Dense Urban Areas Research Articles

Co-existing sanitation systems in dense urban areas

Co-existing sanitation systems in dense urban areas

Networks and Fragments: An Integrative Approach for Planning Urban Green Infrastructures in Dense Urban Areas

Networks and Fragments: An Integrative Approach for Planning Urban Green Infrastructures in Dense Urban Areas

Street trees: The contribution of latent heat flux to cooling dense urban areas

Trees are the most important natural factor to alleviate the urban heat island effect and the latent heat flux (LE) they release contributes significantly to urban cooling. In this study, the model ENVI-met was used to study the influence of building geometry on the LE exchanged by trees at the block scale in compact urban areas. The building density (BD), building height (BH) and sky view factor (SVF) were used to characterize building geometry. The sensitivity of LE to building geometry was estimated by multi-linear regression analysis. The following conclusions were drawn:(1) the LE of trees is sensitive to building geometry, higher during daytime than night-time in winter and the higher during night-time than daytime in summer; (2) LE changes as expected across the seasons, with LE larger in summer; (3) The shade affects the LE of a tree by influencing the solar irradiance; (4) In winter the average LE of a single tree is larger with 0.06 than 0.12 fractional vegetation cover (FVC). This study can provide useful leads towards further research to explore latent heat exchanges by trees at the street scale.

Water Volume and 3D Topographic Analysis of Hub Dam, Karachi, Using Remote Sensing and Global Bathymetry Data

Background: Karachi one of the largest and fastest-growing cities in the world, the city faces severe water scarcity and aggravated by climate change, excessive groundwater extraction in dense urban areas and inefficient water distribution systems. The Hub Dam, along with the Keenjhar Lake, is the source of water for Karachi's population as well as for the industrial and urban agricultural sectors. It is therefore important to have current information on the dam's storage capacity, its topographic features and the hydrological dynamics of its catchment area, which remains poorly understood to date. Objectives: This study's primary objectives are (1) to assess the hydrography of Hub Dam using global bathymetric and remote sensing data and (2) to create a detailed 3D model of the dam to facilitate analysis of its hydrological features. (3) Also generate data-driven insights to guide improvements in Karachi’s urban water management policies. Methods: The methodology integrates global bathymetric data with remote sensing and Google Earth Engine (GEE) for analysing Hub Dam’s hydrological and topographic characteristics. Data processing and visualization were conducted in Google Colab by python codes. This process enabling an efficient workflow for handling and analysing large datasets. Results: Hub Dam 3D model is developed. The approaches is enhancing visualization of the dam's water volume and terrain features to support detailed hydrological analysis. 3D volumetric analysis estimates with total water volume at approximately 79.954 · 106 m3. It was found that currently, the Hub Dam reservoir has enough water to fulfil Karachi needs for 503 days, a critical reserve for urban planning, resource management. Using a topographic analysis that includes surrounding slopes and watershed features, key elements affecting dam performance were identified. This result helps to adjust the filling of the dam with water. The Hub Dam's ability to store water was confirmed through a preliminary volume assessment. Conclusion: The study successfully achieved its objectives. The results obtained highlight the importance of adaptive well informed strategies for sustaining well managed water resources in response to environmental pressures. The current study further advance rational water management by integrating remote sensing and data-driven methodologies into this area of knowledge. That is, the effectiveness of Using Remote Sensing and Global Bathymetry Data has been repeatedly proven by other studies in different areas of knowledge. However, in the current study, this scientific approach has successfully demonstrated the efficient and rapid acquisition of accurate, up-to-date information on reservoir capacity and hydrological characteristics, which opens up new opportunities for efficient water management.

Urban Heat Island and Environmental Degradation Analysis Utilizing a Remote Sensing Technique in Rapidly Urbanizing South Asian Cities

Rapid urbanization in South Asian cities has triggered significant changes in land use and land cover (LULC), degrading natural biophysical components and intensifying urban heat islands (UHIs). This study investigated the impact of LULC changes on land surface temperature (LST) and the role of biophysical indicators in enhancing urban resilience to thermal extremes. We used Landsat satellite imageries from 1993 to 2023, conducted a comprehensive analysis of LULC changes, and estimated LST variations at 6-year intervals in the Dhaka, Gazipur, and Narayanganj districts in Bangladesh. Afterward, we performed statistical analysis upon employing correlation, regression, and principal component analysis (PCA) techniques to summarize information. The results reveal that 339.13 km2 worth of urban expansion has occurred in last 30 years, with an average annual growth rate of 3.5%, accompanied by a substantial reduction in water bodies (−139.17 km2) and vegetation cover. Consequently, summer temperatures exceeded approximately 36.52 °C in dense urban areas. Also, the results highlighted the strong influence of built-up areas (BSI and SAVI) on LST, while vegetation (NDVI) and water indices (NDWI) exhibited a negative association. The findings emphasize the urgency of integrating green infrastructure and deploying sustainable urban planning policies to mitigate the potential adverse impacts of scattered urbanization in the face of climate change.

Using spatial analysis to examine inequalities and temporal trends in food retail accessibility.

In this paper, we examined whether there are inequalities in access to food retail (by type and healthiness) across local government areas (LGA) in Greater Melbourne and by LGA grouped based on their distance from the central business district and Growth Area designation. We also examined whether these inequalities persisted over time. This is a secondary analysis of a repeated cross-sectional census of food outlets collected at four time points (2008, 2012, 2014 and 2016) across 31 LGA. Using Geographical Information Systems, we present a spatial analysis of food retail environments in Melbourne, Australia, at these four times over eight years. Greater Melbourne, Australia. 31 LGA in Greater Melbourne. Findings show significant inequalities in access to healthy food retail persisting over time at the LGA level. Residents in lower density urban growth areas had the least access to healthy food retail. Unhealthy food retail was comparatively more accessible, with a temporal trend indicating increased accessibility over time in urban growth areas only. Accessibility to food outlets, particularly healthy food outlets and supermarkets, in Greater Melbourne is not equal. To identify and address health inequalities associated with rapid urban growth, further understanding of how people interact with the food environment needs to be explored.

Analysis of the Spatial Constraints of Urban Underpass Channels Based on BIM

The construction of urban underpasses faces various spatial constraints, which will lead to deformation or failure of the structures if not satisfied. The introduction of BIM (Building Information Modeling) and other modern information technology to achieve rapid and accurate spatial constraint analysis of the design scheme is of great significance to ensure the quality and safety of the underpass and adjacent structures. Firstly, through extensive literature collection and survey, the key spatial constraint indicators of underpasses in dense urban spaces and the evaluation rules of each indicator are determined. Then, an SQL (Structured Query Language)-based database of spatial constraint rules for underpasses in dense urban space areas is constructed, and the spatial constraint analysis process for underpasses in dense urban space areas is proposed. Finally, based on Building Information Modeling, programming support, and a development environment provided by C# and Visual Studio, a spatial constraint analysis system for underpasses in dense urban space areas is developed to realize complex spatial constraint analysis functions. The application practice of the system is carried out by taking a city underpass project as an example. The results show that in the design of urban underpass engineering, the spatial constraint analysis system designed in this paper and the calculation method adopted can simplify the model transmission process, save on labor costs, and reduce the error of the calculation results.

Semantic Segmentation Uncertainty Assessment of Different U-net Architectures for Extracting Building Footprints

Abstract. Automatic extraction of building footprints from aerial and space imageries has been found ever increasing importance in urban planning, disaster management, and environmental monitoring. However, achieving accurate building footprint extraction poses significant challenges due to diverse building characteristics and their similarities to their background elements. While conventional methods in building footprint extraction have mainly relied on image processing techniques, recent advancements in deep learning, particularly semantic segmentation algorithms like U-Net, have shown promise in addressing these challenges through machine learning. This study explores different depths of the U-Net model for building footprint extraction, aiming to identify the optimum architecture while investigating the semantic uncertainty of the building footprint extraction. Utilizing aerial imagery from cities including Berlin, Paris, Chicago, and Zurich, collected from Google Maps and OpenStreetMap (OSM) data, five U-Net models have been compared with varying depths. In addition, the impact of dataset sizes and learning rates on model performance has been investigated. Results confirmed that the U-Net-32-1024 model achieves the highest intersection over union (IoU), Accuracy, and F1-score. Moreover, increasing the training dataset size leads to significant improvements in model performance with IoU, Accuracy and F1-score reaching their values of 73.73%, 88.65% and 88.53%. However, challenges remain in accurately delineating buildings in dense urban areas. Nonetheless, our findings demonstrated the effectiveness of U-Net models in building footprint extraction.

Barn owl site occupancy and breeding success in relation to land use and nest box characteristics

AbstractAgricultural landscapes play a crucial role in enhancing biodiversity because of their widespread presence over the Earth and their ability to encompass diverse ecosystems. Recognizing this, numerous governments are incentivizing farmers through direct payments to adopt sustainable practices, such as managing extensive pastures and meadows, planting wildflowers, or establishing hedgerows. However, the benefit of such sustainable practices on vertebrate species is not well understood. From 2018 to 2020, we investigated nest occupancy, fledging success, and clutch size of a Swiss population of barn owls (Tyto alba) with respect to nest box characteristics and the presence of extensive agriculture and urbanization in areas surrounding nest boxes. Our results revealed that extensively used pastures were positively associated with site occupancy but negatively associated with clutch size. The proportion of urban areas was negatively related to both site occupancy and clutch size. The altitude of the nest box location was negatively correlated with occupancy, and the number of nest boxes placed at the same site (either 1 or 2) was positively correlated with site occupancy. Moreover, clutch size, but not fledging success, was larger in nest boxes placed outside barns than in nest boxes placed inside barns. Based on these findings, we recommend installing nest boxes at locations <700 m in altitude and in pairs on the same barn, incorporating biodiversity promotion areas into agricultural landscapes, and avoiding dense urban areas in favor of rural zones with lower urban density. Understanding the nuanced relationships between nest box characteristics, environmental factors, and breeding success provides valuable insights for optimizing artificial nesting sites and enhancing the overall reproductive success of barn owls.

Urban environmental acupuncture as a tool to support nature-based solution implementation: does it deliver what it promises?

Urban environmental acupuncture (UEA) is a novel approach designed to engage with a variety of stakeholders to successfully implement nature-based solutions in dense urban areas. The Interreg Central Europe project SALUTE4CE piloted this concept through small-scale, low-budget interventions in four cities: Chorzow (Poland), Erfurt (Germany), Alessandria (Italy), and Liptovski Mikulas (Slovakia). The pilot projects were designed to be quickly implementable, utilizing abandoned or undesirable sites, with the potential to catalyze both physical and social transformation. Interviews with local actors in these cities after project implementation provided valuable feedback, which was used to develop principles of urban environmental acupuncture. While the limited number of interviews means these findings offer only initial insights, they are largely supported by existing research. Nevertheless, this perspective provides important lessons that can inform future transformation projects and help evaluate the success of the UEA approach. The key contributions of this work are the introduction of urban environmental acupuncture concept, deriving principles of UEA based on feedback from local stakeholders and offering insights in future design and evaluation of similar nature-based solution initiatives in dense urban environments. This perspective helps to establish the potential of UEA as a tool for engaging diverse stakeholders and catalyzing sustainable urban transformation (specifically expansion of nature-based solutions) through low-cost interventions.

Kinodynamic Model-Based UAV Trajectory Optimization for Wireless Communication Support of Internet of Vehicles in Smart Cities

Unmanned aerial vehicles (UAVs) are utilized for wireless communication support of Internet of Intelligent Vehicles (IoVs). Intelligent vehicles (IVs) need vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) wireless communication for real-time perception knowledge exchange and dynamic environment modeling for safe autonomous driving and mission accomplishment. UAVs autonomously navigate through dense urban areas to provide aerial line-of-sight (LoS) communication links for IoVs. Real-time UAV trajectory design is required for minimum energy consumption and maximum channel performance. However, this is multidisciplinary research including (1) dynamic-aware kinematic (kinodynamic) planning by considering UAVs’ motion and nonholonomic constraints; (2) channel modeling and channel performance improvement in future wireless networks (i.e., beyond 5G and 6G) that are limited to beamforming to LoS links with the aid of reconfigurable intelligent surfaces (RISs); and (3) real-time obstacle-free crash avoidance 3D trajectory optimization in dense urban areas by modeling obstacles and LoS paths in convex programming. Modeling and solving this multilateral problem in real-time are computationally prohibitive unless extensive computational and overhead processing costs are imposed. To pave the path for computationally efficient yet feasible real-time trajectory optimization, this paper presents UAV kinodynamic modeling. Then, it proposes a convex trajectory optimization problem with the developed linear kinodynamic models. The optimality and smoothness of the trajectory optimization problem are improved by utilizing model predictive control and quadratic state feedback control. Simulation results are provided to validate the methodology.

The X-Minute City: Analysing Accessibility to Essential Daily Destinations by Active Mobility in Seville

The concept of the “x-minute city” emphasises connected, mixed-use, and functionally dense urban areas where residents can access most daily necessities within a short walk or bike ride. By promoting proximity to essential destinations and sustainable transport options, this approach reduces the need for extensive travel and minimises environmental impact. This paper analyses the readiness of cities to function as x-minute cities and identifies necessary interventions. Using a reproducible and scalable methodology based on open data and software, the study assesses the accessibility of key urban amenities within specified timeframes. Cumulative accessibility metrics are calculated for different destination categories, considering both walking and cycling. In the case of Seville, accessibility requirements outlined in policy documents are already met for many essential services, particularly public facilities. The study identifies neighbourhoods that excel in accessibility and others that require improvement in adhering to x-minute city principles. The methodology and findings can inform planning and policy decisions in other cities, guiding efforts to enhance amenity provision, test accessibility scenarios, and target intervention areas.

Testing the Impact of Pansharpening Using PRISMA Hyperspectral Data: A Case Study Classifying Urban Trees in Naples, Italy

Urban trees support vital ecological functions and help with the mitigation of and adaption to climate change. Yet, their monitoring and management require significant public resources. remote sensing could facilitate these tasks. Recent hyperspectral satellite programs such as PRISMA have enabled more advanced remote sensing applications, such as species classification. However, PRISMA data’s spatial resolution (30 m) could limit its utility in urban areas. Improving hyperspectral data resolution with pansharpening using the PRISMA coregistered panchromatic band (spatial resolution of 5 m) could solve this problem. This study addresses the need to improve hyperspectral data resolution and tests the pansharpening method by classifying exemplative urban tree species in Naples (Italy) using a convolutional neural network and a ground truths dataset, with the aim of comparing results from the original 30 m data to data refined to a 5 m resolution. An evaluation of accuracy metrics shows that pansharpening improves classification quality in dense urban areas with complex topography. In fact, pansharpened data led to significantly higher accuracy for all the examined species. Specifically, the Pinus pinea and Tilia x europaea classes showed an increase of 10% to 20% in their F1 scores. Pansharpening is seen as a practical solution to enhance PRISMA data usability in urban environments.

Comparing Sentinel-2 and Landsat 9 for land use and land cover mapping assessment in the north of Congo Republic: a case study in Sangha region

ABSTRACT A study of land use and land cover (LULC) mapping using satellite data was conducted in the Congo Basin rainforest in the Sangha area of the northern Congo Republic, which is crucial for sustainable land management. However, the heterogeneous nature of LULC features makes data classification difficult in this area because persistent cloud cover is challenging for observing the land surface and tropical humid conditions characterizing the study area. This study compares and evaluates the potential of two of the most widely used and popular satellite image sources, the recently launched Landsat 9 and Sentinel-2, to generate land-use land cover (LULC) maps in the Sangha area using pixel-based supervised machine learning algorithms, Random Forest (RF), for classification. All procedures were performed using ArcGIS Pro. The potential to improve Landsat 9 performance was tested using the nearest resampling technique, and different bands were resampled from 30 × 30 to 10 × 10 m. Owing to the heterogeneous characteristics of the Sangha study area, six classes were defined: dense forest, open forest, wetland forest, water bodies, urban areas, and bare soils. To classify and compare Sentinel-2 and Landsat 9, the shortwave infrared (SWIR), Near Infrared (NIR), and Red, Green, Blue (RGB) bands were used. These two satellite images were compared to test the quality of their results, particularly for assessing the accuracy of the LULC classifications and identifying which dataset had the highest accuracy. Results show that overall accuracy was 93.80% for Sentinel-2 while it was 91.60% for Landsat 9, similarly, the Kappa coefficient was calculated 0.89 and 0.85 for Sentinel-2 and Landsat 9, respectively. Therefore, Sentinel-2 exhibits significant classification ability compared to the nearest resample technique Landsat 9, despite the improved resolution of the latter, which offers a scientific basis for choosing the appropriate satellite imagery to create accurate LULC maps.

Experimental study on residual compressive bearing capacity of cracked reinforced concrete columns by SCDA

Abstract The static demolition of structures via soundless chemical demolition agent (SCDA) is attracting increasing attention because of its environmental friendliness and safety, especially in the dense urban areas. However, the research on the application of SCDA in demolishing the reinforced concrete is still scarce, seriously limiting the development of static demolition. In this work, with the combined efforts of experiments and theoretical analysis, we investigate the critical role of borehole layouts in the static demolition of reinforced concrete (RC) by determining the occurrence and expansion of cracks during static demolition, and the resulting residual mechanical properties of RC. The results show that the growth of cracks is significantly dependent on the reaction of SCDA. Additionally, the initiation time of cracking exhibits minimal sensitivity to variations in the layouts pattern of boreholes, while the progression of cracking is predominantly governed by the layouts of boreholes. We demonstrate that cracks formed in static demolition process can significantly reduce the strength of RC with about the remaining bearing capacity is only 10% to 33% of the original and change its failure mode. Further, it is point out that the key factor controlling the failure of RC under axial compression (i.e., the integrity of structures), and the RC with larger crack size and less structural integrity is more prone to fail. The results and findings in this work further clarify the role of borehole layouts and are of great significance in improving the efficiency of static demolition.

Secondary Spaces of Entrance, Corridor, and Balcony in Tehran Housing - A Comparative Analysis with Nagoya Residences

Due to increasing costs and shrinkage of Tehran housing, interior layout plays a more critical role. In addition to the main spaces, such as the bathroom, kitchen, and bedroom, which are present and vital in each residential unit, we identified entrance, corridor, and balcony in our Tehran samples as secondary spaces. We aimed to investigate these spaces' role in Tehran's current housing; we analyzed their existence, size, and relationship with the unit's total area by considering the background and history of these spaces. Japan's experience in small housing convinced us to utilize under 100 m2 of Nagoya samples for comparison. Results revealed sufficient area for these three spaces in all Nagoya samples. In contrast, these spaces in a large percentage of Tehran samples did not exist or lacked efficiency contrary to related rules and regulations. There was a weak correlation between unit size and the lack of entrance and balcony, but corridor was usually removed in smaller units. We suggest separate entrance and corridor as essential spaces and not optional, regardless of unit size. Also, transparent, and visible balconies, especially in dense urban areas, are incompatible with the Iranian lifestyle and should be adjusted to cultural beliefs and norms.

Vegetation density is the main driver of insect species richness and diversity in small private urban front gardens

Urbanisation changes natural ecosystems and vegetation to urban green spaces, and causes insect communities to experience novel challenges for survival. New evidence suggests that urban green spaces, no matter how small, can provide meaningful habitats for insects. Information on design and management of small gardens (<6m2) in dense urban areas is still scarce. In particular, it is hardly known which garden designs provide most benefits to insects. We surveyed 65 small urban façade gardens (μ=1.7m2) in Amsterdam and The Hague in The Netherlands and measured various garden attributes that are expected to be relevant for general, flower-visiting and herbivorous insect species richness and diversity. Plant coverage and richness were the strongest predictors of insect biodiversity and species richness. We found no support for associations with native plants or garden size. Synthesis and applicationsTo strengthen insect biodiversity in the urban environment, we recommend future design of urban green spaces to focus on maximising coverage and richness of vegetation. Although there are advantages to using native species, we acknowledge that garden owners often prefer exotic species. Some of these can also affect insect diversity and abundances positively.

Older adults’ decisions regarding mobility to age in place in medium- and high-rise multi-storey residential buildings in urban settings: A case study of South East Queensland, Australia

Population ageing and urbanisation requires a more thorough understanding and monitoring of older adult residential mobility trends. Many older adults move to urban areas and previous studies have been carried out on ageing in place in traditional low-rise residential buildings. However, there is little in the literature about the important push and pull factors influencing older adult moves to medium- and high-rise multi-storey residential buildings in urban areas as they age. This case study research considered the housing migration model of push and pull factors used in elderly residential mobility and investigated the older adults' decision-making regarding mobility to age in place in medium- and high-rise multi-storey residential buildings in South East Queensland, Australia. The study revealed how the older adults expressed a desire to age in place in multi-storey residential buildings in urban areas and identified it as an important element of quality of life. Many older adults chose to move house to high density urban areas from low density urban areas between the ages of 65 and 84. The ‘pull’ factor to significantly influence the decisions of movers was a low maintenance property and lifestyle change from a large suburban home whereas the ‘push’ factor was upkeep difficulties of the house related to old age. This study makes empirical contributions to knowledge in ageing residential mobility trends in urban areas and concludes by providing policy recommendations for developing more effective housing, public spaces, transportation, and community activities and services for older adults, including highlighting a number of recommendations for future research.

A benchmarking analysis of sunlight and daylight availability in a highly dense urban area in southern China

The availability of daylight and sunlight in dense cities has increasingly received attentions. This article presented a benchmarking analysis of daylight & sunlight availability in six urban residential layouts at Guangzhou in southern China. As representatives of old or new towns, these layouts were achieved using local regulations. The benchmarking system was built based on an urban building under various levels of obstruction (horizontally infinite length). Daysim (Radiance) and T-sun were applied to calculate daylight illuminance and sunlight hours at building facades, respectively. Some findings were achieved as follows: 1) For sunlight availability, significant effects of urban layout and orientation can be found in both towns. Most layouts achieved similar sunlight hours as an urban building with high and heavy obstructions, while several southeast-oriented and southwest-oriented layouts had the values like a building with the medium obstruction. No clear differences of sunlight hours can be found between southeast and southwest orientations. 2) For daylight availability, most buildings in both towns had similar frequencies of proper vertical illuminance as an urban building with the medium obstruction. However, the frequencies of excessive vertical illuminance significantly varied in layout, façade position, and orientation and corresponded with the values of an urban building with different obstructions. Effects of layout were found to be clear at low and middle façade positions, while significant effects of orientation were only found at higher façade positions. 3) Generally, a daylighting analysis using the dynamic climate-based model could achieve more practical results than the approach of sunlight hours.

Evaluating urban biodiversity: Effectiveness of citizen science driven species distribution models in urban ecosystems

Citizen science (CS) and remote sensing (RS) approaches have become more reliable, thus providing higher resolution and generating a large amount of environmental data. When considering urban environments, where fragmented and highly diverse landscapes are predominant, the combination of citizen science data and remote sensing techniques with species distribution models (SDM) can play a vital role in comprehensively investigating and evaluating urban biodiversity. However, citizen science derived species distribution models for multiple avian species in dense and fragmented urban areas are rarely used. The study aims (I) to elaborate, whether CS driven SDMs can be effectively used in spatially complex urban environments; (II) to identify biodiversity hotspots and prioritize areas for nature conservation and (III) to examine, if existing protective areas correspond to species’ hotspots. Therefore, Citizen science-based datasets of 26 breeding bird species over three years were obtained for this analysis in Germany’s Ruhr Metropolis. Quality assurance, data thinning, and pseudo-absence simulations were performed. Spatial data from the ecosystem LiDAR project GEDI (Global Ecosystem Dynamics Investigation), climate data from the German Weather Service, and land use information from Copernicus were used as environmental predictors. Eleven different species distri-bution models (SDMs) were trained on species subselection by using Biomod2 for preliminary analysis. Overall model performance was evaluated via several metrics, including TSS (true skill statistics) and ROC (receiver operating characteristic). Finally, four species distribution models were used for ensemble modelling. Subsequently, a species richness analysis was performed with the aim of identifying spots with high avian biodiversity. Overall, the CS-derived SDMs performed well, with high predictive power for all of the investigated species. Within the Ruhr Metropolis, approximately 6% (250 km²) of the terrain was identified as being highly suitable for avian diversity, inhabiting at least 17 out of 26 species. Predominantly within the core urban areas, high species richness was predicted on preserved brownfields and revitalized mine sites, as well as in the remnants of formerly demarcated regional greenbelts. Additionally, regions outside of the core area, which are part of the overarching biotope network framework, proved to have high species richness capabilities for avian biodiversity. These findings aid in optimizing urban development concepts and (sub)urban green space management with respect to urban biodiversity conservation. Following the implications of the recently established Regional Biodiversity Strategy in the Ruhr Metropolis, this analysis demonstrates the importance of networked green spaces, their preservation and the need to close existing network gaps within the Ruhr Metropolis.