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In West Africa, the number of people facing food crises increases each year in both rural and urban areas, due to interdependent factors. The city of Grand Lome in Togo faces an increasingly large population that must ensure access to food, which it hardly produces anymore, because of the establishment of housing and infrastructure. In addition, the increase in the price of food products in this city further weakens the purchasing power of city dwellers in the context of poverty. The objective of this article is to determine the state of food and nutritional security of households in Grand Lome. The methodology adopted is based on documentary research and field surveys. A total of 310 households were interviewed on questions allowing the construction of indicators of food and nutritional security. The results show that despite the availability of food in urban markets, the food situation of households in Grand Lome is not very good. Nearly 49% of households do not have good dietary diversity, and 48% have adopted stress and crisis strategies to access food. Similarly, in Grand Lome, the prevalence of global acute malnutrition is 2.6% of children under 59 months. [ABSTRACT FROM AUTHOR]

This paper investigates rural mobility in the Global South using a participatory GIS approach to address the lack of mobility data that hampers sustainable planning to support rural development and resilience. Limited rural mobility due to poor infrastructure and financial constraints hinders social and economic activities, impeding development. The study aims to explore the socio-economic impacts of limited mobility, identify software needs for data-scarce environments, and map daily mobility patterns. Fieldwork was conducted in Kenya (2022) and Nepal (2023), collecting geographic data related to mobility. The methodology included community engagement and digital mapping using the QField app for precise data collection. The study highlights the use of participatory GIS to fill data gaps, enabling more accurate mobility assessments. Community engagement revealed gender-specific mobility patterns, with women facing particular challenges in daily activities. The study emphasizes the need for adaptable data models to reflect community-specific mobility needs and the integration of qualitative insights to propose effective and sustainable mobility solutions. This research contributes to understanding rural mobility in the Global South and demonstrates the effectiveness of participatory GIS in overcoming data scarcity and enhancing mobility analysis. [ABSTRACT FROM AUTHOR]

This study leverages a Discrete Event Simulation (DES) model to optimize the sweet potato supply chain in Zimbabwe, focusing on production, distribution, and market dynamics under varying climate conditions. The integration of climate data into the simulation model reveals significant insights into the resilience of different sweet potato varieties, particularly highlighting the suitability of yellow-skinned sweet potatoes for harsh climates due to their high resilience and drought resistance. However, market preferences still favor white-skinned varieties despite their vulnerability to climate extremes. The DES model identifies key bottlenecks, particularly in cultivation and transportation, that hinder supply chain efficiency. To address these challenges, the study emphasizes the importance of targeted interventions, such as improving access to irrigation, strengthening pest management, and adopting community-based resource-sharing approaches. These strategies are critical for enhancing both the resilience and efficiency of the supply chain. Additionally, the study highlights the urgent need for adaptive strategies to mitigate the effects of drought on agricultural productivity, especially in regions that heavily rely on crops like sweet potatoes. Overall, this research offers strategic insights for policymakers and stakeholders aiming to improve food security and agricultural productivity in Zimbabwe, as well as in other countries with similar climate challenges. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon impacting ecosystems, economies, and livelihoods. This research carried out in Bol in the Lake Province of Chad, a region heavily affected by climate change, aims to analyze the gender-differentiated impacts of this phenomenon. It was carried out using the rapid analysis and participatory planning (RAPP) method and structural analysis for social systems (SAS2). Meteorological and socioeconomic data were collected through interviews, household surveys, and focus groups. The results indicate variability in rainfall, with a slight downward trend and an increase in temperature. The women identified an increase in the cost of living, human and material losses, warmer housing, and health problems as socioeconomic socioeconomic consequences of climate change. Their coping strategies include community self-help, humanitarian aid, and welfare activities. Obstacles to full participation in the search for solutions include access to education, low decision-making power, and political representation. This research enriches our understanding of the interactions between gender, climate change, adaptation, and inclusive policy importance. [ABSTRACT FROM AUTHOR]

The advancement to Urban 4.0 requires urban digitization and predictive maintenance of infrastructure to improve efficiency, durability, and quality of life. This study aims to integrate intelligent technologies for the predictive maintenance of photovoltaic panel systems, which serve as essential smart city renewable energy sources. In addition, we employ vision transformers (ViT), a deep learning architecture devoted to evolving image analysis, to detect anomalies in PV systems. The ViT model is pre-trained on ImageNet to exploit a comprehensive set of relevant visual features from the PV images and classify the input PV panel. Furthermore, the developed system was integrated into a web application that allows users to upload PV images, automatically detect anomalies, and provide detailed panel information, such as PV panel type, defect probability, and anomaly status. A comparative study using several convolutional neural network architectures (VGG, ResNet, and AlexNet) and the ViT transformer was conducted. Therefore, the adopted ViT model performs excellently in anomaly detection, where the ViT achieves an AUC of 0.96. Finally, the proposed approach excels at the prompt identification of potential defects detection, reducing maintenance costs, advancing equipment lifetime, and optimizing PV system implementation. [ABSTRACT FROM AUTHOR]

Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco's Oum Er-Rbia (OER) watershed from 2002 to 2022, using the newly developed Watershed Integrated Multi-Drought Index (WIMDI), through Google Earth Engine (GEE). WIMDI integrates several drought indices, including SMCI, ESI, VCI, TVDI, SWI, PCI, and SVI, via a localized weighted averaging model (LOWA). Statistical validation against various drought-type indices including SPI, SDI, SEDI, and SMCI showed WIMDI's strong correlations (r-values up to 0.805) and lower RMSE, indicating superior accuracy. Spatiotemporal validation against aggregated drought indices such as VHI, VDSI, and SDCI, along with time-series analysis, confirmed WIMDI's robustness in capturing drought variability across the OER watershed. These results highlight WIMDI's potential as a reliable tool for effective drought monitoring and management across diverse ecosystems and climates. [ABSTRACT FROM AUTHOR]

African urban agriculture (UA) has garnered attention for its contributions to food security and socio-economic improvement. However, its impact on the psychological well-being of farmers has received minimal focus. This study explores the psychosocial effects of UA by surveying 733 farmers in Dar es Salaam and Greater Lomé. Utilizing the Mental Health Continuum–Short Form (MHC-SF) and bespoke questionnaires, our research evaluates the emotional benefits of urban farming. Findings from regression analyses and spatial assessments conducted using Python and QGIS 3.32.2-Lima indicate significant variations in UA-related happiness across different city zones, with peripheral farmers experiencing greater satisfaction than their urban counterparts. Notably, female farmers reported higher levels of happiness, underscoring UA's potential to empower women. This study advocates for the integration of UA into urban planning frameworks to foster psychologically beneficial urban environments. [ABSTRACT FROM AUTHOR]

Mobility practices in Cameroon have changed considerably due to the rapid spread of COVID-19. Based on data collection in Yaoundé and Douala, the country’s main cities, which combined 878 questionnaires, 11 interviews and direct observation, this research analysed the mobility practices of city dwellers in a crisis context. Its results reveal social coping mechanisms in the face of the fear of contracting COVID-19. The context was marked by a series of aggravating, structural and cultural factors that influenced the choice of modes of daily travel or the option to remain confined. Four types of modal habits were identified, each responding to individual modal logics during the pandemic: users sensitive to the cost of transport, phobic users, local or short-distance users and exclusive circumstantial motorists.

Water distribution systems (WDSs) are complex networks with numerous interconnected junctions and pipes. The robustness and reliability of these systems are critically dependent on their network structure, necessitating detailed analysis for proactive leak detection to maintain integrity and functionality. This study addresses gaps in traditional WDS analysis by integrating hydraulic measures with graph theory to improve sensitivity analysis for leak detection. Through case studies of five distinct WDSs, we investigate the relationship between hydraulic measures and graph theory metrics. Our findings demonstrate the collective impact of these factors on leak detection and system efficiency. The research provides enhanced insights into WDS operational dynamics and highlights the significant potential of graph theory to bolster network resilience and reliability. [ABSTRACT FROM AUTHOR]

This article explores the escalating impact of natural disasters, particularly droughts, in the Southern African Development Community (SADC), with a specific focus on Eswatini. Over the last century, approximately 63 million people in SADC countries have been affected by droughts, leading to challenges in agriculture, livestock losses, and severe food and water shortages. Despite being the smallest SADC nation, the Kingdom of Eswatini faces disproportionate consequences due to its susceptibility to climate variability, particularly drought. The inadequacy and unreliability of rainfall have resulted in a drastic reduction in food production, with maize, a staple crop, experiencing a 70% decline. This adverse trend, spanning three decades, has heightened the vulnerability of farmers to climatic shocks, hindering sustainable agricultural development and impeding poverty alleviation efforts. To address the growing threat of drought in the kingdom, a comprehensive approach is imperative, involving coordinated plans and the development of swift humanitarian relief strategies. This study utilized remote sensing technologies to monitor drought and assess its repercussions, evaluating the impact on agricultural production. Additionally, geospatial tools, including Open Route Service (ORS) and Near Neighbor Analysis algorithms, were employed to optimize humanitarian supply chain logistics. Results from the analysis, including Vegetation Health Index (VHI) fluctuations and drought severity mapping, reveal that 1990 was the year the kingdom was most severely hit by drought. This study also found that smallholder farmers practicing rainfed agriculture in vulnerable regions, such as the lower Middleveld and western Lowveld, suffered the severe socioeconomic consequences of agricultural drought, including income loss, food insecurity, and migration patterns. Through this integrated approach, decision makers can engage in targeted interventions, focusing on farming areas needing irrigation infrastructures or populated areas requiring a coordinated humanitarian response amidst climate variability. [ABSTRACT FROM AUTHOR]

Urban agriculture (UA) is an ancient practice in Africa that meets social- and health-related needs. However, it is unclear whether architects and urban planners have incorporated the topic into their research and practices. This study aimed to assess the scientific contributions of these fields to UA and their relevance compared to other disciplines. The research objectives were to evaluate the trends in the subject, architects' and planners' involvement, and the effects of UA on health in Africa. As a method, a review was conducted using Scopus, PubMed, Web of Science, and Google Scholar. The research query was ("urban agriculture" OR "urban farming") AND Africa AND ("health" OR "global health" OR "urban health"), and the time frame considered was January 2000 to December 2020. Zotero, Mozilla Firefox, Google Chrome, Excel, and VOSviewer were used to collect and analyze metadata. After excluding duplicates, a total of n = 390 articles were involved. The results displayed the mixed health effects of UA, a growing interest in the topic with prominence on food security, and evidence from public health, not architecture and planning. The study recommends more theoretical research on UA by architects, which should be translated into policies and implementation. [ABSTRACT FROM AUTHOR]

This study employs a logistic regression model to offer an in-depth understanding of disparities in the access to essential urban services, specifically focusing on electricity and Internet services, in Nouakchott, Mauritania. Through a comprehensive analysis of demographic, geographic, and socioeconomic data, we identify key determinants of access to these utilities. Our findings reveal that the geographic location within the city, particularly in the western regions, and home ownership, significantly bolster the likelihood of having electricity. Conversely, women are found to be disadvantaged in this regard. For Internet access, income level and education, particularly at the Bachelor's level, emerged as significant predictors. This research not only sheds light on the intricate landscape of service provision in Nouakchott but also offers actionable insights for equitable development. These results empower both policymakers and citizens, marking a step toward transforming Nouakchott into a smarter, more inclusive urban environment. [ABSTRACT FROM AUTHOR]

More and more cities in Southern Africa are struggling to manage their waste in a context of rapid urbanisation and increasing poverty. In the Cameroon's largest city, Yaoundé, managing household waste is a growing concern. The public and the authorities cast blame on each other, and the actions taken by each party far from guarantee an efficient management of household waste, which litters the streets. Considering the above, this paper analyses the socio-political practices of stakeholders and their influence on household waste management in Yaoundé. Based on a qualitative survey that combined both a literature review and interviews, the research analysed the challenges related to household waste management with regard to the economy, the environment, and public health. In addition, a cartographic survey using KoboToolbox was conducted in all seven municipalities to analyse the geographical distribution of the waste areas, their size, and their status within the city organizational framework. In total, 264 waste dumps were collected, of which 110 were formal waste using a waste bin of varying size. Social constructivism, stakeholder theory, and strategic analysis were mobilized to analyse the urban waste governance in Yaoundé. Thus, the poor quality of household waste management in Yaoundé was explained using political, economic, sociocultural, and environmental parameters. The social practices and dynamics of the stakeholders generate undesirable consequences that hinder the achievement of the Sustainable Development Goals (SDGs). By combining social science and engineering methods, this research aims to demonstrate that the shortcomings of waste governance in Yaoundé are both a collective (authorities/public powers) and individual (citizens) matter. [ABSTRACT FROM AUTHOR]

In recent decades, there has been a growing interest in the application of GIS to community empowerment or new policy development through participatory design, information gathering and implementation. This study, therefore, aims to apply a multi-level participatory GIS (PGIS) framework to assess mobility needs and barriers in rural areas from different available transport modes. This assessment was applied to three sub-locations (Lusheya, Khaunga and Mahola) located in the sub-county of Mumias East, Kakamega, Kenya. The study brings two main contributions: (1) an overview of mobility needs and barriers in Sub-Saharan Africa (SSA) and (2) an introduction of a PGIS framework that integrates in-depth local knowledge of rural mobility needs and mobility barriers. This PGIS framework was applied to mobility issues based on three main dimensions: context, process and content. The context in the PGIS framework focuses on identifying the right stakeholders and putting on suitable structures for their training as well as the collection of data. The process considers the collection, analysis and visualization of rural mobility data. The content of the data collected are validated for accuracy in the form of maps and are evaluated for relevance by stakeholders. Local youths with GIS knowledge and digital tools were mobilized along with community people having a solid understanding of the local geographical contexts to collect geographically referenced data related to community resources, transport networks, and mobility barriers. The application of the multi-level PGIS framework has brought to the mainstream daily mobility challenges faced by rural communities in Sub-Saharan Africa. Community members, even those from remote areas, also have access to decision making, reversing the previous structure that strongly relied on often-irrelevant, top-down decision making. [ABSTRACT FROM AUTHOR]

Rural mobility in Africa is an under-researched issue. Rural communities have often suffered from reduced mobility that has hampered their access to essential services and facilities such as education, health care, food, and clean water. In many rural communities, a more affordable mobility option, such as non-motorized mobility (cycling and walking), is the preferred way for people to travel. Apart from its well-known advantages, little is known about the impact of topography and routes on the mobility options adopted by rural communities. Therefore, this study aims to use Digital Elevation Models (DEMs) to analyze the impact of topography and routes on rural mobility patterns at the level of formal and informal cycle track networks in the Bugesera District, focusing on the Nyamata and Mayange sectors, Rwanda. This study used GPS devices given to 50 participants to collect mobility patterns in the two previously mentioned sectors. Then, the study imposed a 30-m buffer on the official road networks of Rwanda collected by the Rwanda Transport Development Agency (RTDA). These data were joined to GPS tracks to highlight official and unofficial roads (tracks that did not fall within the 30-m buffer). In addition, Digital Elevation Models were applied to analyze the SRTM (30 m resolution) and ALOS PALSAR (12.5 m resolution) elevation data of the Bugesera region. The findings revealed an elevation range of 1333 to 1535 for SRTM and 1323 to 1641 for ALOS PALSAR. The study calculated the slope to find the slope percentage (m) and length (m). The findings from the DEMs and the slope calculation revealed that Bugesera has a relatively flat surface, favorable for cycling. The slope percentage was further classified into five levels of slope ranging from steep to very steep. And the Van Zuidam classification results confirmed that Bugesera has "a flat or nearly flat surface, without significant denudation processes". With a favorable topography and a higher bicycle ownership ratio, residents of the Bugesera district favor cycling in their daily activities more than any district in Rwanda. Cycling in Nyamata or Mayange links residents to areas with higher social, educational, administrative, and economic activities. [ABSTRACT FROM AUTHOR]

This article examines the use of multisensor data fusion for land classification in three Moroccan cities. The method employs a Random Forest classification algorithm based on multispectral, synthetic aperture radar (SAR), and derived land surface temperature (LST) data. The study compares the proposed approach to existing datasets on impervious surfaces (Global Artificial Impervious Area—GAIA, Global Human Settlement Layer—GHSL, and Global 30 m Impervious Surfaces Dynamic Dataset—GIS30D) using traditional evaluation metrics and a common training and validation dataset. The results indicate that the proposed approach has a higher precision (as measured by the F-score) than the existing datasets. The results of this study could be used to improve current databases and establish an urban data hub for impervious surfaces in Africa. The dynamic information of impervious surfaces is useful in urban planning as an indication of the intensity of human activities and economic development. [ABSTRACT FROM AUTHOR]

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

With the increase in the amount and variety of data that are constantly produced, collected, and exchanged between systems, the efficiency and accuracy of solutions/services that use data as input may suffer if an inappropriate or inaccurate technique, method, or tool is chosen to deal with them. This paper presents a global overview of urban data sources and structures used to train machine learning (ML) algorithms integrated into urban planning decision support systems (DSS). It contributes to a common understanding of choosing the right urban data for a given urban planning issue, i.e., their type, source and structure, for more efficient use in training ML models. For the purpose of this study, we conduct a systematic literature review (SLR) of all relevant peer-reviewed studies available in the Scopus database. More precisely, 248 papers were found to be relevant with their further analysis using a text-mining approach to determine (a) the main urban data sources used for ML modeling, (b) the most popular approaches used in relevant urban planning and urban problem-solving studies and their relationship to the type of data source used, and (c) the problems commonly encountered in their use. After classifying them, we identified the strengths and weaknesses of data sources depending on several predefined factors. We found that the data mainly come from two main categories of sources, namely (1) sensors and (2) statistical surveys, including social network data. They can be classified as (a) opportunistic or (b) non-opportunistic depending on the process of data acquisition, collection, and storage. Data sources are closely correlated with their structure and potential urban planning issues to be addressed. Almost all urban data have an indexed structure and, in particular, either attribute tables for statistical survey data and data from simple sensors (e.g., climate and pollution sensors) or vectors, mostly obtained from satellite images after large-scale spatio-temporal analysis. The paper also provides a discussion of the potential opportunities, emerging issues, and challenges that urban data sources face and should overcome to better catalyze intelligent/smart planning. This should contribute to the general understanding of the data, their sources and the challenges to be faced and overcome by those seeking data and integrating them into smart applications and urban-planning processes. [ABSTRACT FROM AUTHOR]

Crowdsourcing could potentially have great benefits for the development of sustainable cities in the Global South (GS), where a growing population and rapid urbanization represent serious challenges for the years to come. However, to fulfill this potential, it is important to take into consideration the unique characteristics of the GS and the challenges associated with them. This study provides an overview of the crowdsourcing methods applied to public participation in urban planning in the GS, as well as the technological, administrative, academic, socio-economic, and cultural challenges that could affect their successful adoption. Some suggestions for both researchers and practitioners are also provided. [ABSTRACT FROM AUTHOR]

Summary: Renewable solar energy is one of the most preferable clean energy sources with no environmental impacts. The Marrakech Safi region (Moroccan context), with its arid and semi‐arid climate, can ensure sustainable energy production‐oriented for a green economy. This paper aims to perform a decision analysis using the analysis hierarchical process (AHP) and Fuzzy AHP to identify the suitable areas for potential solar farms. The adopted approaches used 15 factors to produce suitability maps. AHP and Fuzzy AHP were used to minimize the subjectivity related to the factor notation, and to improve the result of the models. The factors' weights were reevaluated using the sensitivity analysis to assess their influence by comparing the theoretical and the effective weights. The final map was validated by overlaying other solar projects implemented in the region. Results show that the suitable areas to host the solar farms cover more than 35% (1300 Ha) of the entire region's surface using AHP and Fuzzy AHP. According to the results, there was no significant difference in Decision‐Making between the two methods in determining the five highest priorities of attributes selection for solar power plants. Moreover, the similarity analysis performed demonstrated that 32% of unequal areas between AHP and Fuzzy AHP can be explained by the factors' weights and the difference of the used approaches. The climatic potential and the geographic location of the study area offer a large suitable area for the installation of solar farms. These findings constitute decision‐making support for solar farm investments in a green economy. [ABSTRACT FROM AUTHOR]

With the rapid urbanization occurring across African cities, the emergence of a middle class is exerting its influence on the urban form and structure. Matching their social status and drawing on global influences, the housing characteristics of this class are distinctive in spatial organization, material choice, and location, among others. Understanding these emerging typologies is critical for urban housing policy to be responsive to the needs and preferences of this class. The present paper aims first to develop a new approach for defining the middle class in the African context and second, to analyze its housing typology through a multidimensional analysis based on housing attributes and socio-economic characteristics in Casablanca City. A data-driven approach based on principal component analysis (PCA) has been used to define multidimensionally the middle class and its housing typology. Through the construction of a multidimensional composite index to measure middle class, the study highlighted that middle-class housing is characterized by an adequate condition, a suitable size (two to three rooms), and affordability between 8000 and 11,000 Moroccan dirhams (MAD) per square meter. In addition, although the Moroccan modern houses (two-floor single-family housing) and apartments (four floors or greater) are the most occupied by the middle class, the study showed that as income and social mobility increase, the apartment building and the villa are increasingly preferred to the Moroccan modern house. [ABSTRACT FROM AUTHOR]

African cities remain little known. As a result, they are outside the global intellectual arena on urban issues, which justifies the need for more productive research. This article aims to empirically analyze the evolution of urban planning studies in Africa, by identifying the trends that characterize scientific production, through a systematic literature review over the last four decades. The study is organized around four different analysis: temporal, thematic, methodological, and geographical, based on 268 journal articles. It highlights major trends in the evolution of this literature. The paper finally discusses important challenges and areas of improvement in African cities research. [ABSTRACT FROM AUTHOR]

Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use and/or land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use and/or land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms: tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent; therefore, they can help promote an understanding of how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use and/or land cover and reference temperature data and can, therefore, be used to evaluate synthetic scenarios such as master plans, urbanization prospects and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies. [ABSTRACT FROM AUTHOR]

Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use/land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use/land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms, i.e., tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent and can therefore help understanding how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use/land cover and reference temperature data and can therefore be used to evaluate synthetic scenarios such as master plans, urbanization prospects, and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies. [ABSTRACT FROM AUTHOR]

Motorcycle taxis operate in a non-regulated, uncontrolled environment, raising public health, environmental and economic issues. Consideration of such issues requires an in-depth understanding of motorcycle taxis’ organizational and operational features. Urban sprawl, a difficult economic context and demographic pressure have led to an increase in motorcycle taxi activities in the Republic of Haiti. This study presents a novel approach to analyzing informal modes of transport using qualitative data from semi-directive interviews and observations with a spatial analysis of motorcycle taxi activities by GPS tracking. The analysis is comprised of three phases. First, a suitable tracking device and fixing method were tested and selected. In the second, 12 drivers were equipped with charged devices on a daily basis. The interviews were conducted simultaneously. Finally, we draw four main results using the Haversine method and calculating the inactivity rate. Given a median action range of <3 km, the lack of peak-hours observed, an inactivity rate of more than 50% and the low profitability of the current structure, the activity’s economic potential is not optimized under the current system. The poor distribution of stands across the territory and large number of drivers results in the overall inefficiency of the system. [ABSTRACT FROM AUTHOR]

The concept of ecosystem services (ES) is regarded as an increasingly important framework and tool to support spatial planning. A limited understanding of how ES knowledge is used in spatial plans constrains our ability to learn from, replicate, and convey an ES approach. This study examined how ES were integrated into spatial planning at the regional scale in Western Switzerland. A directed content analysis of cantonal structural plans was used to assess how ES were covered in various sections of the plans and to explore the differences in the level of ES integration across cantons. First, the results showed that ES were found in each section of the plans but were not equally distributed. Provisioning ES were always the most mentioned while regulating ES were the least considered. Second, strong discrepancies existed between cantons may demonstrate the lack of cantonal coordination to integrate ES. Finally, the concept of ES was more embedded in nonbinding than in binding parts. Promoting the concept at the national level may facilitate the integration of ES at lower planning scales. Further work could focus on other cantons to ensure that the results are fully representative of the current situation in Switzerland. [ABSTRACT FROM AUTHOR]

There is a pressing need for transitional water infrastructures in rapidly growing cities where conventional infrastructures lag behind human settlement expansion. In Kenya, sectoral innovations have addressed local socioeconomic challenges, but empirical evidence on their efficacy (combining quantitative indicators of safety and continuity) is lacking. We addressed this gap by comparing different water infrastructures in their ability to provide constant access to safe water in informal settlements in Nairobi, Kenya. We conducted a cross-sectional survey including 1,147 households in two informal settlements. Water infrastructures were categorized based on their distribution system: 1) piped to premises; 2) piped to a neighboring compound; 3) public tap/dispenser; and 4) street vendor. We tested associations between these systems with two outcomes: constant water availability and diarrhea (stratified by age group). We used adjusted odds ratios (AORs) to test associations between distribution systems and the selected outcomes, while accounting for confounders. Obtaining water from public taps/dispensers or street vendors was associated with service continuity (AOR = 1.45, 95% confidence interval [CI]: 1.06-1.99; AOR = 11.16, 95% CI: 2.45-50.82). Piped sources were associated with service disruption, especially when obtained from a neighboring compound (AOR = 0.45, 95% CI: 0.28-0.70). Public taps/dispensers were the only system consistently associated with lower odds of diarrhea, notably in children under the age of 5 years (AOR = 0.47, 95% CI: 0.29-0.79). Hence, in cities with a high prevalence of informal settlements and limited financial resources, public taps and dispensers hold promise as transitional water infrastructures.

Urban green infrastructure, especially trees, are widely regarded as one of the most effective ways to reduce urban temperatures in heatwaves and alleviate the adverse impacts of extreme heat events on human health and well-being. Nevertheless, urban planners and decision-makers are still lacking methods and tools to spatially evaluate the cooling effects of urban green spaces and exploit them to assess greening strategies at the urban agglomeration scale. This article introduces a novel spatially explicit approach to simulate urban greening scenarios by increasing the tree canopy cover in the existing urban fabric and evaluating their heat mitigation potential. The latter is achieved by applying the InVEST urban cooling model to the synthetic land use/land cover maps generated for the greening scenarios. A case study in the urban agglomeration of Lausanne, Switzerland, illustrates the development of tree canopy scenarios following distinct spatial distribution strategies. The spatial pattern of the tree canopy strongly influences the human exposure to the highest temperatures, and small increases in the abundance of tree canopy cover with the appropriate spatial configuration can have major impacts on human health and well-being. The proposed approach supports urban planning and the design of nature-based solutions to enhance climate resilience., (© 2021 The Authors.)