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Guiding the transformation of cities and regions towards more sustainable pathways requires a deep understanding of the complexities of socio-ecological systems. This entails gaining insights into the status and trends of biodiversity, ecosystems and their services (BES), as well as navigating complex governance and power structures, particularly in contested spaces. Digital dashboards, understood as visual representations of key information, could effectively communicate complex BES information to decision makers and planners in landscape and urban planning, enabling more informed decisions. While dashboards are increasingly being used in spatial-related applications, the lack of scientific understanding regarding the emerging applications of BES information in dashboards underscores the pressing need for research and review in this area. This study aims to identify and analyze contemporary case studies of BES dashboard applications to explore their potential role, which can effectively support decision-making in landscape and urban planning. We develop a conceptual framework of interlinkages between BES dashboards and landscape planning processes and apply this framework to analyze 12 state-of-the-art BES dashboard applications from Asia, Australia, Europe, North and South America. Our results reflect emerging practices of dashboards visualizing BES information, which varied in purposes, content, functionalities, visual design, and output features. The dashboards represented/covered a total of 66 BES indicators, including tree health, forest status and functionality, green and blue spaces connectivity, and specific components of biodiversity. Further research on user demands and real-world impacts is necessary to enhance the effectiveness of BES dashboards in informing landscape and urban planning for people and nature. Dashboards for reporting BES information: Dashboards can facilitate the communication of biodiversity, ecosystems and their services (BES) information, providing policy makers with useful information for decision-making. Framework for analysis: Our conceptual framework developed for assessing BES dashboards in landscape and urban planning contexts enables practitioners to understand BES dashboard applications and opportunities. Insights into worldwide BES dashboards: Our analysis of 12 state-of-the-art of BES dashboards applications worldwide highlights the global reach of this tool. Decision-makers can gain valuable insights from various regions for addressing local biodiversity and ecosystem challenges. Diverse range of indicators and customizations: BES dashboards take diverse forms, including a wide range of indicators to customize BES information for local contexts and priorities. Future BES dashboards research: Future research and innovation should enhance BES dashboards' integration with planning systems, align with user demands, and impact real-world decision-making. [ABSTRACT FROM AUTHOR]

Significant increase in the proportion of elderly and its expected further increase in the days to come draw attention of policymakers, practitioners, and researchers to enhance a community's age-friendliness. Enhancement of a community's age-friendliness requires appropriate policy implications recommended by various stakeholders based on Multi-Criteria Decision Analysis (MCDA) followed by Friedman's rank test. Results showed that 'safety and security' has the highest priority amongst all the criteria considered for the assessment of age-friendliness. Based on Friedman's rank test, community boundary with security check posts has the highest priority to increase safety and security of the community. A combination of policy measures having higher priority such as 'police patrolling', 'mixed land-use urban planning', and 'accessibility to services' could be the effective solution to increase safety and security of the community environment and foster independent living ability of its residents which in turn play important role in increasing age-friendliness of the community. [ABSTRACT FROM AUTHOR]

The relationship between urban density and social conditions in urban areas has received increasing attention in recent research. However, there is a lack of understanding of the dynamics between urban densification and these social conditions from a place-specific perspective, taking into account the institutional, socio-cultural, and contextual complexities. This paper seeks to enhance this understanding by unpacking the relationship between soft densification and place attachment in Tehran, Iran. The paper develops a framework for studying 'soft densification' as a process of incremental place change by prioritising local knowledge. The findings suggest that soft densification impacts place attachment by disrupting the everyday functionality of place, eroding its physical characteristics, erasing some of its collective and personal memories, and altering its socio-demographic structure. The paper highlights the importance of thinking 'procedurally' and 'topologically' about urban densification and calls for incorporating local knowledge and experiences into policy planning and urban decision-making. [ABSTRACT FROM AUTHOR]

The unprecedented urbanization in China has dramatically changed the urban spatial structure of cities. With the proliferation of individual-level geospatial big data, previous studies have widely used the network abstraction model to reveal the underlying urban spatial structure. However, the construction of network abstraction models primarily focuses on the topology of the road network without considering individual travel flows along with the road networks. Individual travel flows reflect the urban dynamics, which can further help understand the underlying spatial structure. This study therefore aims to reveal the intra-urban hierarchical spatial structure by integrating the road network abstraction model and individual travel flows. To achieve this goal, we 1) quantify the spatial interaction relatedness of road segments based on the Word2Vec model using large volumes of taxi trip data, then 2) characterize the road abstraction network model according to the identified spatial interaction relatedness, and 3) implement a community detection algorithm to reveal sub-regions of a city. Our results reveal three levels of hierarchical spatial structures in the Wuhan metropolitan area. This study provides a data-driven approach to the investigation of urban spatial structure via identifying traffic interaction patterns on the road network, offering insights to urban planning practice and transportation management. [ABSTRACT FROM AUTHOR]

A common challenge shared across cities of the Global South is the seemingly impossible task of drawing a consensus on the right interventions and regulatory framework for street hawkers. This impediment, for many countries, originates from not only the pervasive nature of how this sector is characterized, but also the fluidity associated with their perceptions among urban planners and policy makers. This study highlights that while urban planners and state authorities perceive street hawking as a nuisance and try to forcefully evict them from spaces they occupy, some enterprises have modified traditional street hawking to develop what we term "corporate street hawking" in Accra, Ghana. This article presents findings drawing upon semistructured interviews with 47 street hawkers in Accra. [ABSTRACT FROM AUTHOR]

"Settler Colonial City: Racism and Inequity in Postwar Minneapolis" by David Hugill examines the history of racism, inequity, and settler-colonial structures in Minneapolis, particularly focusing on the post-World War II era. The book explores the impact of urban change, racialized policing, and American imperialism on marginalized communities, with a particular emphasis on Indigenous peoples. Hugill highlights the structural barriers faced by marginalized groups and the need to dismantle white supremacist and settler-colonial structures. While the book primarily focuses on the violent aspects of settler-colonial urban policy, it also touches on the need to examine more subtle elements such as access to education, healthcare, and legal services. Overall, the book provides a critical perspective on the history of Minneapolis and challenges the perception of the city as progressive and inclusive. [Extracted from the article]

The acceleration of urbanization leads to a geographical extension of cities, longer distances and travel times, increased motorization, and a constantly growing population. Faced with this situation, new urban policies are attempting to control the interaction between urban planning and urban mobility and to redefine a new dimension of proximity, which reduces excessive use of energy-consuming and polluting modes of travel, namely vehicles. This orientation is embodied in the 15-minute city model, which focuses on pedestrian accessibility from one's home to nearby services and urban spaces. From this perspective, the paper proposes a GIS-based model to evaluate pedestrian accessibility to mosques. Using the open-source software QGIS, a total number of 30 mosques in the Agdal district in the city of Fez in Morocco were studied to investigate their pedestrian accessibility, by examining their spatial distribution and also their capacity to accommodate the worshippers of their catchment areas. Considering the land use and the population density of each mosque's catchment area, the results showed that even if a mosque can be spatially accessible by walking, it may not be able to comfortably satisfy the potential worshippers in its area of influence. Many people are then forced to travel long distances, sometimes by vehicles, to reach other mosques that can eventually accommodate them. The proposed method helps city planners better understand the urban configuration in terms of spatial and functional pedestrian accessibility, for more inclusive and equitable cities. [ABSTRACT FROM AUTHOR]

Semantic understanding of high spatial resolution remote sensing (RS) images can be divided into object detection, object labelling, identification of geospatial relationships, and semantic description generation. Geographical relations represent the spatial distribution dependencies between geospatial entities such as points, lines, and polygons, and the topologies among them. Geospatial relations play a very important role in describing the relations between geographic objects. These relations can be broadly classified as topological, directional, and proximity relations. These relations describe the adjacency and association relations between geospatial objects. An approach to identify an appropriate directional geospatial relationship between geo-objects present in high spatial resolution RS images is proposed in this paper. Geospatial objects in the form of the closed boundary are taken as input and relationship triplets are generated. Two approaches have been used in the identification of directional relationships and the results of both approaches are compared. The first approach is based on the centroid of the objects and the second considers whole objects while calculating the direction. These relations are then further represented using a knowledge graph, where nodes represent objects and edges represent their relationship. Knowledge graph plays a very important role in overall scene understanding. It shows the association of all objects with each other. These relationships are then represented in the form of descriptions by using template-based sentence generation. Results show that these directional relationships are accurately identified between each pair of objects using both approaches, but relations generated by considering whole objects are closer to human cognition. Semantic understanding of remote sensing images is of great significance in different applications such as urban surveys, urban planning, and management, military intelligence, etc. [ABSTRACT FROM AUTHOR]

The simulation of urban expansion has become an important means to assist urban development planning and ecological sustainable development. However, the spatial and temporal heterogeneities of urban expansion has been a major challenge for modelling urban expansion. This study designed three features from the perspective of spatiotemporal heterogeneity to improve the accuracy of CA model. The new features cover the trends effects of long time-series data on urban expansion, urban spatial growth intensity based on urban growth kernel estimation and allocation probability of the newly generated urban cells from global neighbourhood effects. Finally, urban expansion in Huizhou, China, was simulated and predicted. The experimental results show that the new features can effectively reduce the prediction error for the total amount of urban growth with a deviation of about 2%, and the overall accuracy of urban expansion is as high as 0.93. The features designed in this paper are shown to be effective and can be applied to urban simulations and scenario prediction with various models. [ABSTRACT FROM AUTHOR]

Transport data are important for understanding human mobility and urban interactions within a city. As China's transportation infrastructure continues to grow, more research is needed to analyse the spatial patterns of travel flows and to understand how these patterns change over time. With the development of online car-hailing and ride sharing services, floating car data have become a new resource to facilitate the analysis of human mobility patterns and the interactions of urban mobility within a city. The detection of urban communities based on urban networks is a helpful way to represent urban interactions. However, understanding community changes using online car-hailing data remains an underexplored topic. To this end, this study applies a community detection method to explore community changes over time based on the newly available floating car data (DiDi Chuxing ('DiDi')) in Chengdu, China. We applied undirected graphs to examine the spatial distribution of DiDi usage and the spatial patterns of travel distance. In addition, we explored the spatial-temporal variations of the communities at the taxi zone level using Blondel's iterative algorithm, a modularity optimization approach. Results suggest that: 1) taxi zones on the south and west sides of Chengdu have more average daily trips compared to those in other areas; 2) residential taxi zones in the northeast area have a long median travel distance, indicating people living in those areas travel longer distances; and 3) the detected community structures change at different times. These findings provide valuable information for urban planning and location-based services in Chengdu. [ABSTRACT FROM AUTHOR]

The provision of urban green spaces has been widely acknowledged to offer numerous benefits to individuals and communities. Recently, there has been a growing recognition of the importance of evaluating urban greenness from a human-centered perspective, partly due to the rapid development of eye-level greenness measurement. To provide a comprehensive overview of measurement approaches and topics related to eye-level urban greenness, we conducted a systematic review of 77 relevant papers. Our review revealed that street view images are the primarily utilized data source to quantify eye-level urban greenness in urban analysis. Additionally, simulated eye-level urban greenness represents a new frontier for the general public and urban planners, offering the potential to acquire universally applicable quantitative greenness data. Our findings further suggest that eye-level urban greenness has been explored across various domains, including physical behavior, public health, urban planning, human perception, and inequity. Such exploration has highlighted a significant association between eye-level urban greenness and individuals and communities. Our review generates new insights on the integration of urban greenness into urban planning and design, encouraging a greater focus on eye-level urban greenness as a critical component of urban environmental quality. [ABSTRACT FROM AUTHOR]

Urban population size dynamic adjustment has been widely studied for a long time; however, the dynamic adjustment at the urban hierarchy level remains unknown. This study utilises China's urban population data to investigate the dynamic adjustment. Specifically, we utilise methods of the Gini coefficient, linear regression, and coefficients of Spearman, and Moran's I to explore the dynamic adjustment tendency, adjustment rate and correlation of urban population size distribution of different urban hierarchies and groups of different urban hierarchies. We find that the urban population size spatial distribution is gradually even within the same urban hierarchy. The adjustment rate to be even of Megacity II is the highest, and Megacity I is the bottom. We also find the population size spatial distribution of the whole urban system is gradually uneven. We explore the dynamic process by sorting urban hierarchies into six groups. Furthermore, we find there is a complex correlation between different urban hierarchies and global spatial correlation among China cities. These results are valuable as references for Chinese policy-makers and practitioners and will enable them to adopt sustainable land use and urban population management measures. The study outcomes will also benefit future studies on spatial population size distribution in international communities. [ABSTRACT FROM AUTHOR]

The identification of city communities is essential for the regional planning and management of metropolitan areas. City communities could be identified from the perspective of mobile flows, and integrating the advantages of multisource flow data is essential to measure intercity connectivity. In this research, a multisource flow fusion method, which avoids the one-sidedness of a single flow, is proposed to combine the characteristics of population flow, traffic flow, and information flow. Moreover, the silhouette coefficient and hierarchical clustering algorithm are used to determine the number of city communities and the final clustering result. The results show that (1) although population flow, cargo flow, and information flow are positively correlated, there are also some differences among them; (2) the fusion flow between cities in China presents an obvious diamond structure, among which Beijing, Shanghai, Guangzhou, and Chengdu are the four points of the diamond, and Wuhan is located almost in the centre of the diamond structure; and (3) city communities are identified based on multisource flow and hierarchical clustering algorithm, which meet the principles that closely connected cities are in the same community and nonclosely connected cities are in different communities. [ABSTRACT FROM AUTHOR]

The network-constrained flow is defined as the movement between two locations along road networks, such as the residence-workplace flow of city dwellers. Among flow patterns, clustering (i.e. the origins and destinations are aggregated simultaneously) is one of the cities' most common and vital patterns, which assists in uncovering fundamental mobility trends. The existing methods for detecting the clustering pattern of network-constrained flows do not consider the impact of road network topology complexity on detection results. They may underestimate the flow clustering between networks of simple topology (roads with simpler shapes and fewer links, e.g. straight roads) but with high network intensity (i.e. flow number per network flow space), and determining the actual scale of an observed pattern remains challenging. This study develops a novel method, the length-squared L-function, to identify clustering patterns of network-constrained flows. We first use the L-function and its derivative to examine the clustering scales. Further, we calculate the local L-function to ascertain the locations of the clustering patterns. In synthetic and practical experiments, our method can identify flow clustering patterns of high intensities and reveal the residents' main travel behavior trends with taxi OD flows, providing more reasonable suggestions for urban planning. [ABSTRACT FROM AUTHOR]

The disruptions associated with health and energy crisis have emphasized the need for hyperlocal cities. However, in Europe, a tool to measure the efficiency of land use and accessibility planning for localizing urban mobility is missing. In this paper, we construct a comparable 15-Minute-Walking City (15-MWC) index that assesses the walking performance of 121 European metropolitan areas and seven amenity types. The data are combined equally following the PROMETHEE II multicriteria approach to assign a final score and to present a ranking of 15-Minutes cities. The main visualization demonstrates European-level disparities and indicates that most of leading cities are in Germany, while most of the worst performers are in the UK. We also reveal a statistically significant difference in 15-MWC performance due to their GDP per capita disparities. The empirical results may serve as a referencing tool for cross-city comparisons and may support policymakers when designing transport and city-planning strategies. [ABSTRACT FROM AUTHOR]

Radon gas from the ground is the main source of indoor concentrations in buildings, regardless of construction characteristics. According to Council Directive 2013/59/EURATOM, EU Member States must establish national reference levels for indoor radon concentrations in workplaces and draw up a National Radon Plan. In Calabria (Southern Italy), maps of indoor measurements at regional scale are not available. A set of 1434 average annual measurements, taken between 2010 and 2021, has been analysed. For a limited sector, a geostatistical approach allowed to map the expected concentrations at ground floor, the spatial uncertainty of estimates, and the probability of exceedance of the 300 Bq m−3 Italian threshold for workplaces. Highest values characterize the eastern border of the Sila massif. Obtained maps might be used to optimize locations of additional dosimeters, based on geological constraints. Such studies may support urban planning policies and provide recommendations on building techniques. [ABSTRACT FROM AUTHOR]

This article unites different disciplinary debates on 'southern innovation', 'theory from the South', and 'decolonisation of knowledge' in order to discuss existing understandings around the role of Africa in the production of health-related knowledge, public health policy, and medical innovation. Arguing that high-income countries have much to learn from the global South when it comes to health-related knowledge and practices, we propose an interdisciplinary research approach to uncovering and examining African contributions to global health, drawing on an ongoing collaborative project funded by the Swiss National Science Foundation. We present four empirical case studies concerning drug development, healthcare systems, and urban planning to critically enquire into both historical and contemporary transcontinental knowledge circulation and learning potentials, as much as cases of forgetting and silencing. On this basis, we argue that 'learning from the South' must mean more than transplanting quick and cheap technological fixes to serve societies in the global North, but rather recognising the vast contributions that Africans have made to global epistemologies, without losing sight of the asymmetries inherent in South–North knowledge exchanges. Lessons learned might apply to fields other than those discussed here and go far beyond 'reverse innovation'. [ABSTRACT FROM AUTHOR]

Remote sensing and deep learning are being widely combined in tasks such as urban planning and disaster prevention. However, due to interference occasioned by density, overlap, and coverage, the tiny object detection in remote sensing images has always been a difficult problem. Therefore, we propose a novel TO–YOLOX(Tiny Object–You Only Look Once) model. TO–YOLOX possesses a MiSo(Multiple-in-Single-out) feature fusion structure, which exhibits a spatial-shift structure, and the model balances positive and negative samples and enhances the information interaction pertaining to the local patch of remote sensing images. TO–YOLOX utilizes an adaptive IOU-T (Intersection Over Uni-Tiny) loss to enhance the localization accuracy of tiny objects, and it applies attention mechanism Group-CBAM (group-convolutional block attention module) to enhance the perception of tiny objects in remote sensing images. To verify the effectiveness and efficiency of TO–YOLOX, we utilized three aerial-photography tiny object detection datasets, namely VisDrone2021, Tiny Person, and DOTA–HBB, and the following mean average precision (mAP) values were recorded, respectively: 45.31% (+10.03%), 28.9% (+9.36%), and 63.02% (+9.62%). With respect to recognizing tiny objects, TO–YOLOX exhibits a stronger ability compared with Faster R-CNN, RetinaNet, YOLOv5, YOLOv6, YOLOv7, and YOLOX, and the proposed model exhibits fast computation. [ABSTRACT FROM AUTHOR]

The local climate zone (LCZ) scheme has been widely utilized in regional climate modeling, urban planning, and thermal comfort investigations. However, existing LCZ classification methods face challenges in characterizing complex urban structures and human activities involving local climatic environments. In this study, we proposed a novel LCZ mapping method that fully uses space-borne multi-view and diurnal observations, i.e. daytime Ziyuan-3 stereo imageries (2.1 m) and Luojia-1 nighttime light (NTL) data (130 m). Firstly, we performed land cover classification using multiple machine learning methods (i.e. random forest (RF) and XGBoost algorithms) and various features (i.e. spectral, textural, multi-view features, 3D urban structure parameters (USPs), and NTL). In addition, we developed a set of new cumulative elevation indexes to improve building roughness assessments. The indexes can estimate building roughness directly from fused point clouds generated by both along- and across-track modes. Finally, based on the land cover and building roughness results, we extracted 2D and 3D USPs for different land covers and used multi-classifiers to perform LCZ mapping. The results for Beijing, China, show that our method yielded satisfactory accuracy for LCZ mapping, with an overall accuracy (OA) of 90.46%. The overall accuracy of land cover classification using 3D USPs generated from both along- and across-track modes increased by 4.66%, compared to that of using the single along-track mode. Additionally, the OA value of LCZ mapping using 2D and 3D USPs (88.18%) achieved a better result than using only 2D USPs (83.83%). The use of NTL data increased the classification accuracy of LCZs E (bare rock or paved) and F (bare soil or sand) by 6.54% and 3.94%, respectively. The refined LCZ classification achieved through this study will not only contribute to more accurate regional climate modeling but also provide valuable guidance for urban planning initiatives aimed at enhancing thermal comfort and overall livability in urban areas. Ultimately, this study paves the way for more comprehensive and effective strategies in addressing the challenges posed by urban microclimates. [ABSTRACT FROM AUTHOR]

This study explores the impact of street pattern measurements on urban heat islands (UHI) in the arid climate of Mashhad, Iran. The Landsat-8 top-of-the-atmosphere (TOA) brightness images from 2013 to 2021, average values of normalized difference vegetation index (NDVI) and land surface temperature (LST) were calculated. Street pattern measurements, including closeness-centrality, straightness, and street orientation, were employed to analyse the patterns in each district. The results indicated that districts with higher straightness and lower closeness-centrality exhibit cooler surface temperatures. Strong correlations were observed between LST and NDVI, straightness, and local closeness-centrality. The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions. A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably. Street pattern indexes, such as straightness and local closeness-centrality, are identified as significant factors in urban design to mitigate UHI. These findings have implications for urban planners, who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness. [ABSTRACT FROM AUTHOR]

This study addresses a crucial gap in our understanding of flooding in the predominantly agricultural Qaa'Jahran watershed in Yemen, where urbanization, though currently limited in extent, is rapidly expanding. We aim to discern the effects of earth fissures on flood dynamics, particularly focusing on their present significance. It is noteworthy that, in the long run, these fissures are anticipated to accumulate soil and sediment, potentially heightening the risk of future flooding. To achieve this, we developed a comprehensive floodplain delineation model, incorporating field observations and rainfall data from the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm. Additionally, advanced hydrologic and hydraulic models were integrated to accurately simulate runoff hydrographs and create flood inundation maps. Our findings underscore the considerable influence of earth fissures, effectively mitigating runoff volume, peak discharge, flood depths and inundated areas during storm events. It is imperative to emphasize that specific areas remain persistently vulnerable, with water levels surpassing one meter during historical floods. This reinforces the ongoing risk of flooding in targeted zones and emphasizes the necessity of implementing tailored flood management strategies. In conclusion, this study makes a significant contribution to the field, providing a comprehensive analysis of the intricate factors influencing flooding in the Qaa'Jahran watershed. The integration of flood inundation mapping, advanced hydrologic modelling and meticulous consideration of earth fissures offers a distinctive perspective on flood dynamics in a rapidly evolving and urbanizing environment. Furthermore, it highlights the critical implications for effective flood risk management and urban planning, not only in the Qaa'Jahran watershed but also in similar urbanizing regions worldwide. [ABSTRACT FROM AUTHOR]

Predicting future urban land-use scenarios and assessing their encroachment on ecological land is important for sustainability policy formulation. This study develops a new Futureland model using cellular automata with user-defined transformation rules, graphical neighborhood configuration and matrixed transformation cost to simulate multiple land-use changes. Compared with existing models, Futureland applies different factors to different land-use types in a single simulation experiment. Futureland was developed using Geospatial Data Abstraction Library and parallel computing, which significantly improve the implementation efficiency. The case study of Shanghai 2010–2020 illustrates an overall accuracy of 86.6% and a Kappa simulation of 0.79. The land-use scenarios for 2020–2035 were projected under greenspace planning constraints using Futureland. The results indicate that Shanghai's urban sprawl will gradually slow down by 2030, and the increased urban areas will be mainly in the urban fringes and suburban regions. Futureland can help decision-makers to manage future land-use and optimize urban planning policies. [ABSTRACT FROM AUTHOR]

Obtaining high-precision information on functional areas is very important in urban spatial management. It has become common to integrate social perception data and high-resolution remote sensing images to identify functional areas. Based on Point of Interest (POI) data, a scoring evaluation model is constructed to identify functional zones in built-up areas. Two weight values in the model, the POI area weight and normalized kernel density value, are used in the calculation of the impact score. Functional areas are identified by the proportion of the influence score associated with each function type. The information corresponding to 10 first-level and 29 s-level functional areas is obtained by integrating the classification results for natural attributes in high-resolution images and the social attribute functional areas in the scoring evaluation model. The overall accuracy is 87.2%, and the kappa coefficient is 0.86. The spatial structure characteristics of functional areas are analyzed based on spatial syntax, the location entropy index and so on. The main functions of each street core area and high-selectivity area are consistent with the function types, are associated with high location entropy index values and coincide with distribution centres with various functions. This study is conducive to enhancing urban spatial planning, management and decision support. [ABSTRACT FROM AUTHOR]

Water stress is an everyday issue in developing countries and especially in Foumban, a municipality located in the West Region of Cameroon between longitudes 10°40'-11°10'E and latitudes 05°30'-05°55'N. The failure of the water distribution system in the Municipality of Foumban (MoF) led the citizens as well as the municipal authorities to exploit groundwater. Unfortunately, an extensive hydrogeophysical field campaign, with incidental cost, is required because the groundwater potential is not priorly assessed. The main objective of this article is to demarcate groundwater potential zones of MoF. For this, six thematic layers contributing to groundwater occurrences are combined using analytical hierarchy process (AHP) on a GIS environment to produce a sound groundwater potential map. This map is classified into three zones: low potential for 39.06%, acceptable potential for 27.27% and high potential for 33.68% of the study area. This may help to increase the rate of productive wells (by focusing hydrogeophysical investigation on areas with high groundwater potential) using little financial resources. [ABSTRACT FROM AUTHOR]

An underlying factor with the problems of trip making in urban areas is related to the land use potentials and the condition of its transport system. The land use pattern of any settlement is the basis for its physical planning, especially in rapidly growing cities. This study examines land use and households' trip in selected cities of Osun State, Nigeria. Data were obtained for the pattern of land uses. Data were also randomly obtained from 2,134 households to examine their trip pattern. Descriptive statistics was used to analyse land use pattern, while correlation analysis was used to examine relationship between land use and households' trip pattern. Findings revealed that all the cities studied possessed characteristics of mixed land use. The study shows that 57.15% of the land use is for residential while non-residential accounted for 42.85%. Further, households made an average of 27 trips per week and travelled an average of 10.65kilometres per day in the selected cities. Results from correlation analysis indicated that there is low positive correlation between residential land use and trip frequency (r = 0.302) as well as distance travel (r = 0.222). Further, with correlation coefficient (r) of 0.613 and 0.559, there is strong positive correlation between non-residential land use and trip frequency as well as distance traveled by the household. The study recommends holistic urban planning to reduce future urban land use problems that may lead cities into a chaotic situation. [ABSTRACT FROM AUTHOR]

The preparation of urban development plans and their implementation for urban development in the Global South are often not treated as projects, despite the time, cost and other resource implications. Urban development plan preparation and implementation often overrun their schedule, and cost and at times become uncertain. So, an argument has emerged that plan preparation and implementation should be managed by the use of project management principles. Thus, the objective of the study was to explore the challenges in the preparation of urban plans and their implementation and how project management as an anti-planning measure can improve efficiency in these aspects. A Delphi research method involving surveys among urban planning and project management professionals and experts was used. Findings suggest that the preparation of plans and implementation suffer from several challenges under the conventional process. However, project management can become an anti-planning measure and enable the preparation of plans and implementation efficiently. As advocated by anti-planning, it can enable keeping a journal of the occurrences regularly which would allow diagnosis of the challenges and to take appropriate remedial interventions. Practically, it can enable controlling the schedule, cost, and resources and eliminate uncertainty in urban planning and implementation. [ABSTRACT FROM AUTHOR]

This research aims to develop mitigation techniques for the implications that affect the city planning sectors in Egypt during COVID-19, which will guide urban planners and policymakers to enhance Egyptian citizen life during pandemics. A statistical thematic methodology was adopted by the research. The research method divided into three phases. The first phase considers the attitude of Egyptian citizens toward the global pandemic through conducting surveys. These surveys discuss the global effects of the pandemic and if these effects are felt in the Egyptian context or not. The second phase targets the citizen that disagree with the global effects as a result of the phase one survey through structured interviews. These interviews concluded the reasons behind the disagreement of the surveys in phase one as well as the effects that they personally suffer from during the pandemic. The third phase targets the policymakers and planners inside Egypt and their perspectives on the suitable mitigation techniques that can be implemented in the Egyptian context. This will finally lead to suggesting a set of mitigation techniques suitable for Egyptian cities. The research paper identified through a review of literature the mostly affected city planning sectors during COVID-19 which were 6 sectors. In addition, 25 global mitigation measures were identified through the literature. Results of the Surveys and structured interviews confirmed that the most affected sectors are transport & land use, housing, and ICT respectively. Findings of data analysis showed that 10 extra mitigation measures were encountered to better enhance the Egyptian cities. These findings help planners and policy makers to plan cities that can cope with future pandemics. This research presents mitigation techniques for the implications that affect the city planning sectors in Egypt during COVID-19. It was based on research from case studies, a literature review, and a survey questionnaire. The mitigation techniques developed in a practical procedure where the goals of the research; required activities; techniques, and tools; elaborated the citizen needs and outputs. The mitigation techniques was authenticated by 24 of the Egyptian professionals' planners and policy makers to ensure its viability and practicability for implementation. The research categorized and examined the global effects that changed the quality of life during pandemics. Moreover, real life case study authenticated the global effects and explored the most successful mitigation countermeasures that suites the Egyptian context. The study focused on a subject that has recently attracted interest on a global scale. In addition, this paper developed 10 extra mitigation measures to better enhance the Egyptian cities and other developing countries of similar context. It represents a novel contribution that planners and policy makers can employ in similar context to the Egyptian cities. [ABSTRACT FROM AUTHOR]

Land Cover or Land Use (LCLU) classification is an important, challenging problem in remote sensing (RS) images. RS image classification is a recent technology used to extract hidden information from remotely sensed images in the observed earth environment. This classification is essential for sustainable development in agricultural decisions and urban planning using deep learning (DL) methods. DL gets more attention for accuracy and performance improvements in large datasets. This paper is aimed to apply one of the DL methods called transfer learning (TL). TL is the recent research problem in machine learning and DL approaches for image classification. DL consumes much time for training when starting from scratch. This problem could be overcome in the TL modeling technique, which uses pre-trained models to build deep TL models efficiently. We applied the TL model using bottleneck feature extraction from the pre-trained models: InceptionV3, Resnet50V2, and VGG19 to LCLU classification in the UC Merced dataset. With these experiments, the TL model has been built the outdate performance of 92.46, 94.38, and 99.64 in Resnet50V2, InceptionV3, and VGG19, respectively. [ABSTRACT FROM AUTHOR]

This research merges individual self-reported physical-activity data from the fifth wave of the Indonesia Family Life Survey (IFLS) with data on Indonesian cities' and municipalities' built environments and employs cross-sectional multilevel regression to disentangle the relevant factors that affect individual incentives to engage in physical activity. The results suggest that high-density settings and land-use diversity in Indonesian urban settings adversely affect the incentive to engage in physical activity. Our finding reflects the common case of developing countries where the main problem arises from insufficient urban planning, which further results in other issues such as conventional land use and low-level safety and security. Thus, the result implies the urgency to improve built-environment planning in Indonesia to create a more supportive living environment that encourages residents to be more physically active, hence creating a healthier society. [ABSTRACT FROM AUTHOR]

African urban areas and cities are primarily seen as vulnerable to climate change. Apparent attempts to get required policies have led to the widespread proliferation of overlapping and duplications of policies. Using a policy coherence framework, this study aims to synthesise the coherency of climate adaptation and urban policies in Ghana. The study used content analysis of existing policy documents to understand if specific variables are explicit, implicit or not mentioned in four urban and climate change policies in Ghana. It was found that there is a minimal degree of coherence only in the adaptation measures, but there is a general lack of coherence in the motivation and implementation. This can be attributed to radically different current institutional arrangements for urban planning and climate change, inconsistent use of data and terminologies, and lack of embracement of innovations in urban planning in African cities. The findings suggest that attention must be given to integrated collaborative adaptation planning to address these impediments in urban planning context of African cities. [ABSTRACT FROM AUTHOR]

Based on a case study of Alexandria city, Egypt, this paper investigates the configuration, interrelation, and integration of urban expansion within the framework of sustainability transitions to enhance the performance of sociotechnical transitions. It explores two main arguments; first, to evaluate the recent urban planning innovations, and second, to raise awareness of the participatory planning model to enhance the involvement of the three pillars to better integrate urban sustainable development. It presumes there is a linkage between urban sustainability transitions and the geographical transitions. It further evaluates whether this linkage would benefit accommodating the rapid population growth of Alexandria. This research applies an empirical methodology to test concepts and patterns known from theory generating three scenarios from empirical data. Moving beyond the 'niche–regime dichotomy', this study concludes that innovative practices and vested interests are typically constituted in a dualistic manner and tend to incite processes of change in both. [ABSTRACT FROM AUTHOR]

In Luanda maybe more than elsewhere, controlling the city landscape is synonymous with controlling the polity at large. Despite a tremendous political change in Angola during the twentieth century, the paper traces how the modernist plans elaborated in the late colonial period (1945–1975) have influenced the planning imagination of Luanda until today. It argues that the construction boom that reshaped Luanda at the end of the war in 2002 can be interpreted as a modernist promise to break the middle class free from a hopeless urban fabric by promoting a specific urban aesthetic rather than facilitating social transformation. These continuities are, however, complex and fragile. What happens when the utopia of a city under control starts to lose power? Reflecting on two urban projects built around half a century apart, this paper explores how the kinesthetic experience of the city might constitute an unexpected form of ideological dissent able to disrupt modernism at large. The trajectory of Kilamba City, in particular, is the epitome of the oil-fed reconstruction frenzy of the late 2000s that brutally ended in 2014. Looking at how residents, planners and even state media relate to this project suggests that the unsustainability of a utopian suburban life eventually triggers new political subjectivities and directly challenges the modernist ideology that endured for so long. [ABSTRACT FROM AUTHOR]

At a time when the world is critical of the Brazilian government and the loss of Amazonian rainforest, Brian J. Godfrey casts his 40-year gaze on Rio de Janeiro. Geographer Godfrey deftly uses various scales of analysis - global, hemispheric, national, regional, metropolitan, and neighborhood - to point out how memory can be used to reinvent places both in Rio and elsewhere. Godfrey's real nugget is chapter 3's examination of Little Africa in Rio. [Extracted from the article]

With the emergence of new forms of geospatial/urban big data and advanced spatial analytics and machine learning methods, new patterns and phenomena can be explored and discovered in our cities and societies. In this special issue, we presented an overview of nine studies to understand how to use urban data science and GIS in healthcare services, hospitality and safety, transportation and mobility, economy, urban planning, higher education, and natural disasters, spreading across developed countries in North America and Europe, as well as Global South areas in Asia and the Middle East. The embrace of diverse geo-computational methods in this special issue brings forward an outlook to future GIS and Urban Data Science towards more advanced computational capability, global vision and urban-focused research. [ABSTRACT FROM AUTHOR]

Studying the structure of polycentric cities can promote a better understanding of urban development and contribute to urban planning. In this study, we identified polycentric cities in China and evaluated the urban centre development level of polycentric cities from new data and method. We used Luojia-1A night-time light (NTL) data, combined with the concept of natural cities (NCs), to identify urban centres and thus identify polycentric cities in China. In addition, we used the urban centre development index (UCDI) to quantify the urban centre development level (UCDL) that represents the overall urban centre development level within a polycentric city. The polycentric cities in China are characterized by the spatial distribution pattern of a larger number in the east and fewer in the west. There are a large number of polycentric cities in eastern China, and the closer to the coastal areas, the more polycentric cities there are. The distribution of UCDL in China's polycentric cities is characterized by significant spatial heterogeneity. UCDLs are generally smaller in polycentric cities in western China. In addition, polycentric cities in northeastern China have smaller UCDL. Polycentric cities with high UCDL are concentrated in the central and coastal regions of China. [ABSTRACT FROM AUTHOR]

HIA implementation has rapidly grown in France. The question arises as to whether such growth is paving the way towards institutionalisation. An analytical framework was built based on the literature, capturing key dimensions characterising HIA practice and institutionalisation. Collected data draw upon documented HIAs, evaluation reports, direct observations and workshops. HIA practice in France follows a stand-alone procedure and is based on a holistic model of health. Its largely concerns intermediate HIAs commissioned by municipalities with the support of regional health authorities. Mainly applied to urban planning, HIAs are usually conducted by private firms, and local health observatories. Levers of institutionalisation include: an enduring tradition of intersectoral collaborations for health; a growing culture of health promotion; supportive environmental regulatory requirements; and policy frameworks and mandates addressing health inequalities at a regional and municipal level. For HIA to be more institutionalised, there is a need to clarify its purpose, continue building capacity, promote impact evaluations for evidence on HIA' potential to advance HiAP and obtain greater commitment from national authorities. [ABSTRACT FROM AUTHOR]

The use of quantitative analysis and related metrics has traditionally been unusual for assessment of ecological impacts in urban planning. Since 2010, however, quantitative modelling has been increasingly used in such contexts in Sweden to analyze ecological connectivity. The study reviews and analyses 21 connectivity analysis reports (CAR) based on 17 criteria. Despite the use of quantitative analysis, CARs primarily leverage qualitative aspects of modelling results. Most CARs comply with about 50% of the proposed criteria and close to 90% of the reports fail to address some issues related to modelling transparency and therefore jeopardize an adequate ecological interpretation of the results. The results demonstrate that the primary accomplishment during the last decade is an increase in awareness and acceptance of ecological connectivity among practitioners and decisionmakers. Results point to that an increased use of quantitative methods per se will not deliver more sustainable outcomes, and that an increased use of quantitative methods for ecological impact assessment in urban planning needs to be accompanied by guidelines, standards, and a continuous science – practice knowledge exchange. [ABSTRACT FROM AUTHOR]

The third or organismic view of space states that space is neither lifeless nor neutral, but a living structure capable of being more living or less living, thus different fundamentally from the first two mechanistic views of space: Newtonian absolute space and Leibnizian relational space. The living structure is defined as a physical and mathematical structure or simply characterized by the recurring notion (or inherent hierarchy) of far more small substructures than large ones. This paper seeks to lay out a new geography as a science of the Earth's surface founded on the third view of space. The new geography aims not only to better understand geographic forms and processes but also – maybe more importantly – to make geographic space or the Earth's surface to be living or more living. After introducing two fundamental laws of geography: Tobler's law on spatial dependence (or homogeneity) and scaling law on spatial heterogeneity, we argue that these two laws are fundamental laws of living structure that favour statistics over exactitude, because the former (or statistics) tends to make a structure more living than the latter (or exactitude). We present the concept of living structure through some working examples and make it clear how a living structure differs from a non-living structure, under the organismic worldview that was first conceived by the British philosopher Alfred Whitehead (1861–1947). In order to make a structure or space living or more living, we illustrate two design principles – differentiation and adaptation – using two paintings and two city plans. The new geography is a science of living structure, dealing with a wide range of scales, from the smallest scale of ornaments on walls to the scale of the entire Earth's surface. [ABSTRACT FROM AUTHOR]

Ground motion modification over large areas is generally evaluated by focusing on source effects disregarding local lithostratigraphic site conditions. Hence, amplification maps of peak ground acceleration and peak ground velocity are proposed to improve the forecast of ground motion on a national scale. Topological information about litho-type successions and soil mechanical behaviour were retrieved from the Italian database of seismic microzonation and more than 30 million of seismic site response analyses were performed to quantify the amplification factors (i.e. the ratio between expected ground motion at the site of interest and that at the outcropping engineering bedrock). The maximum value of the amplified peak ground acceleration on the Italian territory results in about twice as much as the value expected at the outcropping of the engineering bedrock. Finally, damage scenario maps based on the amplified ground motion could be produced as a supporting tool for urban planning and emergency system management. [ABSTRACT FROM AUTHOR]

As the electronic process of land management is accelerating, the research on the construction of land use planning system tends to be intensified. This paper combines the concept of traditional farming culture to construct a rural land planning system, and proposes a stacked combination collaborative filtering recommendation algorithm to process traditional farming cultural data and promote the integration of traditional farming cultural data and rural land planning data. Moreover, starting from the existing problems in urban land planning at this stage, this paper proposes the rationality and importance of the land use planning system, and at the same time guarantees that it can be used in a standardised and scientific way. In addition, after explaining the construction purpose of the land use planning system, this paper also explains the tasks, design and corresponding steps to be completed to construct the system. Finally, this paper verifies the performance of this system through experimental research. Through the experimental results, we can see that the method proposed in this paper has a certain effect. [ABSTRACT FROM AUTHOR]

The provision of urban green spaces (UGS) within a reasonable walking distance/time for each resident has become a major challenge of urban planning. We provide a novel method to map the availability of UGS for different socio-economic groups in cities using a demand–supply composite index (DSCI). Budapest, the capital city of Hungary, has been chosen to test how the DSCI works. The results show significant differences in the availability of UGS for people living in different neighborhood types. Furthermore, findings reveal that regardless of which type of residential area is considered, young and middle-aged people with higher per capita income are more likely to access UGS. As the demographic and socio-economic structure of the population is continuously changing in the different neighborhood types and so is the demand for UGS, urban planners should carefully monitor societal changes and elaborate interventions to help improve the availability and accessibility of UGS. [ABSTRACT FROM AUTHOR]

Social Impact Assessment (SIA) facilitates sustainable and equitable consideration of social issues in transport infrastructure planning. However, SIA practitioners face significant constraints in practice. Good SIA is effective in contributing to institutional mechanisms for holding political, bureaucratic and commercial processes accountable for social outcomes. This paper aims to better understand constraints to the assessment and management of social impacts. Drawing on interviews with expert infrastructure professionals involved in projects in Sydney (Australia), Amsterdam (The Netherlands), and internationally, this paper highlights weaknesses in the implementation of SIA, technical engineering-, time- and cost-focused project management practices, and poorly regulated, politically-driven urban governance and planning processes as key constraints. The findings suggest that overcoming those constraints cannot be the sole responsibility of EIA and SIA practitioners and there is more to be considered than practice alone. Instead, this requires an integrated approach across multi-level governance scales and the lifecycle of projects. This paper concludes that for good practice SIA to be realised as intended, systemic adjustments are needed in the planning of urban transport infrastructure, to address constraints and ensure that social impacts are considered in strategic stages and prioritised equally against other project and urban planning issues in decision-making. [ABSTRACT FROM AUTHOR]

Urban Functional Zone (UFZ) identification is vital for urban planning, renewal, and development. Point of Interest (POI), as one of the most popular data in UFZ studies, is transformed into a geo-corpus under specific sampling strategies, which can be used with Natural Language Processing (NLP) technology to extract geo-semantic features and identify UFZs. However, existing studies only capture a single spatial distribution pattern of POIs, while ignoring the other spatial distribution information. In this paper, we developed an integrated geo-corpus construction approach to capture multi-spatial distribution patterns of POIs that were represented by different modal POI embeddings. Subsequently, random forest model was leveraged to classify UFZs based on those embeddings. A set of combination experiments were designed for performance validation. The results show that our proposed method can effectively identify UFZs with an accuracy of 72.9%, with an improvement of 8.5% compared to the baseline methods. The outcome of this study will help urban planners to better understand UFZs through investigating the integrated spatial distribution patterns of POIs embedded in UFZs. [ABSTRACT FROM AUTHOR]

The accurate prediction of population distribution is crucial for numerous applications, from urban planning to epidemiological modelling. Using one-week data collected from open and multiple sources, including telecommunication activity, weather, point of interest, buildings, roads, and land use in Milan, Italy, we develop a hybrid method combining cellular automata (CA) and long short-term memory (LSTM) to predict population distribution with fine temporal and spatial granularity. Specifically, the convolutional autoencoder and LightGBM are applied to identify missing building types based on the pedestrian shed. The LSTM learns the transition rules of CA and Shapley additive explanations value is used for variable importance analysis. Results demonstrate that the combination of convolutional autoencoder and LightGBM is effective in building type prediction. The proposed model for population distribution prediction outperforms LSTM, the combination of CA and neural network, and the combination of CA and LightGBM by at least 5–10%. A variable importance analysis reveals that temporal variables are the most significant for prediction, followed by spatial and natural variables. The order of hour, housing-related variables, and types of precipitation are the most important variables in each category. [ABSTRACT FROM AUTHOR]

The dynamic population distributions by activity type (e.g. working, shopping or in-home) are vital for resource allocation, urban planning and epidemic containment. Although studies have incorporated individual-level human mobility data to map population distribution by activity type, access to such data is hindered due to privacy issues and they rely on auxiliary data to provide priori activity knowledge. This paper presents a method for generating the population dynamics by activity type. We first introduce more readily available sequential snapshot data to construct the population mixture model, then decompose the population mixture, and finally estimate the dynamic population size for each activity. We test the method in the central districts of Guangzhou city, China, based on real-time Tencent user density data. Correlation analysis and accuracy assessment prove that our method can accurately estimate hourly distributions for populations engaging in working, stay-at-home, and socializing activities. The temporal distribution of the working population reproduces the regular work scenarios and socializing population displays complex spatial patterns. We also find that there is an underlying relationship between a region's function and its dynamic population structure. The presented method has great potential for application and could provide new insight for studying urban dynamic functions. [ABSTRACT FROM AUTHOR]

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

As a significant part of sustainable urban development proposed by the United Nations, urban planning is related to the ecological environment and transportation, especially affecting quality of life and social well-being. In the process of urban planning, the public express their opinions on open network platforms, resulting in large quantities of network public opinion data, which has important implications for evaluating urban planning. Based on the idea of geographical case-based reasoning (CBR), this paper constructs an expression framework for urban planning cases in the form of a 'case problem–case attribute–case result' triad. On this basis, this paper proposes a similarity calculation method of urban planning cases that integrates case attribute. Finally, based on an improvement to the traditional k-nearest neighbors method, the proposed public opinion feature calculation model considers similarity weights, which allow us to predict network public opinion features, including viewpoint-level emotional tendency and concerned groups of urban planning cases. The experimental result shows similarity weights (SWs) model could effectively improve the prediction accuracy, where the average MIC-F1 score reached more than 74%. Based on CBR, the proposed method can predict the development trends of public opinion in future planning cases, and provide scientific and reasonable decision support for urban planning. [ABSTRACT FROM AUTHOR]

Virtual geographical environments (VGEs) are being used to represent our sense of place through the application of extended-reality or cross-reality (XR) technologies with a focus on technological advancement and immersion. In light of this, we propose that an expanded and interdisciplinary understanding of the concept of immersion is required to facilitate an understanding of spatial data to a broader audience. The potential of focusing on narrative immersion and literary placemaking in VGEs is discussed to evoke a stronger sense of place and a feeling of presence and belonging in users. This paper seeks to highlight the unique affordances and potentialities of XR narrative style GIS digital representations through an interdisciplinary theoretically lead analysis of outputs created by the Building City dashboards project towards the goal of expanding audiences of non-specialist stakeholders in urban planning processes. [ABSTRACT FROM AUTHOR]

Public medical facilities that are closely related to the health of residents have been recognised as one of the most crucial elements in sustainable urban planning. For the sake of social equality of medical services (especially for emergency medical conditions), the spatial distributions of medical resources need to be accurately measured and continuously optimized. This study presents an effective method to examine night emergency hospital visit and analyse its spatiotemporal characteristics using float car data (FCD). By extracting the hospital service areas, the two-step floating catchment area (2SFCA) methodology was improved to calculate hospital accessibility. Then, the balance between hospital accessibility and population density was analysed. In addition, we investigated the relationship between individual hospital choice preferences and hospital level and analysed several factors that affect individual choices. These results help us understand the special requirements and need of emergency hospital travel in cities and identify areas where medical resources are scarce. They can be used as guidance for urban hospital planning and construction. And the approach of hospital access behaviour investigation and the improved 2SFCA method can also provide insights for other activity-based travel behaviour research. [ABSTRACT FROM AUTHOR]

The article tried to study the public transport role as one of the means that contribute to sustainable urban development by investigating the effect of the coverage rate for public transport on the number of those who use public transport in the neighbourhoods of Kut city. This article investigates the link between public transportation and supportive urban design trends. The research spatial and tem- poral limits are represented by the municipal boundaries Al-Kut city, which are shown in the master plan of the city for the period 2008–2012. The results showed a positive but weak relationship between public transport (variable factor) and the proportion of public transport coverage and population density (independent fac- tors). These factors do not explain the apparent, which is confirmed by the high Bo value and its great reliability, and this result is inconsistent with the hypothesis that states a positive effect between public transport and the coverage rate. However, this relationship is abnormal and indicates an imbalance in the distribution of land uses and the provision of services in the structure of Kut city. Furthermore, it is a negative indicator of the city’s structure, where a good and efficient structure requires a strong relationship. As for public transport passengers, they seem to be restricted by this for poor services. [ABSTRACT FROM AUTHOR]