This article is an effort to scrutinize the role of Information Technology development in the chronological transformation of Urban Planning domain using the exploratory research approach. In this research, it is argued that the theoretical and practical understanding of Urban Planning should absorb and integrate the bright outcome of the rise of Information and Technology to foster congruent future urban development. The article addresses the trends of transformation in the urban planning domain through the myopic lens of the expansion of information and communications technology era followed by investigating the key drivers shaping the interaction between modern-day urban planning and information technology considering both the dark and bright sides into account.

Public participation is crucial in the process of urban governance in smart-city initiatives to enable urban planners and policy makers to take account of the real public needs. Our study aims to develop an analytical framework using citizen-centred qualitative data to analyse urban problems and identify the areas most needed for urban governance. Taking a Chinese megacity as the study area, we first utilise a web-crawling tool to retrieve public comments from an online comment board and employ the Baidu Application Programming Interfaces and a qualitative content analysis for data reclassification. We then analyse the urban problems reflected by negative comments in terms of their statistical and spatial distribution, and the associative factors to explain their formation. Our findings show that urban problems are dominantly related to construction and housing, and most frequently appear in industry-oriented areas and newly-developed economic development zones on the urban fringe, where the reconciling of government-centered governance and private governance by real estate developers and property management companies are most needed. Areas with higher land price and a higher proportion of aged population tend to have less urban problems, while various types of civil facilities affect the prevalence of urban problems differently.

Information and Communication Technology (ICT) is at the heart of the Smart City approach, which constitutes the next level of cities’ and communities’ development across the globe. Thereby, ICT serves as the gluing component enabling different domains to interact with each other and facilitating the management and processing of vast amounts of data and information towards intelligently steering the cities infrastructure and processes, engaging the citizens and facilitating new services and applications on various aspects of urban life - e.g. supply chains, mobility, transportation, energy, citizens’ participation, public safety, interactions between citizens and the public administration, water management, parking and many other use cases and domains. Hence, given the fundamental role of ICT in cities in the near future, it is of paramount importance to lay the ground for a sustainable and reliable ICT infrastructure, which can enable a city/community to respond in a resilient way to upcoming challenges whilst increasing the quality of life for its citizens. This paper constitutes a continuation of a series of research documents and standardization activities, which relate to the concept of Open Urban Platforms (OUP) and the way they serve as a blueprint for each city/community towards the establishment of an ICT backbone. Thereby, the current paper emphasizes on the aspects of sustainability and resilient ICT, whilst reporting on our latest activities and related developments in the research area.

Intelligent cities or smart cities evolve bottom-up along with the digitisation and the creation of digital entities linked to human activities, physical space, and institutional settings of cities; but also, they progress top-down through smart city strategies and projects designed and implemented by public authorities. Yet, thirty-five years since the first use of the term “smart city” or “intelligent city” in the second half of the 1980s, and more than ten years of intense publications in this field, since 2009, there is still a great deal of fuzziness about the projects that make cities intelligent or smart. There is low awareness about the big differences between large, complex urban projects, such as ‘Zero Energy Districts’ or “Mobility-as-a-Service” and projects for automation of city infrastructures, such as smart city lighting, smart metering or finding a parking place. There is a widespread misconception that city intelligence or smartness, the core attribute of smart cities, can be achieved through automation of the city infrastructure. This paper focuses on projects that make cities intelligent or smart. Our intention is to show the complexity and effort needed to achieve this objective. It is an inquiry on projects and data from a large number of smart cities around the world. We analyse core properties of smart city projects, such as (a) interventions on the physical, social, and digital space of cities, (b) the relation to city sectors and ecosystems, (c) engagement of users and stakeholders in decision-making, and (c) impact through optimisation and innovation of city processes and routines. We discuss also projects we have designed and implemented in the framework of URENIO Research and ITI-CERTH. Our conclusions are two-fold. First, we propose a typology of smart city projects along 3 axes and 9 properties. Second, we argue that success and failure to achieve city smartness are mainly institutional. Most barriers to implementation are organisational, legal, and institutional. This can be explained by the social and institutional inertia of the urban system against new solutions, especially when innovation and radical change of existing routines take place. Change management should be a permanent companion of smart city projects implementation, and the modification of routines should be clearly defined and considered already at the design phase of projects.

Considering citizens' perceptions of their living environment is very helpful in making the right decisions for city planners who intend to build a sustainable society. Mental map analyses are widely used in understanding the level of perception of individuals regarding the surrounding environment. The present study introduces Aram Mental Map Analyzer (AMMA), an open-source program, which allows researchers to use special features and new analytical methods to receive outputs in numerical data and analytical maps with greater accuracy and speed. AMMA performance is contingent upon two principles of accuracy and complexity, the accuracy of the program is measured by Accuracy Placed Landmarks (APL) and General Orientation (GO), which respectively analyses the landmark placement accuracy and the main route mapping accuracy. Also, the complexity section is examined through two analyses Cell Percentage (CP) and General Structure (GS), which calculates the complexity of citizens’ perception of space based on the criteria derived from previous studies. AMMA examines all the dimensions and features of the graphic maps, and its outputs have a wide range of valid and differentiated information, which is tailored to the research and information subject matter that is required.

Intense climate change and rapid urbanization have increased the risk of urban flooding, seriously affecting urban economic and social stability. Enhancing the urban flood resilience (UFR) has required a new solution to cope with urban flood disasters. In this study, taking Yingtan city as an example, a system of indicators for evaluating UFR was constructed, with 17 representative indicators, comprising three subsystems: socio-economic, ecological and infrastructural. A hybrid (FAHP-EWM)-TOPSIS model was applied, to develop an index-based measurement to compare and evaluate UFR, and Gray Relational Analysis (GRA) was used to discover the main factors affecting UFR. In addition, the natural discontinuous method was innovatively used to divide the UFR grade interval into levels, and the grade change was evaluated based on the TOPSIS method. The results showed that (1) from 2010 to 2022, the UFR in Yingtan City increased by 80.69%, and the factors affecting UFR are highly correlated with urban infrastructure development. However, the ecological resilience in the subsystem showed a fluctuating downward trend, because of the influence of the surface area of lakes and rivers. (2) The grades of UFR for Yingtan City increased from Level III (2010 and 2016) to Level IV (2022), with local financial expenditures and the age structure of the population being the main factors currently limiting the development of UFR. The study provides a theoretical basis for the construction of an indicator system for assessing the UFR of Yingtan and proposes practical improvement directions for UFR.

As the world’s second largest economy, China ranks amount the world’s top nations when it comes to carbon emission, and therefore its attitude towards climate change is closely followed by all parties concerned. There have been few researches on the role of environmental governance in low-carbon city transformation process, especially the Chinese one. This paper analyses the role of government environmental regulation played in the low-carbon city transformation process by taking Shenzhen as the research object. One of the world's youngest super cities, it also happens to be the lowest carbon emission intensity city in China. Striving to explore green low-carbon development path for the whole country, Shenzhen provides practical experience for countries to cope with global climate change. However, its efforts to reduce the total carbon emissions failed, but it emphasized the carbon emission intensity, which is consistent with the international commitments made by the central government. China’s policy towards handling climate change relies on hierarchical governance arrangement. The strength of the NGOs in the country is weak and incomparable with the government’s, which has mastered most of the resources and is just a reality in China.

Historically, urban development has always been centered on coastal areas – with access to waterbodies – seas, rivers and canals being a significant advantage for movement and trade. With most of the world’s megapolises located on coasts, land reclamation offers a solution for the expansion of city centers which are otherwise restricted by the coastline. The current understanding of urban regeneration and development on reclaimed lands is defined in this study, answering the basic questions of what, why and how. This study aims to assess the urban regeneration on reclaimed coastal land based on the principles of sustainable development defined by existing studies. The literature review establishes a theoretical framework and defines performance-based benchmarks identifying the spatial indicators of urban development. Composite indicators namely open space coverage, land use mix, percentage of coast for people, accessibility to public transportation and amenities, availability of pedestrian paths and cycling tracks and adequate road networks are considered for this framework. The conclusions are drawn based on the results of the analysis of spatial layout using GIS as a tool to map and empirically measure each indicator. The framework is validated using a major land reclamation project, West Bay, in the coastal urban area of ​​the city of Doha. The results determine that West Bay has achieved a good level of sustainability, although there are areas that could be enhanced to further improve the overall sustainability of urban development. These findings can serve as a guide for policymakers and various stakeholders for sustainable urban planning on reclaimed coastal lands.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

Building energy consumption plays an essential role in urban sustainability. The prediction of the energy demand is also of particular importance for developing smart cities and urban planning. Machine learning has recently contributed to the advancement of methods and technologies to predict demand and consumption for building energy systems. This paper presents a state of the art of machine learning models and evaluates the performance of these models. Through a systematic review and a comprehensive taxonomy, the advances of machine learning are carefully investigated and promising models are introduced.

Current acceleration in digital innovations, unexpected challenges in our social interactions, acceleration to virtualization, limitation in our physical spaces, and unpredictable changes in our Old lifestyles - as originated from the COVID-19 global pandemic 2020 - continue to provide us with a framework, rapidly updating under our eyes, of the modifications our world is undergoing by pursuing into a New “digital age”. Or, as many scholars say nowadays, into the New Normal! These are shared and deep changes that concretely stress their effects on how ideally a city should function. Forcing us to reflect on the capability to achieve shared choices and visions for the future by taking vantage from both the New digital platforms and New suddenly opened paths. In the pages of this article authors, through different but shared viewpoints, propose an answer to the topic of "Governance 3.0", addressing the attempt of a radical change of those paradigms, now consolidated, within which the spatial dimensions, in which we live and act, are shaped. Also analyzing the relationship between Technocracy and Democracy as defined by Khanna, it is argued that it is possible to realize new forecasts and acquire a more democratic and participatory (inclusive) dimension of Governance, also thanks to new digital technologies, by exploring the general unconscious "feeling" of people, through anonymous data collection and without any direct or indirect interference with it. The analysis of the "Sentiment", already developed in other fields but easily exportable within the urban discipline, can be considered as the beginning of hybrid practices where digital and analogic find a compromise to make the "Urbs" more attractive and inclusive, while the "Civitas", connected to the Internet, can contribute to the optimization of services, of the "Polis" and a new social/spatial reorganization.

Contemporary cities are facing many challenges, from social and economic issues to the new risks related to the impacts of climate change. Focusing on energy consumptions, and the related GHG emissions, cities are considered not only the main global contributors but also the areas most exposed to risks, because of their density of population and economic activities. Implementing urban planning strategies with the purpose of increasing energy efficiency and resilience overall are, for all these reasons, considered a top priority. This paper investigates the innovative contents about energy-efficient and energy-resilient urban planning solutions that have started to be implemented in the cities of the Emilia-Romagna region. Two kinds of planning instruments are therefore analyzed: the voluntary Sustainable Energy and Climate Action Plans (SECAPs) and the mandatory General Urban Plans (GUPs), recently approved in several cities of Emilia-Romagna. A comparative analysis of three cities in the Emilia-Romagna region, Bologna, Modena and Ravenna, is proposed on the strategies of their newly local city plans and SECAPs with focus on energy management and planning. The aim is to assess whether the new structure of local city plans and the influence of SECAPs could be useful in implementing such urban energy resiliency solutions.

In the last five years, European research and innovation programmes have prioritised the development of online catalogues and tools (handbooks, models, etc.) to facilitate the implementation and monitoring of Nature Based Solutions (NBS). However, only a few catalogues and toolkits within European programmes are directly related to mainstreaming of NBS for food production (i.e., edible NBS). Therefore, the main aim of this paper is to present existing NBS tools through the eyes of productive urban landscapes. We reviewed 32 projects related to NBS and 50 tools were identified and characterised. Then, the 6 tools already available, and providing indicators, were further analysed in terms of their format and knowledge domains. Our main conclusion demonstrates that there is a lack of tools capable of supporting users for planning and implementing edible NBS, calculating the food potential of the city and/or of individual edible NBS, including the needed resources for implementation and operation (water, nutrients, energy), and assessing their urban design value, environmental and socio-economic impacts. And when they do exist, there is a resistance to share the models and equations behind the tools to allow other projects to reuse or validate them, fact which is contrary to Open Science principles stood up by many research public agencies.

Anarchic urbanization and land artificialization expose urban ecosystems and Ecosystem Services (ES) to the threat. Urban ecosystems and trees play a crucial role in improving urban environments, and their management depends on the perceptions and preferences of urban residents. An assessment of the socio-ecological factors determining the perception of the actors allows for the proper design and planning of ecological urban policies and urban adaptation to climate change. In this study, we assessed the perception and discriminating variables of the different stakeholders of urban ES provided in the city of Cotonou. Thus, 381 city dwellers were individually interviewed after statistical sampling. Focus group discussions with the stakeholders also made it possible to highlight the ES provided in the different Land Use Units (LU). The results show that 73.23% of the city dwellers agreed that they were aware of ecosystem services. The hierarchical classification shows two homogeneous groups of perceivers with ethnicity, age and education as statistically discriminating sociological variables (pv˂0.001). Urban dwellers in the city of Cotonou perceived more SEs in the cultural and regulatory services category significantly (pv<0.001; v-test>3). The principal component analysis (PCA) reveals the varying availability of ES according to the different LU in the city. This study adds scientific value in the application of urban ecology to decision-making in climate and environment policy planning for sustainable cities in Africa and all over the world.

Adaptation to climate change is being addressed in many domains. This means that there are multiple perspectives on adaptation; often with differing visions resulting in disconnected responses and outcomes. Combining singular perspectives into coherent, combined perspectives that include multiple needs and visions can help to deepen the understanding of various aspects of adaptation and provide more effective responses. Such combinations of perspectives can help to increase the range and variety of adaptation measures available for implementation or avoid maladaptation compared with adaptations derived from a singular perspective. The objective of this paper is to present and demonstrate a framework for structuring the local adaptation responses using the inputs from multiple perspectives. The adaptation response framing has been done by: (i) contextualizing climate change adaptation needs; (ii) analyzing drivers of change; (iii) characterizing measures of adaptation; and (iv) establishing links between the measures with a particular emphasis on taking account of multiple perspectives. This framework was demonstrated with reference to the management of flood risks in a case study Can Tho, Vietnam. The results from the case study show that multiple perspective framing of adaptation responses enhance the understanding of various aspects of adaptation measures, thereby leading to flexible implementation practices.

Flood Management remains a major problem in many urban environments. Commonly, catchment models are used to generate the data needed for estimation of flood risk; event-based and continuous-based models have been used for this purpose. Use of catchment models requires calibration and validation with a calibration metric used to assess the predicted catchment response against the recorded catchment response. In this study, a continuous model based on SWMM using the Powells Creek catchment as a case study is investigated. Calibration of the model was obtained using 25 selected events from the monitored data for the catchment. Assessment of the calibration used a normalised peak flow error. Using alternative sets of parameter values to obtain estimates of the peak flow for each of the selected events and different accuracy criteria, the best datasets for each of the accuracy criteria were identified. These datasets were used with SWMM in a continuous simulation mode to predict flow sequences for extraction of Annual Maxima Series for an At-Site Flood Frequency Analysis. From analysis of these At-Site Flood Frequency Analyses, it was concluded that the normalised peak flow error needed to be less than 10% if reliable design flood quantile estimates were to be obtained.

The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within smart cities realm. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable and self-organized behaviour to deal with dynamic and fast changing systems. The intelligence of cities can be modelled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence, sensors and tags, and software. In this paper, a new approach based on the use of the Natural Computing paradigm and Collective Computation is shown, more concretely taking advantage of an Ant Colony Optimization algorithm variation and Fireworks algorithms in order to build a system that makes the complete control of the UPTS a tangible reality.

Artificial Intelligence and especially machine learning have noticed rapid advancement on image processing operations. However, its involvement in the architectural design is still in its initial stages compared to other disciplines. Therefore, this paper addresses the issues of developing an integrated bottom up digital design approach and details a research framework for the incorporation of Deep Convolutional Generative Adversarial Network (GAN) for early stage design exploration and generation of intricate and complex alternative facade designs for urban infill. This paper proposes a novel building facade design by merging two neighboring building’s architecture style, size, scale, openings, as reference to create a new building design in the same neighborhood for urban infill. This newly produced building contains the outline, style and shape of the parent buildings. A 2D urban infill building design is generated as a picture where 1) neighboring buildings are imported as a reference using mobile phone and 2)iFACADE decode their spatial adjacency. It is depicted the iFACADE will be useful for designers in the early design stage to generate new façades depending on existing buildings in a short time that will save time and energy. Besides, building owners can use iFACADE to show their architects their preferred architecture facade by mixing two building styles and generating a new building. Therefore, it is depicted that iFACADE can become a communication platform in the early design stages between architects and owners. Initial results properly define a heuristic function for generating abstract design facade elements and sufficiently illustrate the desired functionality of our developed prototype.

The manuscript wants to investigate the debate on urban resilience and climate change linking theory and practice, describing the possible innovations that concern urban design, urban normative and regional laws developing in different countries. The approach pursued would encourage resilience and flood protection through smart planning and through the architectural and urban project; considering public space as strategic soil where developing the resilient city, using engineering technical climate defence as new space for citizens and communities. Resilience themes are included in all levels of government and in spatial and strategic development policies such as in some project concerning public and private space and in municipal plans; the urban defense structures has to become new pleasant space for the city; these actions will not only contribute to making cities more resilient but will contribute to the creation of a more pleasant and attractive urban environment. The Resilience is the main keyword of some strategic vision of the Netherlands and of Italian laws and the concept is tested in some best practice such as in Rotterdam, in Bordeaux, in London and in the research carried out by "Arquitectos de Cabecera" in Barcelona. Resilience is seen as a new paradigm of smart planning.

Smart Cities leverage technology to address various urban challenges and creating disaster resilience is one of them. Technology is a vast and ever-evolving field, and hence the research on technology for improving disaster resilience is scattered. A major drawback of prevailing studies is that they continue to overlook the bottlenecks to effectively harness the benefits of technological innovations and that includes the need for a holistic and multidisciplinary approach. Therefore, this research intends to address that need by methodising the scattered research to provide meaningful insights towards the linkages between society and technological innovations through an urban scholar’s perspective. A comprehensive literature review was conducted to explore emerging and disruptive technologies for improving disaster resilience in Smart Cities. The review findings identified the emerging and disruptive technologies for improving disaster resilience in Smart Cities which were then classified. The findings suggested 4 key criteria to classify technologies including their impact the society, adoption speed, technology maturity and capabilities offered to the community. A Smart City which plans the technologies/ tools for disaster resilience may conduct the assessments under the aforementioned criteria, together with their context-specific feasibility assessments to make informed decisions and ultimately prioritise the most suitable for them.

: E-commerce sales surge represents a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by COVID19 pandemic) and delivering in few predefined places might help coping with missed deliveries substantially. Furthermore, this option enables consolidated shipping and reducing delivery trip costs. This paper analyses and compares consumers’ preferences for alternative collection strategies. It investigates home delivery vs parcel locker use and forecasts their future market shares. This is performed based on both customers’ socio-economic variables and attributes characterising these alternative logistic fulfilment strategies. The case study considered rests upon a stated preference survey deployed in the city of Rome. The investigation specifically targets young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

The phenomenon of Airbnb has significantly permeated the urban housing markets of major U.S. cities. This qualitative analysis meticulously examines its wide-ranging impacts, exploring Airbnb’s operational model, regulatory challenges, and its influence on housing availability, prices, and neighborhood dynamics. The research aggregates insights from various sources, including academic articles, web-based resources, and case studies, providing a nuanced understanding of the intricate balance cities are endeavoring to achieve between the economic opportunities Airbnb presents and the potential strains it places on local housing markets. The paper also scrutinizes the evolving policy frameworks and their effectiveness in mitigating the impacts of short-term rental platforms. Furthermore, it deliberates on future trends in the short-term rental market and the wider implications for the sharing economy. Concluding, the paper acknowledges the limitations of the qualitative method and suggests areas for future in-depth research, aiming to offer insightful contributions to policymakers, researchers, and urban planners engaged in urban housing discourse in the United States.

Although, promotion of urbanization culture in recent decades has made inevitable development of cities in the world, however, the development can be guided in a direction that leave, to the extent possible, minimum socioeconomic and environmental impacts. For this, it is required to first forecast auto-spreading orientation of cities and suburbs in rural areas over time and then avoid shapeless growth of cities. This paper is an attempt to develop a dynamic hybrid model based on logistic regression (LR), Markov chain (MC), and cellular automata (CA) for prediction of future urban sprawl in fast-growing cities. The model was developed using 12 widely-used urban development criteria, whose significant coefficient was determined by logistic regression, and validated by relative operating characteristic (ROC) analysis. The validated model was run in Guilan, a tourist province in northern Iran with a very high rate of urban development. For this, changes in the area of urban land use were detected over the period of 1989 to 2013 and then, future sprawl of the province was forecasted by the years 2025 and 2037. The analysis results revealed that the area of urban land use was increased by more than 1.7 % from 36012.5 ha in 1989 to 59754.8 ha in 2013, and the area of Caspian Hyrcanian forestland was reduced by 31628 ha. The results also predicted an alarming increase in the rate of urban development in the province by the years 2025 and 2037, during which urban land use is predicted to develop 0.9 % and 1.38 %, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban basements as well as around major roads and commercial areas. This development, if not controlled, will lead to the loss of 13863 ha of Hyrcanian forests and if the trend continues, 21013 ha of Hyrcanian forests and 20208 ha of Barren/open lands are expected to be destroyed by the year 2037. In general, the proposed model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable development of cities by providing decision-makers with an overview on future development of cities where the growth rate is very fast.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

The objectives of this paper are to analyze the urban growth and urbanization phenomenon in Algeria. Two processes that originated respectively by the expansion of existing urban areas and the process of urbanization that took place between 1954 and 2008, a period marked by significant economic, social and political changes in Algerian society. Our analysis was mainly based on the Algerian general census of population and habitat (2008) and on the application of rank-size distribution of cities according to Zipf’s rule. This study revealed that in Algeria, the urban system is particularly marked by the dramatic expansion of small cities. Indeed, the development of small towns, through the transition from rural to urban and the residential loosening of large cities have influenced the trend towards the balance of the urban system in Algeria. Results revealed also how the "primatial" city is undergoing profound economic and social changes at the national level. These changes are most often imposed from the top as part of land-use planning policy. This study provides some insights into the demographic dynamics of cities and the evolution of urban hierarchies in Algeria, through the comparison of the different rank-size distributions of Algerian cities in space and time. Our results suggest that land-use planning strategies are the only policies capable of influencing the future of the Algerian urban system.

Deep learning (DL) and machine learning (ML) methods have recently contributed to the advancement of models in the various aspects of prediction, planning, and uncertainty analysis of smart cities and urban development. This paper presents the state of the art of DL and ML methods used in this realm. Through a novel taxonomy, the advances in model development and new application domains in urban sustainability and smart cities are presented. Findings reveal that five DL and ML methods have been most applied to address the different aspects of smart cities. These are artificial neural networks; support vector machines; decision trees; ensembles, Bayesians, hybrids, and neuro-fuzzy; and deep learning. It is also disclosed that energy, health, and urban transport are the main domains of smart cities that DL and ML methods contributed in to address their problems.

This research paper is to analyze the planning and design techniques of the tourism complexes in the process of municipalities’ master planning. First, it explains the importance of the tourism industry with the help of theories of scholars and experts. Then, it emphasizes the link between the economic developments of cities/regions with the development of the tourism industry. The innovation of this work is to integrate tourism industry planning and comprehensive regional/ urban planning. The main way of doing this is to plan and design the tourism complexes in the early stages of the master planning of the municipality. Urban land-use policies and locating techniques are suggested through this research. Land-use policies and new urban design models for the regional/urban sustainable development are some of the other handouts in this paper. The outcome of this research is good assistance for engineers, planners, and students of urban and regional development.

Understanding how humans perceive animals is important for biodiversity conservation, however, only a few studies about this issue were carried out in South America. We selected two Brazilian cities to assess people’s perceptions of birds: Bauru (São Paulo, Brazil) and Belo Horizonte (Minas Gerais, Brazil). From the bird data we gathered, we developed a questionnaire and applied it between September 2020 and June 2021. The data obtained were analyzed by simple counts, Likert scale, and percentages. Also, open questions were placed on the Free Word Cloud Generator website. Our study confirmed that most respondents are aware of the importance of birds to ecological balance and that respondents had a generally positive attitude towards most of the bird species. However, they disliked exotic species such as the Domestic Dove and the House Sparrow, which are associated with disease, dirt, and disgust. Respondents also underestimated the number of birds that can live in urban areas and the song of birds is still a sense less explored and perceived by people. The concept of environmental perception seeks to cover aspects and understanding these human–biodiversity relationships is essential to successfully guide public policies, urban planning interventions, and environmental education activities.

Although our emotional connection with the physical urban setting is often valued, it is rarely recognised or used as a resource to understand future actions in city planning. Yet, despite the importance of emotion, citizens’ emotions are typically seen as difficult to quantify and individualistic, even though knowledge about people’s response to space could help planners understand people’s behaviours and learn about how citizens use and live in the city. The study explores the relationship between the physical space and emotions through identifying the links between stress levels, and specific features of the urban environment. This study aims to show the potential of integrating the use of galvanic skin response (GSR) within urban spatial analysis and city planning, in order to address the relationship between emotions and urban spaces. This method involved participants using a (GSR) device linked to location data to measure participant’s emotional responses along a walking route in a city centre environment. Findings show correlations between characteristics of environment and stress levels, as well as how specific features of the city spaces such as road crossing create stress ‘hotspots’. We suggest that the data obtained could contribute to citizens creating their own information layer - an emotional layer- that could inform urban planning decision-making. The implications of this application of this method as an approach to public participation in urban planning are also discussed.

Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.

Infection with the hepatitis B virus (HBV) is a public health problem in many parts of the world, due to its frequency, complications and socio-economic consequences. This study aimed to assess the seroprevalence of hepatitis B virus infection in rural areas and in urban areas. This cross-sectional study assessed the prevalence of HBV infection from 2015-2018 at CHR-Sokodé and USP of Ogaro. Biological data of 3000 participants (500 per year in each zone) enrolled and results of HBsAg were assessed during the study period. Female are represented 60% with average age comprised between [20, 29] years old. The high rate of participants enrolled (45.10%) are come for the monitoring of pregnancy. The prevalence of VHB during the study are 20.33% (610/3000), high prevalence (6.27%) and the means of VHB prevalence are shown in the age range between [30; 39] with 12.17% (365/3000) of female and 8.17% (235/3000) of male are positive after diagnostic detection of HBsAg (antigen of Hepatitis B virus). The prevalence of HBV in rural zone (Ogaro) are 5.23% and 15.07% in urban zone (Sokodé) and the high prevalence (17.50%) are shown in urban zone. The high prevalence of young suggests that some effort will be due to sensibilized young for HBV sexual transmission and the way of prevention. In addition, some research would be done in research of alternative therapy against this infection.

This paper presents the results of a recent study that was conducted with a number of German municipalities/cities. Based on the obtained and briefly presented recommendations emerging from the study, the authors propose the concept of an Urban Data Space (UDS), which facilitates an eco-system for data exchange and added value creation thereby utilizing the various types of data within a smart city/municipality. Looking at an Urban Data Space from within a German context and considering the current situation and developments in German municipalities, this paper proposes a reasonable classification of urban data that allows to relate the various data types to legal aspects and to conduct solid considerations regarding technical implementation designs and decisions. Furthermore, the Urban Data Space is described/analyzed in detail, and relevant stakeholders are identified, as well as corresponding technical artifacts are introduced. The authors propose to setup Urban Data Spaces based on emerging standards from the area of ICT reference architectures for Smart Cities, such as DIN SPEC 91357 “Open Urban Platform” and EIP SCC. Thereby, the paper walks the reader through the construction of an UDS based on the above mentioned architectures and outlines all the goals, recommendations and potentials, which an Urban Data Space can reveal to a municipality/city.

Considering characteristics of high river density, special underlying surface in plain river network region, and municipal drainage system function, river network drainage unit model is proposed, which is defined as a region surrounded by main river or embankment. Flood storage variety and control projects regulation of small rivers in each unit is simulated. With drainage catchment as an object, according to its drainage capacity, simplified municipal drainage model was developed. Coupling river network drainage unit model, simplified municipal drainage model and 2D flood routing model, urban flood analysis model for plain tidal river network region was developed, which could be applied to analyzing flood from upstream river, storm surge and local rainfall. Demonstration research was carried out in Puxi flood protected area in Shanghai.

Advances in the availability of multitemporal and global built-/human-settlements datasets as derived from Remote Sensing (RS) can now provide globally consistent definitions of “human-settlement” at unprecedented spatial fineness. Yet, these data only provide a time-series of past extents and urban growth/expansion models have not had parallel advances at high-spatial resolution. We present a flexible modelling framework for producing annual built-settlement extents in the near future past last observed extents as provided by RS-based data. Using a random forest and autoregressive temporal models with short time-series of built-settlement extents and subnational level data, we predict annual 100m resolution binary settlement extents five years beyond the last observations. We applied this framework within varying contexts and predicted annual extents from 2010 to 2015. We found that our model framework preformed consistently across all sample countries and, when compared to time-specific imagery, demonstrated the capacity to capture human-settlement missed by the input time-series and validation extents. When comparing building footprints of small settlements to forecast extents, we saw that the modelling framework had a 12 percent increase in ground-truth accuracy. This framework shows promise for predicting near-future settlement extents, and provides a foundation for forecasts further into the future.

Flavours of Glenroy (2013-4) was a socially engaged art research project focused on developing strategies to connect the diverse, mobile and transforming community of Glenroy through the theme of growing and distributing edible plants. The project was action research based, where artist researchers used creatively imagined mobile edible gardens to connect and engage with locals through project presentation and execution. The process of producing, presenting and conversing about edible gardening revealed Glenroy to be a transnational Australian dream suburb, reflecting the fluid globalising conditions of our cities. The project emphasized how social relations encouraged through art, has the capacity to transform social spaces, providing a platform to introduce new voices and narratives of a community and encourage inclusive participation in sustainable citizenship.

This study provides a detailed investigation into the pathways through which microplastics from urban sources are transported to marine ecosystems, their distribution across different environments, and their impacts on marine life. Utilizing a combination of water and sediment sampling across urban, riverine, and marine environments, the research quantitatively assesses the concentration and types of microplastics present, and evaluates the ecological consequences of their accumulation in marine ecosystems. The findings reveal a significant concentration of microplastics in all examined environments, with the highest levels detected in urban areas, closely linked to industrial activities and inadequate waste management practices. The study documents a variety of microplastic polymers, with polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET) being the most prevalent. A substantial impact on marine organisms was observed, including evidence of microplastic ingestion across a wide range of species and indications of stress and physical damage to coral reefs. Seasonal variations indicate that microplastic concentrations peak during periods of high rainfall, suggesting urban runoff as a critical pathway for microplastic transport. The study concludes with recommendations for improving waste management practices, enhancing public awareness and engagement in plastic recycling efforts, and implementing policies aimed at reducing the production and use of single-use plastics. This research underscores the urgent need for coordinated actions to mitigate the pervasive issue of microplastic pollution, highlighting the role of urban management and policy interventions in safeguarding marine ecosystems.

Cars are a highly inefficient mode of urban transport with significant negative impacts. Electric vehicles make it possible to eliminate direct CO2 emissions (though the total over a vehicle’s entire life cycle greatly offsets the advantages) but leave unchanged – or even aggravate – all the other negative effects on the quality of urban environments. Three visions for urban transport were presented: automobility, multimodality and accessibility. The first dominates North American cities, the second European one. The anomalies of these two visions have been examined. The automobility cities cannot manage the congestion and the attempts are self- defeating. The anomalies of multimodality city are related to the public space consumption for mobility and the impossibility to plan spatial proximity. The sustainable vision, that resolve the anomalies, is represented by the accessibility city in the Triple Access System (TAS) version which, however, still has a long way to go to be accepted and implemented.

Vegetation identification using remote sensing is essential for understanding terrestrial ecosystems and monitoring climate change. This technology by providing high-resolution images of the Earth's surface from satellites, aircraft, and drones has revolutionized the way scientists study and un-derstand vegetation patterns, providing information on the distribution, structure, and health of plant communities in different regions and biomes. However, identifying vegetation in multi and hyperspectral images remains a difficult, time-consuming, and costly process. Traditional methods for vegetation mapping involve the in-terpretation of spectral indices such as the Normalized Difference Vegetation Index (NDVI), alt-hough they often suffer from limitations such as manual interpretation and limited spatial resolution of satellite images. Furthermore, machine learning techniques, artificial neural networks, decision trees, support vector machines, and random forests have shown promising results in identifying and classifying vegetation cover from hyperspectral images. However, due to the need for per-son-nel with specialized expertise, their application on a large scale is still challenging. On the other hand, correlation methods between curves have emerged as powerful and simplified tool for comparing spectral signatures of hyperspectral image pixels and efficiently classifying vegetation in a study area. Pearson's correlation coefficient and spectral angle mapper are among the most common correlation methods used in vegetation mapping. These correlation methods, among many others available, offer an easily implemented and computationally efficient approach, making them particularly useful for applications in developing countries or regions with limited resources. In this article, a comparative study of correlation/distance metrics was conducted for the detection of vegetation pixels in hyperspectral images. The study allowed for the comparison of five distance and/or correlation metrics: direct correlation, cosine similarity, normalized Euclidean distance, Bray-Curtis’s distance, and Pearson correlation. The two metrics that yielded the best accuracy results in vegetation pixel detection were direct correlation and Pearson correlation. Based on the selected methods, a vegetation detection algorithm was implemented and validated on a hyper-spectral image of the Manga neighborhood in Cartagena de Indias, Colombia. The spectral library was utilized for image processing, while the numpy and scipy libraries in the Python programming language were used for the mathematical calculation of correlations. Both the study's approach and the implemented algorithm aim to serve as a reference for conducting detection studies of various material types in hyperspectral images using open-access programming platforms.

Free-space communication is a leading component in global communications. Its advantages relate to a broader signal spread, no wiring, and ease of engagement. Satellite communication services became recently attractive to mega-companies that foresee an excellent opportunity to connect disconnected remote regions, serve emerging machine-to-machine communication, Internet-of-things connectivity, and more. Satellite communication links suffer from arbitrary weather phenomena such as clouds, rain, snow, fog, and dust. In addition, when signals approach the ground station, it has to overcome buildings blocking the direct access to the ground station. Therefore, satellites commonly use redundant signal strength to ensure constant and continuous signal transmission, resulting in excess energy consumption, challenging the limited power capacity generated by solar energy or the fixed amount of fuel. This research proposes LTSM, an artificial recurrent neural network technology that provides a time-dependent prediction of the expected attenuation level due to rain and fog and the signal strength that remained after crossing physical obstacles surrounding the ground station. The satellite transmitter is calibrated accordingly. The satellite outgoing signal strength is based on the predicted signal strength to ensure it will remain strong enough for the ground station to process it. The instant calibration eliminates the excess use of energy resulting in energy savings.

China is experiencing rapid urbanization. The focus on health issues has shifted from the treatment of diseases to passive or active prevention. Diseases caused by the deterioration of the urban environment, such as cardiovascular disease, diabetes, obesity and other chronic diseases and mental illness, have gradually become the main threat to public health. Studies have confirmed that urban green spaces (UGS) can help residents relieve mental stress, improve mood, reduce mental fatigue and restore attention, which has a positive effect on people's physical and mental health. In this study, the relationship between the quantity and quality factors of UGS and the physical and mental health of urban residents in Xihu District of Hangzhou is examined, and on this basis, UGS design strategies are proposed to promote the physical and mental health of residents. This study is of great significance for the future construction of UGS that are beneficial to the health of residents and the promotion of a healthy China and healthy city construction.

As digital technology has become an integral part of urban’s daily operations; the urban landscape is constantly evolving with the needs of its society. This new reality allowed Municipalities to exert a higher influence in the national and local economy. Through deliberate planning and executing initiatives, they can ignite the local financial ecosystem to growth. In line with this, the paper aims to understand the possibilities available to the Greek Municipalities to exploit the smart city benefits to foster economic development. It is essential to understand the role of different factors including the strategy during the planning and implementing phases of initiatives concerning economy and innovation in a smart city. To achieve this, a tailor-made questionnaire and advanced statistical techniques are applied. The main findings highlight the importance to plan initiatives aligned with the needs of the municipality and the business environment. The existence of a smart city strategy has a catalytic effect on the final impact of the implemented initiatives on the urban environment. A systematic analysis of the smart cities’ dynamics and the new state of the urban environment can help the local actors focus on the value creation and public service provision, fostering innovation and profitability.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism where examining social sustainability becomes imperative. While prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases that include Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana) are discussed through multi-layered investigations that involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people-place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people-place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

Analyses of faculty citation activity usually focus on counts as a function of author characteristics such as rank, gender, previous citation levels, and other factors influencing productivity and career path. Citation analyses of publications consider aspects such as number of authors, author reputation, author order, length of the title, methodology, and impact factors of the publication. While publication topics or discipline are considered to be important factors, they are more difficult to analyze, and therefore performed less frequently. This paper attempts to do that for the field of urban planning. Urban planning is multi-disciplinary and includes consideration of social, economic, technological, environmental, and political systems that shape human settlement patterns. It has been suspected that some topics are more “popular” and have larger audiences, therefore are cited more often. Using nearly 15,000 urban planning publications, this paper presents an analysis of topics to assess which are cited most frequently. The classification of publications was performed using a Support Vector Machine (SVM), a machine learning (ML) approach to text classification, using citation data from Google Scholar. The citation levels for the resulting categories are analyzed and discussed.

Free-range sloths living in an urban environment is rare. In this study, human opinions, attitudes and interactions with a population of Bradypus variegatus in a public square were investigated. A questionnaire was applied to people in the square where the sloths reside, and informal, opportunistic observations of human-sloth interactions were made. 95% of respondents knew of the sloths’ existence in the square and 87.8% likes their presence. Opinions about population size differed greatly and younger people were concerned if the square was appropriate place for them. Some human-sloth interactions showed the consequence of lack of biological knowledge. People initiated all sloth-human interactions. The fact that sloths are strictly folivorous has limited their interactions with humans and consequently minimised negative impact of the human-animal interaction on their wellbeing. These results demonstrate that while there is a harmonious relationship between people and sloths, actions in environmental education of the square’s public could be beneficial for the sloths.

Cities’ delineation remains a hot topic of debate in a time where comparisons between cities are becoming increasingly based on different issues that address various scales of interventions and thus different concepts of cities. Aiming to compare cities and their insertion into globalization, we suggest that the “urban field of influence” is the best way to approach cities for this specific perspective. However, after reviewing the different existing possible concepts, we replace this concept with four different approaches proposed by Pumain et al. (1992): political entities, morphological agglomerations, functional urban areas and conurbations/Mega city regions. We discuss the top-down and bottom-up existing initiatives launched at the world scale and then use a mixed top-down and bottom-up approach to propose a new delineation of a large urban region (LUR), denoting a concept close to the conurbation or Mega city-region concept. The compositions of these LURs are published as an initial incomplete framework, suggesting the need for further critical comments and contributions to improve them.

Low- and middle-income country cities face unprecedented urbanization and growth in slums. Gridded population data in small grid squares (e.g., 100x100m) derived from demographic and spatial data are a promising source of current population estimates, but face limitations in slums due to the dynamic nature of this population as well as modelling assumptions. The efficacy of using gridded population data in slum areas remains a question mark especially in the context of UN SDG indicator development. In this study, we use field-referenced boundaries and population counts from Slum Dwellers International (SDI) in Lagos (Nigeria), Port Harcourt (Nigeria), and Nairobi (Kenya) to assess the accuracy of nine gridded population datasets in slums. We also use a modelled map of all slums in Lagos to assess use of gridded population dataset for SDG11.1.1 (percent of population living in deprived areas). We found that all gridded population estimates vastly under-estimated population counts in populous slums, and the calculation of SDG11.1.1 in Lagos was impossibly low; gridded population datasets estimated that just 1-3% of the Lagos population lived in slums, compared to 56% using the UN-Habitat approach. We outline specific steps that might be taken to improve each gridded population dataset in deprived urban areas. While gridded population estimates are not yet sufficiently accurate to estimate SDG11.1.1, we are optimistic that some datasets could be following updates to their modelling approaches.

Numerous cities in our modern world are unfortunately encountering the negative effects of urban sprawl: this includes unrestricted settlement, degradation in the quality of their environment, traffic congestion, sub-standard buildings, and air pollution as well as flooding, swampy areas, landslides, and settlement zones with dilapidated utilities and infrastructures that are not safe for living. The Ulaanbaatar City land management master plan defined the settlement zone area suitable for living as 33,698 hectares. However, due to unrestricted urban sprawl caused by exponential growth of the city’s population, the settlement zone area reached 39,235 hectares, which exceeds the limit by 5,537 hectares. In order to tackle this issue, several urban planning concepts were developed to be implemented within the Ulaanbaatar City urban planning framework. It is, in any case, problematic to choose a single planning concept due to the fact that neither measurements nor analyses are being made of the respective spatial quantitative indicators in urban planning assumptions that are taking the current situation into consideration. One of the prerequisites for identifying an optimal concept in urban planning is an assessment of the current situation, and measuring the impacts against its quantitative data. In the current research, when defining Ulaanbaatar city sprawl, the base year was selected as 1990, the time when the city started to sprawl. Research analyses were made using geographic information systems based on the satellite data 1990, 1995, 2000, 2005 Landsat ТМ-5, 2010 Quickbird, 2015 World View and 2020 Sentinel2, respectively. Based on the results of determining the city sprawl using spatial indicators, the urban planning concepts applied thus far have been analyzed in relation to land use efficiency and land use structural changes. This research paper addresses the issue of reducing unrestricted urban sprawl by increasing the internal density of the city. The research results show that, by applying the concept of a compact city in urban redevelopment planning for 4,604 hectares, and by allocating the settlements in 12,479 hectares, it is possible to reduce the urban expansion threefold and increase land use efficiency accordingly.

The rapid growth of urban areas is a major challenge facing cities around the world. This growth can have a significant impact on the local climate, leading to higher temperatures and other changes. In desert climates, the effects of urban expansion can be particularly pronounced. This study investigated the impact of urban expansion on land surface temperature (LST) in Baghdad, Iraq. Notably, this study employs a sophisticated artificial intelligence method known as Random Forest for Land Use Land Cover (LULC) classification, utilizing three Landsat images spanning the temporal spectrum from 1985 to 2021 to meticulously monitor land use transformations and associated LST variations. The results showed that vegetated areas declined by 46.8% during the study period, while built-up areas increased by 124.7%. This decline in vegetation was accompanied by an increase in LST, with bare soil recording the highest temperatures. The study also found that LST has a strong inverse relationship with vegetation and moisture. This means that areas with more vegetation and moisture tend to have lower LSTs. These findings suggest that urban expansion can lead to higher LSTs in desert climates, which can have implications for the health and wellbeing of residents. The study has important implications for urban planners and policymakers in Baghdad and other cities in desert climates. By identifying the main factors that control LST, the study provides insights into strategies for mitigating the effects of urban expansion on temperature.

The purpose of this article is to analyze urban form through the mapping of morphological indices, namely impervious surface fraction, building density, verticality, height/width ratio, roughness length, and porosity, to support urban planning in the city of João Pessoa, PB, in northeastern Brazil. The application of this study identifies and calculates such significant indices for the city's urban space from a Geographic Information System (GIS) model. The spatial indices play notable roles in climate at different scales, developing guidelines to maximize environmental quality, promote improvements to thermal comfort, minimize the urban heat island in the city of João Pessoa, and provide relevant data (considering microclimate aspects), guiding decisions related to the planning process.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

This article addresses the urbanization model in valley bottom areas in the city of São Paulo, an-alyzed in its urban planning and socio-environmental aspects, and examines the hydrological impacts triggered by its implementation. It argues that sustainable occupation of urbanized hy-drographic basins should be based on environmental criteria in order to attain a sustainable water management regime that can ensure urban and environmental resilience. In the “Introduction,” the article emphasizes that urbanization in São Paulo has neglected the natural features of river basins, promoting the channeling of watercourses, which resulted in floods and inundations. “Theoretical Basics” brings in key concepts related to the environmental approach of drainage infrastructure with gray and green-blue systems. “Methods” details our qualitative research, bibliographical analyzes, referential case studies, and cartographical analyzes (geoprocessing), focusing on a case study in the Jaguaré creek basin. “Results” includes guidelines and recom-mendations for an urbanization model adjusted to valley bottom areas, applicable to new patterns of urban occupation or to the adjustment of existing patterns. “Discussion” explores the concept of “local sustainable self-development,” and “Conclusions” highlights the importance of an inte-grated, multisectoral, and sustainable planning, adjusted to the characteristics of river basins in valley bottom areas, promoting a socially responsible urban occupation, especially in the face of climate change.

People living in slums and other deprived areas in low- and middle-income country (LMIC) cities are under-represented in censuses, and subsequently in "top-down" gridded population estimates. Modelled gridded population data are a unique source of disaggregated population information to calculate local development indicators such as the Sustainable Development Goals (SDGs). This study evaluates if, and how, WorldPop-Global (WPG) -Unconstrained and -Constrained “top-down” datasets might be improved in a simulated realistic LMIC urban population by incorporating slum profile population counts into model training. We found that the WPG-Unconstrained model with or without slum training data grossly underestimated population in urban deprived areas while grossly overestimating population in rural areas. SDG 11.1.1, the percent of population living in slums, for example, was estimated to be 20% or less compared to a "true" value of 29.5%. The WPG-Constrained model, which included building auxiliary datasets, far more accurately estimated the population in all grid cells (including rural areas), and the inclusion of slum training data further improved estimates such that SDG 11.1.1 was estimated at 27.1% and 27.0%, respectively. Inclusion of building metrics and slum training data in “top-down” gridded population models can substantially improve grid cell-level accuracy in both urban and rural areas.

Observing air quality from sensors onboard light rail cars in Salt Lake County, Utah began as a pilot study in 2014 and has now evolved into a five-year state-funded program. This metropolitan region suffers from both elevated ozone levels during summer and high PM2.5 events during winter. Pollution episodes result predominantly from local anthropogenic emissions but are also impacted by regional transport of dust, chemical precursors to ozone, and wildfire smoke as well as being exacerbated by the topographical features surrounding the city. Two electric light-rail train cars from the Utah Transit Authority light-rail Transit Express (“TRAX”) system were outfitted with PM2.5 and ozone sensors to measure air quality at high spatial and temporal resolution in this region. Pollutant concentration data underwent quality control procedures to determine whether the train motion affected the readings and how the sensors compared against regulatory sensors. Quality assurance results from data obtained over the past year show that TRAX Observation Project sensors are reliable, which corroborates earlier preliminary validation work. Two case studies from summer 2019 are presented to illustrate the strength of the finely-resolved air quality observations: 1) an elevated ozone event and 2) elevated particulate pollution resulting from 4th of July fireworks. The mobile observations were able to capture spatial gradients as well as pollutant hotspots during both of these episodes. Sensors have been recently added to a third light rail train car, which travels on a north-south oriented rail line along which we were unable to monitor air quality previously. The TRAX Observation Project is currently being used to provide reliable pollutant data for health studies and inform urban planning efforts. Links to real-time data displays and updated information on the quality-controlled data from this study are available at https://atmos.utah.edu/air_quality/trax/.

Cities exemplify the evolving world with changing demographics and climates. Urban green spaces play a crucial role in improving the quality of life of people through their potential to mitigate temperatures. Therefore, comprehending their impact is of para-mount interest. Given the challenges in obtaining temperature data from urban locations, this study develops Artificial Neural Networks (ANNs) to predict daily and hourly temperatures in Valladolid, Spain, with a particular focus on urban allotment gardens and a forested urban park. ANNs were built and evaluated from various combinations of inputs (X), hidden neurons (Y) and outputs (Z) under the practical rule of "making net-works simple, to obtain better results". The best performing model was 6-Y-1 ANN archi-tecture with an impressive result of Root Mean Square Error (RMSE) = 0.42°C in the urban garden called Valle de Arán. However, other five ANN architectures were also tested (7-Y-5; 6-Y-5; 7-Y-1; 3-Y-Z and 2-Y-1). ANNs dedicated to urban temperature analysis hold immense potential for urban planning and research, aiding in under-standing the urban climate, forecasting future temperatures, identifying temperature mitigation strategies and even for managing urban crops

Maker spaces can contribute significantly to the circular economy of cities: they demonstrate not only the economic potential of inner loop circularity, but also provide tangible evidence of spatial and social integration of production into the urban context. This paper presents findings from a typological analysis of 326 maker spaces in seven European cities, with a focus on selected exemplar case studies to reveal design characteristics, principles and opportunities for circular city development. The research shows that circular economy principles of ‘reduce-reuse-recyle’ are aligned with maker spaces such as repair cafés, secondhand shops and fab labs. In the context of cities, circularity is revealed by a spatial tightening of resource cycles that close the loops of product life cycles. Furthermore, urban maker spaces demonstrate social engagement and a relationship to local production which inherently includes maintenance, repair, reuse, and redistribution. This paper defines five maker typologies, presents exemplars of each from different urban contexts and posits hybrid design strategies for the transition to circular maker cities. Through the adoption of these findings into urban planning policy it is possible accelerate circular urban production and close the sustainability gap between small scale local and large scale regional manufacturing.

Men are perceived as significant barriers to the uptake of contraception in some communities, and lack of spousal communication regarding contraception is evident in some studies conducted in South-West and Northern Nigeria. The objective is to identify and discuss how husband consent to family planning (FP) and spousal communication influence family planning use among peri-urban dwellers in Nigeria. The study was limited to the primary dataset collected among young mothers that resides in peri-urban between the age of 15-30 years in South West, Nigeria. The result showed that the use of family planning was high among the respondents whose husband give consent to the use of family planning, and respondents who had appropriate spousal communication. Similarly, respondents whose spouse asks questions or whose husband advises on communication are likely to use FP. On the other hand, respondents whose husband didn’t give consent, respondents with inappropriate communication with the spouse, respondents whose spouses didn’t give advice, and those whose spouses didn’t ask questions are less likely to use FP.

In this study we sought to investigate the impact of urbanization, presence of concrete river bottom, and nutrient pollution on microbial communities along the L.A. River. Six molecular markers were evaluated for identification of bacteria, plants, fungi, fish, and invertebrates in 90 samples. PCA (principal components analysis) was used with PAM (partitioning around medoids) clustering to reveal community structure and an NB (Negative binomial) model in DESeq2 was used for differential abundance analysis. PCA and factor analysis exposed the main axes of variation but were sensitive to outliers. Differential abundance of Proteobacteria was associated with soft bottom sites, and there was an apparent balance in the abundance of organisms responsible for nitrogen cycling. Nitrogen cycling was explained by differential abundance of ammonia oxidizing archaea, the complete ammonia oxidizers Nitrospira sp., nitrate reducing bacteria Marmoricola sp., and nitrogen fixing bacteria Devosia sp. which were differentially abundant at soft-bottom sites (p adj &lt; 0.002). In contrast, differential abundance of several Cyanobacteria and other anoxygenic phototrophs was associated with the concrete bottom sites, which suggested the accumulation of excess nitrogen. The soft bottom sites tended to be represented by differential abundance of aerobes, whereas the concrete-associated species tended to be alkaliphilic, saliniphilic, calciphilic, sulfate dependent, and anaerobic. In Glendale Narrows, downstream from multiple water reclamation plants, there were differential abundance of cyanobacteria and algae, however indicator species for low nutrient environments and ammonia-abundance were also present. There was differential abundance of ascomycetes associated with Arroyo Seco and a differential abundance of Scenedesmaceae green algae and cyanobacteria in Maywood, in the analysis which compared suburban with urban river communities. The proportion of Ascomycota to Basidiomycota within the LA River differed from the expected proportion based on published worldwide freshwater and river 18S data; the shift in community structure was most likely associated with the extremes of urbanization. This study indicates that extreme urbanization can result in overrepresentation of cyanobacterial species that could cause reductions in water quality and safety.

This paper responds to the research question, “can urban farming help Nepali cities become more sustainable”? Especially after the Covid-19 pandemic, urban residents have begun to realize that food transported from long distances could not always be reliable. Urban farming can help produce fresh food locally and avoid long-distance transportation, and refrigeration. This practice also helps reduce greenhouse gases through plant carbon use efficiency (CUE). Urban farming not only helps city-dwellers towards achieving self-reliance in food production but also in vegetation carbon dynamics (VCD) while supporting the circular economy. Urban farming consists of edible landscapes, which can also be an aesthetic public space. As urban lands command higher prices than agricultural land, urban farming usually happens on residential yards, roofs, balconies, community gardens, and dedicated areas in public parks. Rainwater harvesting, and redirecting can help irrigate urban farms which can be part of rain gardens. The national census of 2021 (CBS 2022, p5) identifies that 66 percent of Nepal’s population live in urban areas. However, the World Bank (2018), shows that only 21 of Nepal’s population was projected to live in urban areas in 2021. It is not debatable that the urbanization process in Nepal is on the rise. Thus, urban agriculture can play an important role to supplement the residents’ food needs. Many cities in Nepal have already successfully adapted to urban farming where residents grow food on their building site, balconies, and rooftop often growing plants on pots, vases, and other types of containers. The UN-Habitat, with the support of European Union and local agencies, has published a rooftop farming training manual (2014) showing the feasibility of urban farming in Nepal.The paper discusses how Public Private Partnership (PPP) can promote urban agriculture and make the process more effective and attractive to urban farming households. It also analyzes how a PPP approach also facilitates the use of better technology, advisory support, and use of research extension activities. This paper draws on literature review, secondary data (e.g., from National Census Nepal 2021) and authors’ professional experiences related to best practices in the areas to analyze the benefits and challenges related to urban farming in Arizona, USA. The paper will provide recommendations for Nepali cities to maximize the benefit provided by urban farming. It is expected to be useful to Nepali policy makers, and government agencies, and nonprofit organizations which promote sustainability, and organic farming.

This study explores how to delineate Russian cities in order to make them comparable on the world scale. In doing so we introduce the concept of large urban regions (LUR) applicable to the Russian urban context. This research is motivated by a principal research question: how to construct a statistical urban delineation, which would allow first, to demonstrate integration of cities into globalization, and second, to make global urban comparative research. Previous studies on urban delineation in Russia have focused almost exclusively on functional urban areas, which have substantial limitations and are not suitable for global urban comparisons. Addressing this research gap, we propose a new definition of Large Urban Regions (LUR). In doing so, first, we introduce the context of Russian cities (2), then we discuss existing Russian urban concepts (3), and justify a need for a new urban delineation (4). Afterwards, we present a general method to delineate Large Urban Regions in Russian context (5.1), and illustrate it in the two case studies of St. Petersburg (polycentric region) and Samara (monocentric region) (5.2). In the last part (6), we discuss the 10 the largest urban regions in Russia and describe a constructed database including all Russian LURs.

Urban environments face escalating challenges, e.g. due to uncontrolled urbanization, rapid population growth or climate changes, prompting the exploration of sustainable solutions for enhancing urban green spaces (UGS). For this reason, poplars (Populus L.), due to their rapid growth, wide range adaptability to environmental conditions and versatility of use, would have emerged as very promising. This comprehensive review synthesizes current knowledge regarding poplar's application in urban landscapes, emphasizing its multifaceted contributions and benefits. However, challenges arise from the variable lifespans of different poplar cultivars, necessitating strategic management approaches. Selecting cultivars based on growth rates, root system characteristics, and adaptability to urban conditions is pivotal. Adaptive replanting strategies, incorporating species with varying lifespans, offer solutions to maintain continual greenery in urban landscapes. Collaborative efforts between researchers, urban planners, and policymakers are essential for devising comprehensive strategies that maximize benefits while addressing challenges associated with their variable lifespans. In conclusion, harnessing poplar's potential in urban greenery initiatives requires a balanced approach that capitalizes on their benefits while mitigating challenges. Further research and adaptive strategies are crucial for sustained and effective utilization in creating resilient and vibrant urban landscapes.

Heavy metals constitute pollutants particularly common in air, water, and soil. They are present in both urban and rural environments, on land and in marine ecosystems, causing serious environmental problems since they do not degrade easily, remain almost unchanged for long periods, and bioaccumulate. Detection, though especially quantification, is a systematic process as monitoring of their levels needs to be carried out at regular intervals since there is often seasonal variation. The need for rapid and low-cost determination of metals is therefore considerable. In the present study atomic absorption spectroscopy (AAS), using a flame or graphite furnace, and square wave anodic stripping voltammetry (SWASV), using a bismuth thin film electrode, a sensitive voltammetric method is being compared and analytically validated. Atomic absorption spectroscopy (AAS) represents a well-established analytical technique while anodic stripping voltammetry is being criticized for its applicability in complicated sample matrices such as soil samples. This sample-handling challenge is being investigated in the present study. The results show that both methods AAS and ASV were satisfactorily correlated and showed that the concentration of metals is lower than the limit values, but with increasing trend. Therefore, continuous monitoring of metal levels in the urban complex of the city is necessary and a matter of great importance. Regarding Cd, the detection limits of Cd are lower compared to those of AAS when using the graphite furnace, while an overestimation was noted when using flame-AAS in comparison with those found with SWASV. The SWASV method has the advantage of being cheaper and faster, enabling the simultaneous determination of heavy elements across the range of concentrations that these elements can occur in Mediterranean soils. Additionally, we applied a dsDNA-modified electrode which can be used in the speciation analysis of Cu(I) and Cu(II). The changes in the characteristic peaks of guanine and adenine can be applied in the redox speciation analysis of copper in soil which represents an issue of great importance.

The Sustainable Development Goals (SDGs) represent a central framework to guide sustainable urban development (2030 Agenda). However, it is not clear how and where SDG 11 (Sustainable Cities and Communities) is being implemented, and how such implementation might be improved. We investigated this subject by analyzing United Nations (UN) SDG Good Practices data from 2018 to 2021. We applied five criteria to the 336 SDG 11 responses: (1) geography; (2) actors; (3) progress toward targets; (4) areas of implementation; and (5) scale of action. Overall, 86 of the 193 countries that adopted the 2030 Agenda submitted at least one SDG 11 good practice. 33 countries contributed 73.8% of the total, and most developing countries did not make submissions. A very small number of responses (between 2.6 and 9.1%) addressed equity-related targets. Good practices from developed countries were usually more technology-based and system-forming; developing countries typically focused on issues of day-to-day concern. Overall, this analysis points to the need for better and more systematic reporting on SDG 11 implementation, a more active public sector role in SDG implementation and reporting, more focus on dimensions related to social equity, and better formulation of urban sustainability targets and indicators in the future.

There is an overall scientific consensus that public space and, mainly, space with a high ecological index – most notably experienced in green areas – positively affects individual and collective well-being and urban dwellers’ physical and mental health. However, the ‘reality check’ indicates difficulties in translating the assumed benefits of green space into implementable interventions in urban environments. To examine such an ‘implementation gap’ on the case of Zurich seems valid, given that the ‘green urban agenda’ debate has been embedded in numerous Swiss policies (from the federal to the municipal levels). In narrow terms, the research first focuses on Zurich’s district 9 consisting of two neighborhoods (Altstetten and Albisrieden) – the area under ongoing densification yet with a variety of green spaces, to then elucidate four green space clusters and their 400-meter catchment areas in the mentioned district. The mixed-method approach has been applied at three analytical levels: 1) documentary analysis of multi-scale national policy toolkits, to identify the critical tenets associated with the ‘green urban agenda’, 2) assessment of green spaces in Zurich’s district 9 based on online available quantitative data and on-site observation, to determine their provision, types, size and mutual connectivity, and 3) analysis of four green space clusters within the mentioned district through on-site observation, to identify green space attributes and main activities. Through critical mutual examination of the identified ‘green urban agenda’ principles in the national policies, on the one hand, and green space attributes, on the other, the research findings reveal the extent of the convergence and/or divergence between the ‘green urban agenda’ policy trends and their implementation in practice.

Traffic source emissions inventories for the rapidly growing West African urban cities are necessary for better local characterization of vehicle emissions released into these cities atmosphere. This study based on local field campaign in a representative site of anthropogenic activities over West African cities such as Yopougon (Abidjan, Côte d'Ivoire) during 2016, provided useful information on vehicle type and age, traveling time, fuel type and amount for fuel consumption estimation. Also, high traffic flow of personal car were recorded on highway, boulevard and backstreet whereas high flows of intra-communal sedan taxi are recorded on main and secondary roads. In addition, the highest daily fuel consumption value of 56 L.day^-1 was recorded in heavy vehicle while the lowest value of 15 L.day^-1 is recorded for personal car using gasoline. This study will be useful for the improvement of uncertainties related to the different databases used to estimate inventories emissions either national or international reports. This work provides useful information for future studies on urban air quality, climate and health impacts assessment in African cities. It may also be useful for policy makers to support implementation of emission reduction policy in West African cities.

During the Covid 19 pandemic, we saw a huge impact on the lives of individuals in cities. The way people responded was controlled and limited. The lockdown restricted a lot of movements in the cities as well as contained the citizens in their houses. Through a semi-structured interview, the research aims to understand the change in behaviour and response of individuals across various cities. The paper aims to understand how people change their day-to-day life in cities during the pandemic and while the restrictions getting released post the first wave. The paper also understands how the pandemic impacted urban spaces and what value they hold for people. By interviewing individuals from different cities, the data were transcribed and analysed to understand this behavioural change and the attitude of people. The outcome of the research was derived as a concept map through the codes generated during the research.

Sea level rise and increased storm events, urge cities to develop governance capacity. However, a cohesive conceptual and empirical-based understanding of what governance capacity implies, how to measure it, and what cities can learn, is largely lacking. Understanding the influence of context is critical to address this issue. Accordingly, we aim to identify crosscutting contextual factors and their influence in impeding, enhancing or prioritising different elements of governance capacity to address urban flood risk. By assessing governance capacity through nine conditions and 27 indicators in two Dutch and two cities in the UK, three crosscutting contextual factors are identified: 1) flood probability and impact, 2) national imposed institutional setting, and 3) level of authority to secure long-term financial support. We found that contextual factors explain differences in urban capacity-priorities within and between both countries. The institutional setting in the UK and recent political devolution emphasized the role of citizen awareness, stakeholder engagement, entrepreneurial agents, and the overall necessity for local capacity-development. The Dutch focus on flood safety through centralised public coordination reduces flood probability but also inhibits incentives to reduce flood impacts and reduced public awareness. In conclusion, the three identified contextual factors enable a better understanding of capacity-building priorities.

The paper makes a critical assessment of urban development in Nigeria against the backdrop of a rapidly changing population and growth rate. The Authors interrogated the effects of development control- mechanisms through the lenses of identified social anomalies in three selected pilot cities of Nigeria (Kaduna, Abuja FCT, and Lagos). Thematic areas examined include, the state of critical infrastructure, population dynamics, urban sprawl, city polarization, transportation, waste management systems, security/crime and economics. The Authors identified structural transformation of three Nigerian cities with focus on the causes and attendant consequences on urban development. The study found that urban growth has over-stretched the state of critical infrastructure in the cities and the mechanisms of development control seem ineffective in stemming unregulated growth, compromises and unplanned ‘development’. The paper noted that the impact of these developments has overstretched the state of critical infrastructure with far-reaching consequences. The authors conclude with some recommendations for strategic planning and sustainable development strategies aimed at mitigating the problems of urban development in Nigeria.

Urban air pollution is a significant threat to both the environment and public health. Primarily originating from traffic emissions, particulate matter is identified as the most prevalent and toxic pollutant in cities. In recent years, street vegetation has emerged as a nature-based solution to improve urban air quality. However, to achieve this goal, proper placement of vegetation is crucial. This study critically investigates how different street tree placement strategies affect the local air quality, based on a model calibrated using existing air quality measurements from one of the most polluted streets in Glasgow. We then test the local air quality effects of tree orientation, spacing, shape, porosity, size, species, and wind directions. The findings suggest that trees effectively enhance air quality, particularly when implemented on the leeward side of the street. To achieve optimal effectiveness, the spacing of trees require careful alignment with the aspect ratio, as haphazard planting could lead to unfavorable results. The insights on improving air quality in Glasgow's street canyons, complements the objectives of the ‘Glasgow Avenues Programme’ and can be included in its Low Emission Zones to co-benefit the environment and the wellbeing of the local community.

With growing urbanisation the sustainability of cities has become increasingly important. Although cities have been using indicators for a long time it is only in the last decades that attempts have been made to collate indicators into indicator sets with the aim of reflecting the many different aspects that need to be covered to assess the sustainability of a city. The aim of this paper is to review how indicators for monitoring sustainable urban development have evolved over time and compare them to the indicators suggested by the UN Sustainable Development Goals (SDGs). The review reveals that previous indicator sets emphasised environmental sustainability, health and economic growth. It is also shown that indicator sets that pre-date the SDGs lacked dimensions such as gender equality and reduced inequalities. In all, the SDG indicators provide the possibility of a more balanced and integrated approach to urban sustainability monitoring. At the same time, a methodology is needed to facilitate the adaptation process of localising the SDGS, targets and indicators. Challenges of local application include their large number, their generic characteristics and the need to complement them with specific indicators that are more relevant at the city level.

The COVID-19 pandemic has put lifestyles in question, changed daily routines and limited citizen freedoms that seemed inalienable before. A human activity that was greatly affected since the beginning of the health crisis is mobility. Focusing on mobility, we aim to discuss the transformational impact that the pandemic brought on this specific urban domain, especially with regards to the promotion of the smart growth agenda and the acceleration towards the smart city paradigm. We collect 60 initial policy responses related to urban mobility from 86 cities around the world and analyse them based on the challenge they aim to address, the exact principles of smart growth and sustainable mobility that they encapsulate and the level of ICT penetration. Our findings suggest that emerging strategies, although mainly temporary, are transformational, in line with the principles of smart growth. As a result the pandemic becomes an opportunity for shifting towards more sustainable urban planning and mobility practices. However, most policy responses adopted during the first months of the pandemic fail to leverage advancements made in the field of smart cities, and to adopt off-the-shelf solutions such as in monitoring, alerting and operations management.

This study constructs an evaluation system of high-quality utilization of urban land (HUUL) and comprehensively adopts the entropy method, the kernel density estimation, and the geodetector model to analyze the spatio-temporal evolution and driving factors of the HUUL levels of 284 Chinese cities from 2006 to 2020. The measurement results show that during 2006-2020, the HUUL level showed an obvious upward trend, and the eastern region > the central region > the overall region > the western region > the northeastern region. According to the kernel density map, except for the region of the west, there is a trend of different degrees of enlargement of the difference in the main peak position of the HUUL level among cities in the other three regions, and there are individual cities in the eastern and western regions with much higher HUUL levels than the others; According to the results of factor detection, it can be seen that innovative utilization and open utilization are the endogenous dominant factors that promote the improvement of HUUL level, and the level of economic development is the exogenous dominant factor that supports the im-provement of high-quality utilization of urban land.

The study focuses on solving urban challenges such as temperature reduction, urban stormwater management, noise reduction, air quality improvement, and CO2 concentrations reduction, and suggests terrestrial and freshwater habitat types (HTs) found in Europe, as innovative forms of nature-based solutions (NBS) for them. Establishment of native HTs in different urban environments to solve urban challenges would enhance biodiversity at different levels and integrate this aspect in urban planning. This contribution builds on the recognition that surfaces of vegetated terrain are the most versatile NBS in addressing the broadest range of environmental problems in urban areas and that the processes running within these green spaces offer the key to socio-ecological improvements of such areas. Employing narrative literature review, qualitative content analysis, and interdisciplinary expert discussion this paper defines why and how native HTs of unchanged nature can be implemented as NBS in the urban environment, indicate potential HTs for specific urban challenges and presents an approach to the inclusion of HTs as NBS into spatial planning documents at national, regional, and local levels. The proposed planning approach attributes added value to HT, and by linking the concepts of NBS and HT integrates them into urban planning.

Urban governance and sanitation in the peri-urban commune of Agoè-Nyvé 6 in Togo: Diagnosis of the sanitation system in Adétikopé.

The evaluation of spatial planning results, or outcomes, has been rather neglected by scholars and practitioners. The causes of this neglect are linked to the characteristics of the planning systems in use or difficulties in quantifying results. To advance the state of the art of outcome evaluation, this paper focuses on assessing the implementation of national spatial planning objectives in urban landscapes, through the use of an evaluation framework that makes use of spatially explicit information. The framework is built on four dimensions which reflect the main domains of spatial planning: efficient built-up development, conservation of agricultural land, landscape preservation, and human perception. Indicators capable of capturing landscape changes in both time and space are used to verify degree of conformance between adopted objectives and actual development patterns. We make use of spatially explicit data and assess whether and where landscape changes occurred, by integrating the framework into a multi-criteria analysis. In the present study, the framework is tested in two study areas in Switzerland and Romania, and the results are interpreted from the perspective of spatial planning approaches in the two countries. The efficiency and utility of the framework is demonstrated by its ability to provide valuable information facilitating improvement in the performance of planning processes, such as identifying where the implementation of objectives is less effective, and the domains of spatial planning that are affected. Our findings highlight that the distance between objectives and outcomes can be attributed to differences in countries’ spatial planning approaches, particularly regarding landscape preservation and management. Our study provides valuable insights for the integration of time series of spatial data into the evaluation procedure.

Choosing the optimal location for a city based on sound environmental geomorphology planning is of the utmost importance to achieving environmental sustainability, as it can spare the State and other decision-making entities a great deal of stress in the long run. GIS offers great potential for environmental planners to choose the most appropriate places for the cities of the future, especially when coupled with environmental geomorphological analyses. The State of Kuwait seeks sustainable development through the implementation of clear and specific urban plans, some of which suffer from a severe lack of geomorphological and spatially based environmental planning. This study aims to: 1) Conduct suitability modelling for establishing new cities in Kuwait, 2) Assess the current 2005-2030 urban plan, and 3) Propose possible recommendations and solutions for potential urban problems. The study relies on integrating several methods to devise a framework that will aid researchers and decision-makers in selecting optimal locations for built structures based on analysis and modelling (e.g., digital elevation model, geologic mapping, geomorphology, natural hazards, heritage/archaeological sites, military areas, oil fields, soils). Using this methodology in choosing city sites contributes to achieving sustainable development, reducing city problems, saving countries’ budgets, and saving lives. Results from this study enhance understanding of how environmental geomorphology, when combined with GIS, can be harnessed to achieve sustainable urban development in the Arabian Gulf countries and other desert countries.

This paper addresses challenges and solutions in urban development and infrastructure resilience, particularly in the context of Japan's rapidly urbanizing landscape. It explores the integration of smart city concepts to combat land subsidence and liquefaction, phenomena highlighted by the 2011 Great East Japan Earthquake. Using advanced technologies such as smart sensing and predictive analytics through kriging and ensemble learning, the study aims to improve the accuracy of geotechnical investigations and urban planning. By analyzing data from 433 geotechnical surveys in Setagaya, Tokyo, it develops predictive models to accurately determine the depth of bearing layers critical to urban infrastructure. The results demonstrate the superiority of ensemble learning in predicting the depth of bearing layers, with significant implications for smart city development and the sustainability of urban environments. This interdisciplinary approach not only seeks to mitigate risks associated with geological disturbances, but also promotes sustainable urban growth that prioritizes safety and prosperity. Through advanced technology and comprehensive research, the study underscores the potential of smart cities to address urban complexities and ensure a resilient, sustainable future.

Current acceleration in digital innovations, the unexpected challenges in our social interactions, open access to virtualization, huge limitation in our physical spaces, and unpredictable changes in our old lifestyles - as originated from the COVID-19 global pandemic in 2020 - continue to provide us with a framework, rapidly updating under our eyes, of the modifications our world is undergoing by pursuing into the “new digital age”. Or, as many scholars say nowadays, into the new normal! These are shared and deep changes that, regardless of their permanence or temporariness in the time, concretely stress, ever more greatly, their “own” effects on how ideally a city should function. Forcing us to reflect on the real ability to achieve choices and visions for the future by taking vantage from the new digital platforms. In the pages of this article authors, through different eyes but sharing an early response to the matter of new Governance, explore the theme of a radical change of those already consolidated paradigms and, therefore, of the innovations that are transforming the way we understand our society and its technologic advancements, economics, and culture, as defined through dimensions of time and space. This article identifies a methodologic vision for acquiring a more democratic and participatory (inclusive) dimension in the newest configuration of contemporary cities, the new smart city, and in the possible innovations in reading the common sentiments and wishes through the new digitalized world. The analysis investigates how ICT is altering the meanings/ideas of “urban planning”, driving us toward a more effective “governance” through a citizen-centred digital approach. Indeed, city governance's success must be measured based on the “listening capacity” of the inhabitants and the facilities that we are capable to provide to citizens. “Sentiment Analysis” tool is tested as a useful tool to achieve these aims.

The paper provides a critical synthesis of analysis and evaluation of some case studies in the Italian national context, which allowed, through an inductive method, to assess, in terms of integration and coherence, the process of transposition of climate change adaptation contents, possibly already contained within a regional urban framework (Regional Urban Laws) or specific Regional Adaptation Strategies or Local Adaptation Plans, within the territorial and urban planning tools of metropolitan or local scale.

There has been an increase in the inefficiencies of urban infrastructure services in Indian cities as a result of rapid and unplanned urbanization (UNDP, 2017). Indian cities have grown multidimensional as a result of massive industrializa-tion and technological spread backed by globalization impacting the early 2000. It has transformed the city fabric and the associated challenges. Therefore, an Urban Climate Vulnerability Assessment (UCVA) is needed to identify, target and recognize climate vulnerable urban cities, sectors, or populations. The UCVA framework consists of seven broad thematic indicators — physical, hazard, social, demographic, financial provisioning, infrastructure and admin-istration vulnerabilities, and their sub indicators to represent the climate vul-nerability of Indian cities. This assessment is for seven Indian cities namely Delhi, Mumbai, Chennai, Bengaluru, Srinagar, Shillong, and Ahmedabad which were selected based on their geographical location, population, ecosystem types and hazards/ hazard trends to understand and assess the respective vul-nerabilities. The Assessment is done through a comprehensive approach using a robust and predictive qualitative framework. It helps in determining respec-tive risks and in improving community resilience to the climate hazards by in-tegrated planning and improved preparedness. UCVA can support as a deci-sion support mechanism for devising suitable mitigation and adaptation strategies for building urban climate resilience.

This study assessed the impact of counter-mapping on university students' perception and knowledge of their cities, focusing on cultural diversity, urban dynamics, and social challenges. Using a quasi-experimental design with pretests and posttests in the province of Alicante, Spain, changes in the understanding of urban geography, everyday life, and cultural diversity were analyzed among 54 Geography Didactics students. Likert scale surveys and open-ended questions were employed, complemented by statistical and qualitative analyses, to measure knowledge and perceptions before and after the counter-mapping project. The results indicate that although quantitative correlations did not show statistically significant significance, qualitative analysis revealed significant and profound learning. Participants uncovered the hidden layers of their urban environments and gained a better understanding of the complexities and challenges of their cities. The project promoted the development of critical skills such as analytical thinking, active research, and effective communication, proving to be a valuable pedagogical tool that surpasses the limitations of traditional teaching methods and encourages active and committed citizenship. This inclusive and multidimensional approach enriches the diversity of experiences and knowledge, significantly contributing to the teaching of urban subjects, community engagement, and social responsibility, laying the groundwork for proper tourist, cultural, social, or urban planning of city spaces.

In this paper, a land utilization efficiency evaluation model, which takes environmental loss into consideration, has been structured via taking advantage of the slack-based measure (SBM) model. Meanwhile, based on the panel data from 280 prefecture-level cities in China from 2003 to 2013, the paper thoroughly probed into, and discussed, the effect imposed by industry clustering and specialization on the utilization efficiency of urban land. Research results indicate several conclusions, as follows: (1) Taking environmental loss into account, the land utilization efficiency of prefecture-level cities in China is generally low. During the research period, the average value of the land utilization efficiency of prefecture-level cities in China is only 0.349, with, first, a declining trend, and then a rise. Geographically speaking, the land utilization efficiency presents a “depression in the center” phenomenon which means the land utilization efficiency of prefecture-level cities in the central China are relatively lower than in the east and west. Now, the difference among the urban land utilization efficiency in China significantly reflects the distinctions among Eastern, Western, and Central China. Moreover, the contribution degree of the difference of the land utilization efficiency among cities of central China to the aggregation difference shows an ascending momentum. Additionally, the relation between the population scale and land utilization efficiency in cities manifests as a U shape; (2) theoretically speaking, the relation between industry clustering and urban land utilization efficiency presents an inverted-U shape. However, this kind of relation is not significant in Western and Central China and medium-sized cities. Moreover, most of cities are still relatively far away from the inflection point or the critical value; and (3) the industry professional level has imposed a positive influence on urban land utilization efficiency. However, that influence is not significant in Eastern China and large cities. Consequently, strengthening the industry professional development of Western and Central China and small and medium-sized cities, facilitating diversified development of industries in Eastern China and large cities, and accelerating industrial clustering, all of these measures above will be conducive to improving urban land utilization efficiency in China.

The aim of this study is to solve the problems of complicated pretreatment and high analytical cost in the detection technology of trace drug toxicants in municipal wastewater. A high-performance magnetic sorbent was synthesized for enrichment of trace drug substances in wastewater to develop magnetic solid-phase extraction pretreatment combined with the acoustic ejection mass spectrometry (AEMS) analytical methods for the molecules in wastewater drug toxicants. The magnetic nanospheres was successfully prepared by magnetic nanoparticles modified with divinylbenzene and vinyl pyrrolidone.The results showed that the linear dynamic range of 17 drugs was 1-500 ng/L, the recovery was 43%-105%, the matrix effect was more than 67%, the limit of quantitative detection was 1-2 ng/L, and the detection time of each sample was 2.98s. It can be seen that the developed magnetic solid-phase extraction (MSPE) method is a good solution to the problem of complicated pre-treatment and analytical cost in the detection of drugs in wastewater. The developed magnetic material and acoustic excitation coupled mass spectrometry analysis method can realize the low-cost, efficient enrichment and fast analysis of different kinds of drug molecules in urban sewage.

Globally, the need for sustainable urban development has never been more urgent than now. This is because estimates indicate that more than half of the global population will be living in urban areas by 2050, with South Africa estimated at 80%. This paper focuses on socio-economic nuances that impede sustainable urban development, as well as the strategies that can accelerate sustainable urban development in South Africa. Through a literature review methodology, the analysis identified the following issues as impediments to sustainable urban development in South Africa, informal settlements and businesses, lack of consultations with urban citizens, unresolved apartheid legacies, violence, crime and insecurity, and migration and immigration intricacies in South Africa. The paper also established the strategies to accelerate sustainable urban development as working with informality and against it, promoting inclusivity and access to resources, formulating, and accelerating policy reforms, investing in rural areas and towns, and finally investing in superior technology and innovation. These findings imply that there is a need to seek alternative development models and approaches, to address social challenges such as poverty, unemployment, and poor housing, aspects that impact negatively on urban development planning and sustainable development. This is because the major challenges to sustainable urban development are human-related challenges, that need social and economic solutions. There is also a need to reduce rural-urban migration by developing rural towns to ease pressure in major towns which are already spilling over.

In recent decades, particularly intense changes have occurred in Spanish urban areas. This is the result of demographic and urbanizing transformations that have led to a change in the city model. The predominance of compact forms has been replaced by the growing prominence of urban sprawl. Structures are now more extensive, characterized, in turn, by fragmentation and notable consumption of land in the peripheries. In medium-sized cities, the municipalities bordering the central cities have concentrated the processes of suburbanization and periurbanization. This paper addresses the process of change for 34 cities and their urban areas located in inland Spain. A proposal is made for the delimitation and characterization of urban areas, taking the municipality as the unit of analysis. At the methodological level, six variables are used, analyzed by means of multicriteria statistical techniques combined with the use of GIS tools. An Urban Transformation Index (ITU) has been developed that synthesizes urbanizing, demographic and socioeconomic dynamics. In the territorial area, the 20-minute isochrone is used as a reference. In the temporal domain, the period of analysis addresses the events of the first two decades of the twenty-first century.

The systems for automated monitoring of a human’s personal carbon footprint and CO2-equivalent emissions at industrial enterprises were developed in the article. The personal carbon footprint monitoring system includes data collection subsystems based on energy consumption metering devices, data storage and transmission, and calculation subsystems. To measure the consumption of water, electricity, thermal energy, IoT control sensors were selected. The calculation of the individual carbon footprint of a person is proposed. The system for automated monitoring of the carbon footprint of an enterprise includes a subsystem of devices for monitoring the use of energy resources, a subsystem for data transmission, calculation and prompt display of the carbon footprint. Selected devices for monitoring the consumption of water, energy and heat resources with data transfer to the SCADA system. An algorithm for calculating the carbon footprint of an enterprise is proposed. Structural schemes for automated carbon footprint control have been developed.

Recent developments in US immigration policies have brought tired attention to the problems of immigration in the United States. Although there has been growing awareness of the need to manage immigration that address the economic causal factors underlying the motivation to cross borders, the recent changes in immigration policies fail to do so. This paper brings attention to the futility of border control laws and calls on urban planners to address immigration through strategic planning for a socially-responsible, sustainable economic development in sending countries. This paper concludes with recommendations for how to do this.

This study aims to understand the current state of research in urban resilience and to open a discussion about multi-level perspectives for this concept. Starting with the history of the concept of resilience, we identify three main stages in resilience concept’s evolution: conceptualization, contextualization and operationalization. Confusion occurs between sustainability and resilience, therefore we clearly separate these two concepts by creating conceptual maps. Such maps also underline the specificities of urban and regional resilience discourses. We illustrate that urban resilience research, operating within intra-urban processes, is oriented towards natural disasters, while regional resilience research, operating mostly within inter-urban processes, is oriented towards economic shocks. We show that these two approaches to resilience – urban and regional – are complementary, and we propose to integrate them into a multi-level perspective. By combining these two discourses, we propose a multi-level approach to urban resilience that takes into account both top-down and bottom-up resistance processes. In the discussion section, we propose to take the panarchy perspective as a theoretical framework for multi-level urban resilience, that explains the interactions between different levels through adaptive cycles, relationships between which can help to explain urban resilience.

Reducing GHG emissions is a crucial challenge in urban areas, characterized by high energy consumption and reduced exposure to nature. In this context, the urban green system could play a pivotal role. In the literature, scholars analyzed both the ability of species-specific and layout-specific green infrastructures to increase carbon sequestration and the best location sites of new green infrastructures, to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement, based on vegetation species-specific performance and local carbon emissions of city components. This paper uses tree inventory data from a medium-sized city in central Italy (Perugia) to develop a spatial analysis of the urban parks' performance in carbon sequestration. Then, the method evaluates the carbon emission of a public city building to generate a spatialized balance between buildings’ demand and trees’ supply, to support local decisions about the best locations for new green infrastructures and the choice between species. The paper contributes to GIS-based tools that vary the recommended location sites and species for new green infrastructures based on the demanded ecosystem service.

Smart cities, leveraging advanced data analytics, predictive models, and digital twin techniques, offer a transformative model for sustainable urban development. Predictive analytics plays a crucial role in proactive planning, enabling cities to adapt to evolving challenges. Concurrently, digital twin techniques provide a virtual replica of the urban environment, fostering real-time monitoring, simulation, and analysis of urban systems. This research underscores the significance of real-time monitoring, simulation, and analysis of urban systems to support test scenarios that identify bottlenecks and enhance smart city efficiency. The paper delves into the crucial roles of citizen report analytics, prediction, and digital twin technologies at the neighborhood level. The study integrates ETL/ELT processes, AI techniques, and a digital twin methodology to process and interpret urban data streams derived from citizen interactions with the city's coordinate-based problem mapping platform. By employing an interactive GeoDataFrame within the digital twin methodology, dynamic entities facilitate simulations based on various scenarios. This approach enables users to visualize, analyze, and predict the response of the urban system at the neighborhood level. Consequently, antecedent and predictive patterns, trends, and correlations are visualized at the physical level of each city area, leading to improvements in urban functionality, resilience, and resident quality of life.

Urban form is associated with both socio-economic and urban physical properties. This study explores the differences among urban forms in the Seoul Metropolitan Region with a comparison between census-based socioeconomic variables and landscape metrics computed from remotely sensed data. To accomplish this, factor analysis and multi-dimensional scaling were used with the selected variables and metrics. When all of the measures are considered together, four types of cities and towns emerged: 1) exurban-fragmented high growth, 2) exurban-fragmented low growth, 3) compact-extensive urban core and 4) sub-urban compact-high growth. The results indicate that the fusion of knowledge of the physical urban layout and that of socio-economic characteristics is beneficial for a better understanding of urban spatial patterns. However, there remain challenges in delineating each urbanized area and with indicator selection for comparing urban form across cities and towns.

Mapping settlement extents at the annual time step has a wide variety of applications in demography, public health, sustainable development, and many other fields. Recently, while more multitemporal urban feature or human settlement datasets have become available, issues still exist in remotely-sensed imagery due to coverage, adverse atmospheric conditions, and expenses involved in producing such feature sets. These challenges make it difficult to increase temporal coverage while maintaining high fidelity in the spatial resolution. Here we demonstrate an interpolative and flexible modeling framework for producing annual built-settlement extents. We use a combined technique of random forest and spatio-temporal dasymetric modeling with open source subnational data to produce annual 100m x 100m resolution binary settlement maps in four test countries of varying environmental and developmental contexts for test periods of five-year gaps. We find that in the majority of years, across all study areas, the model correctly identified between 85-99% of pixels that transition to built-settlement. Additionally, with few exceptions, the model substantially out performed a model that gave every pixel equal chance of transitioning to the category “built” in each year. This modelling framework shows strong promise for filling gaps in cross-sectional urban feature datasets derived from remotely-sensed imagery, provide a base upon which to create future built/settlement extent projections, and further explore the relationships between built area and population dynamics.

Drone imagery has the potential to enrich urban planning and preservation, especially where it converges with the growing creation and use of 3D models. The authors have conducted a systematic literature review of articles published between 2002 and 2022, drawing from reputable academic repositories including Science Direct, Web of Science, and China National Knowledge Infrastructure (CNKI), to identify current gaps in existing research in the application of UAVs to the creation of 3D models in urban planning and preservation. Findings indicate five research shortcomings: limited participation of planning experts, research focus imbalance, lack of usage for special scenarios, lack of integration with smart city planning, and limited interdisciplinary collaboration. The study also acknowledges current limitations with UAV applications and discusses possible countermeasures as well as future prospects.

Rapid technological advancements in information communication technologies have enabled water resource data collection at greater spatial and temporal scale. However, this water data is often limited to the purposes of its primary collection, and limits decisions made by stakeholders towards sustainable urban water management. This empirically focused research paper examines how water practitioners involved in strategic planning can capture additional values from integrating different water data. Furthermore, the perception of 22 urban water practitioners across Australia are presented, regarding the importance of and difficulty in using water data for strategic planning, and the necessary steps for achieving integrated water management practices. Interviewees perception revealed gaps in available water resource data (i.e. water quality, ground water, stormwater, and urban water use), and limitations of industry guidelines for operating within existing governance frameworks. Overall, the research highlights the Australian urban water sector’s perception of water data’s crucial role in representing stakeholders interest; however, changes made in water data’s collection are required for an integrated water management approach. Implications for future open water data standard are discussed.

Community centers play a crucial role in urban environments, providing physical and educational services to their surrounding communities, particularly for students. Among the many benefits for students are enhanced academic outcomes, improvement of behavioral problems, and increased school attendance. Such centers are also particularly vital for low-income and racial minority students as they are pivotal in giving them outside-of-school learning opportunities. However, determinants influencing attendance at community centers remain largely unexplored. Using census data, Boston Centers for Youth and Families (BCYF) attendance data, and specific center attributes, we develop human mobility gravitational models to predict attendance across the BCYF network. Using those models, we investigate the potential effects on general and student attendance by changing center attributes, such as facilities and operating hours. We also research the impact of changing the walking accessibility to those centers on their respective attendance patterns. After the analysis, we find that the most cost-effective policy to increase BCYF attendance is changing each center’s educational and recreational offerings far beyond any accessibility interventions. Our results provide insights into potential policy changes that could optimize the attendance and reach of BCYF Community Centers to underserved populations.

According to the Global Report on Internal Displacement (GRID, 2022), the number of displaced people worldwide at the end of 2021 was 59.1 million, with 53.2 million of them being the result of conflicts and violence, and 5.9 million caused by climate-related disasters. Furthermore, the In-ternational Organization for Migration (IOM) predicts that the climate crisis will be solely re-sponsible for one billion migrants by 2050. In this context, the research examines the issue of coastal multi-risk arising from a combination of heavy rainfall, river's overflow, and sea-level rise phenomena, analysing it through the disciplinary perspective of urban planning. Specifically, the study focuses on the need to upgrade the Local Urban Plan from a climate-proof perspective by defining a method aimed at updating the territory's cognitive framework through the preparation of a multi-risk map (which considers different time horizons), as well as the prescriptive apparatus of the Plan through the definition of a toolkit of site-specific design actions oriented towards urban adaptation. The proposed methodology is verified on the case study of Isola Sacra, Fiumicino (Italy), and it is intended to be applicable to other territorial contexts. The research aims to outline guidelines for updating urban planning tools from a climate-proof perspective to promote long-term resilient urban development in risk-prone areas.

Mexico is currently facing important water management challenges. Cities in the country are facing water scarcity and at the same time, they struggle with floods during the raining season. The water sensitive urban design (WSUD) approach has proved to be helpful in tackling urban water challenges such as floods and water scarcity and it is being implemented in cities around the world. The WSUD approach highlights the role of both the water cycle and the water utilities systems, when transitioning towards a water sensitive stage. Therefore, the objective of this research is to analyse the current situation of the water cycle and the water utility (SIAPA). To do so, we have selected the Metropolitan Area of Guadalajara (MAG) and proposes a case study approach. Within our case of study, we answer two questions: 1) What are the causes of water scarcity and flooding in the MAG? and 2) What are the proposals to solve these problems under a WSUD approach? By answering these questions, we identified that the water management in the MAG corresponds to a single purpose infrastructure. This type of management does not contribute to solve the problems of water scarcity and floods. The water supply policy is based only on the construction of large dams disregarding the storage and use of rainwater, and reuse of greywater, and water-conservation devices. In order to transition towards a water sensitive stage, a WSUD approach that includes multi-purpose infrastructure should be considered. Such as green roofs, swales, rainwater gardens, infiltration trenches, etc.

Buildings can generate heats which are mostly generated from the machinery using inside the buildings, and these heats generally released to the atmosphere. Buildings can also block the wind flow by their canopies and trap the heat by using low albedo materials. These causes pointedly contribute to urban heat island and greenhouse effects. Likewise, urban development and building construction in Cambodia are growing rapidly. The construction has been recognized as a key development sector while thousands of buildings are being built and have been operated in the main cities. However, those buildings mostly have not been considered to incorporate sustainability concepts while the major final energy consumers in the country are buildings. The buildings’ energy consumption is also projected to increase more than double until 2040. Hence, sustainable building promotion in Cambodia is necessary, and sustainable building criteria are completely required. This research aims to find out significant sustainable building criteria for Cambodia and focused on planning and design criteria because having proper planning and design is a smart start leading to achieving building sustainability in all stages. This research used the Delphi methods to validate the relevant sustainable building criteria available in the literature and then select the significant ones for Cambodia based on the Delphi consensus. The results showed that ninety-nine consensus planning and design criteria were found to be significant for sustainable buildings in Cambodia.

Since the public inauguration of the URP (Urban and Regional Planning) Bill in 2009, which is now law (The Urban and Regional Planning Act No. 3 of 2015), urban planning in Zambia has undergone changes. In partnership with the Volunteer Service Overseas (VSO) Federation, the Zambian parliament put into effect pilot urban planning assistance programs to assist districts around the country, including Chipata District in 2011, transition to a more decentralized, integrated and locally-defined approach to urban planning. However, the presence of discrimination, corruption, and negative attitudes towards urban planning engagement, social maladies prominently displayed in Zambian society, pose challenges to implementing the ideal goals of the 2009 URP Bill. The extreme, widespread poverty in Zambia merely exacerbates the propensity towards corrupt and discriminatory behavior, and influences poor attitudes toward urban planning engagement. This paper describes the projects undertaken by the VSO volunteer from the USA between 2011 and 2012 in the light of the specific urban problems facing Chipata District, and discusses the ways the social maladies play out in Zambian society to pose challenges to implementing the recommended changes to the planning system scribed in the 2009 URP Bill.

This study’s primary goal was to conduct an analysis on the flood propensity of the Tabua (Ribeira Brava) drainage basin’s main watercourse. In addition to that, this study also recommends two different methodologies in order to mitigate flood’s impacts, namely by dimensioning a detention basin and adjusting the riverbed roughness coefficient. Regarding the study on the flood propensity, it was necessary to resort to geomorphological data, which was obtained when characterizing the watershed; that data was crucial to determine the expected peak flow rate, according to the Gumbel Distribution methodology and considering a 100 years return period, and to perform necessary tasks in the SIG ArcGIS software. Lastly, it was also analyzed the drainage capacity of this drainage basin’s river mouth, in order to conclude whether it would have the capacity to drain the total volume of rainwater if an extreme flood event was to happen. Indeed, the main results point out that this watershed’s river mouth doesn’t have the necessary drainage capacity to cope with an extreme event, for the return period that was considered. As a consequence of that, the two mitigation measures aforementioned were developed considering Tabua (Ribeira Brava) drainage basin’s specific features: the sizing of the detention basin was estimated through the Dutch Method and the Simplified Triangular Hydrograph Method, while the adjustment of the roughness coefficient was considered a valid solution to enhance the drainage capacity of this river mouth.