inclusive Research Perspective: The Vaartkom Case

Cities and dense urban areas are dynamic environments, always adapting to changing circumstances and shocks, such as the recent COVID-19 pandemic. The Vaartkom (or the Canal Bowl in English), a neighbourhood in Leuven, provides an interesting case study, having undergone a drastic transformation in the past two decades from a dilapidated industrial zone to mixed neighbourhood and cultural hotspot. This has introduced renewed and ongoing community dynamics, which inevitably influences the use of public and private space in the neighbourhood, creating new areas for inclusion and exclusion. This threefold transdisciplinary research focuses first on the spatial dynamics on the level of public space under COVID-19 as part of a wider series of neighbourhood dynamics. Second, it dives into the aspect of inclusive environments and third, it uses the transdisciplinary research process to reflect on a meta-level. Employing various methods – such as interviews, site visits, stakeholder and physical mapping exercises, we worked with community members to explore these spatial dynamics. Our findings highlight the conflicting expectations about the present and future use of public space. These opposing opinions reveal the tensions that exist among community members about how public spaces are used and whom they are for. This suggests there are multiple understandings of the Vaartkom. These multiple understandings were drawn from responses collected during a public engagement activity, which were subsequently analysed in a thematic and spatial way. This analysis brought forward influences of a temporal and spatial nature – that is, we acknowledge that the selected locations at which we engaged with community members, and the time of day, played a role in who we reached in the community and the responses we collected. This highlights the degree of awareness and participatory effort required to be truly inclusive. We therefore pro pose that future engagements involve the creation of a "Third Sphere" – a space for open, transparent and neutral dialogue – allowing the opportunity not only to imagine a collective future, but also to build bridges and help community members feel heard and empowered to contribute to the creation of a more inclusive post-COVID-19 environment.

Fourfold Bounce Scattering-Based Reconstruction of Building Backs Using Airborne Array TomoSAR Point Clouds

Building reconstruction using high-resolution tomographic synthetic aperture radar (TomoSAR) point clouds has been very attractive in numerous applications, such as urban planning and dynamic city modeling. However, for side-looking TomoSAR, it is a challenge to reconstruct the obscured backs of buildings using traditional single-bounce scattering-based methods. It comes to our attention that the higher-order scattering points in airborne array TomoSAR point clouds may provide rich information on the backs of buildings. In this paper, the fourfold bounce (FB) scattering model of combined buildings in airborne array TomoSAR is derived, which not only explains the cause of FB scattering but also gives the distribution pattern of FB scattering points. Furthermore, a novel FB scattering-based method for the reconstruction of building backs is proposed. First, a two-step geometric constraint is used to detect the candidate FB scattering points. Subsequently, the FB scattering points are further detected by seed point selection and density estimation in the radar coordinate system. Finally, the backs of buildings can be reconstructed using the footprint inverted from the FB scattering points and the height information of the illuminated facades. To verify the FB scattering model and the effectiveness of the proposed method, the results from the simulated point clouds and the real airborne array TomoSAR point clouds are presented. Compared with the traditional roof point-based methods, the outstanding advantage of the proposed method is that it allows for the high-precision reconstruction of building backs, even in the case of poor roof points. Moreover, this paper may provide a novel perspective for the three-dimensional (3D) reconstruction of dense urban areas.

The urban wage premium is disappearing in U.S. micropolitan areas.

A key driver of urbanization is the pursuit of economic opportunities in cities. One such opportunity is the promise of higher wages in larger cities, a phenomenon known as the urban wage premium. While an urban wage premium has been well-documented among U.S. metropolitan areas, little is known about its existence in micropolitan areas, which represent an important link between rural and dense urban areas. Here we measure the power law scaling coefficient of annual wages versus employment for both U.S. metropolitan and micropolitan areas over a 37-year period. We take this coefficient to be a quantification of the urban wage premium for each type of urban area and find the relationship is superlinear in all years for both area types. Though both area types once had wage premiums of similar magnitude, the wage premium in micropolitan areas has steadily declined since the late 1980s while in metropolitan areas it has generally increased. This growing gap between micropolitan and metropolitan wage premiums is ongoing in parallel to other diverging characteristics, such as inequality and voting behavior, suggesting that our result is part of a broader social, cultural, and political divergence between small and large cities. Finally, we speculate that if urban residents respond to the COVID-19 crisis by migrating, the trends we describe may change significantly.

Analysis of the potential of a new concept for urban last-mile delivery: Ducktrain

As cities continue to grow and the online retailing business continues to boom, last-mile logistics is becoming more and more of a challenge. This paper introduces Ducktrains, a new electric, automated, and compact light vehicle logistic solution for dense urban areas. Moreover, we present first insights on the potential of such a concept from a transport planning and social science perspective. Using a comparative transport analysis focusing on the factors speed, payload, and range, we validated the vehicles’ suitability for urban delivery. To explore social acceptance, we used an empirical mixed-method approach, conducting both a qualitative interview study (N = 70) and an online survey (N = 1007). Results of both analyses reveal the general suitability of the introduced concept for urban deliveries. The Ducktrains showed to be competitive for standard delivery tours, and acceptance was generally high, with the main associated advantages being environmental friendliness and quality of life improvements. However, some concerns, including negative impacts on the overall traffic situation and safety, remain from the public’s perspective.

The adoption of alternative delivery locations in New York City: Who and how far?

Online shopping has shown a remarkable growth trend for the past three decades. The increasing demand for deliveries resulting from online shopping generates lots of negative externalities contributing to traffic congestion, parking violations, and air pollution. To mitigate these negative externalities, the importance of an alternative delivery location (ADL) is growing in transportation area as delivery and transportation systems are intertwined. The ADL includes a delivery locker (e.g., Amazon Hub Locker), a brick-and-mortar store who partners with parcel delivery companies (e.g., UPS Access Points), and a postal store. Despite the growing size and importance of the ADL, little is known about receivers’ behavior on the ADL from the transportation perspective. To better understand the ADL, this research developed joint models of parcel demand and the ADL to investigate factors affecting (a) the adoption of the ADL and (b) the distance people are willing to travel using the NYC DOT Citywide Mobility Survey in 2018. The results show that delivery frequency received by respondents negatively affects the adoption but does not affect the tolerable distance. The impacts of socio-demographic attributes on the behavior are also discussed. A prediction to the entire population in Manhattan was made and a corresponding strategy to determine the optimal ADL location is discussed. This research is the first attempt comprehensively investigating behaviors on the ADL from the transportation planning perspective. This research will contribute to the literature in urban freight systems by improving understanding of the ADL in dense urban areas.

Lessons learned that impact acoustics from the California Courts Program

Architect Clifford Ham served as the Project Director and Principal Architect for the Judicial Council of California Administrative Office of the Courts. He was responsible for overseeing more than 450 court facilities throughout California. Projects ranged from renovations and small single court buildings in remote locations to new multistory (31 and 71 multiple purpose courtrooms) in dense major urban areas. As an architect, with courtroom design experience, he was able to efficaciously support all aspects of design, engineering, and specialty consulting. Throughout the process, projects were implemented to effectively meet the needs of various stakeholders. California Trial Court Facilities Standards, covering all aspects of architectural design and engineering, had been developed when the program began in 2006, with minor revisions leading up to the new 2020 edition. Revisions gained from first-hand experience emphasized changes in the guiding principles and updated technical areas which influenced the design and cost of courthouses. This presentation will review the discuss significant aspects of the overall courts program with specific emphasis on acoustics. Case study examples will present some interesting subtleties in the planning and design process that should be realized to avoid costly follow-up repair solutions after occupancy.