BackgroundSpatial accessibility to healthcare is a critical factor in ensuring equitable health outcomes. While studies on a global, continental, and national level exist, our understanding of intra-urban differences, particularly between formal and informal areas within cities in sub-Saharan Africa, remains limited.MethodsThis study integrates openly available datasets on land use in 19 sub-Saharan cities, healthcare facilities in the region, and street networks from OpenStreetMap. Using these datasets, we calculate service areas around hospitals, considering travel times ranging from 1 to 120 minutes with walking as the mode of travel. The resulting service areas are then merged with population data from WorldPop, allowing us to assess the proportion of the population with specific travel times to healthcare facilities from informal and formal residential areas.ResultsOur analysis reveals that 33% of the urban population can reach hospitals within 15 minutes, 58% within 30 minutes, and 78% within 60 minutes. Importantly, for some cities, we observe significant differences between formal and informal areas, with informal areas experiencing a disadvantage in terms of spatial accessibility to healthcare facilities. The population in informal areas is particularly disadvantaged in medium-sized cities.ConclusionsThis study sheds light on the spatial accessibility of healthcare facilities in sub-Saharan African cities, emphasizing the need to consider intra-urban disparities, particularly in informal areas. The findings underscore the importance of targeted interventions and urban planning strategies to address these disparities and ensure that healthcare services are accessible to all segments of the urban population.

Monitoring change in informal settlements remains a critical challenge, particularly in data-scarce contexts across the Global South. While satellite remote sensing provides strong temporal coverage, conventional approaches for mapping the built environment often rely on very high-resolution imagery or LiDAR, which lack consistent temporal availability and are costly to scale especially for capturing vertical growth. This study leverages Google’s Open Buildings 2.5D Temporal Dataset (2016-2023), which offers annual estimates of building presence, count, and height, to detect structural change in Nairobi, Kenya. By analysing differences in building count and average height across 100-meter grid cells, we developed a rule-based framework to identify four key transformation types: vertical densification, horizontal densification, combined densification (increase in both count and height), and decline. To our knowledge, this is the first study to use this dataset to assess vertical change within informal settlements. Validation was conducted through a two-source approach using historical satellite imagery (Google Earth Pro) and archival street-level imagery (Google Street View). A total of 154 grid cells across 13 slum areas were manually assessed, yielding an overall accuracy of 96.75%. Horizontal and combined densification showed perfect agreement, while vertical densification and decline categories had over 80% accuracy. Spatial analysis across slums, adjacent buffer areas, and the broader city revealed horizontal densification as the dominant trend within informal settlements, while vertical and combined growth were more prominent in surrounding zones. These results demonstrate the potential of Google’s 2.5D dataset for scalable, interpretable urban monitoring in rapidly changing environments.

This chapter presents a concise synthesis of recent research efforts, emphasizing the combined use of ecosystem services and landscape metric concepts for quantifying provision, quality, and accessibility to ecosystem services as indicators of socio-ecological well-being in deprived urban areas in the Majority World. Such analyses are challenging due to the common lack of official and reliable data related to socioeconomic, demographic, ecological, and land use/land cover variables. The recommended analytical steps leverage freely available earth observation products with global coverage, requiring no proprietary software and enabling barrier-free application. Integration of readily available data sets is possible during image classification, post-processing, and ensuing spatio-ecological evaluation. The study highlights the importance of differentiating between ecosystem functions and services and separating land use from land cover to ensure accurate attributions. Additionally, incorporating spatial and temporal aspects, as well as considering beneficiaries, is essential for assessing ecosystem services. Local stakeholder and community interactions are advised to gain a comprehensive understanding of the local context. Future research should explore challenges associated with sustainable management of ecosystem service provision areas in densely populated informal settlements. This includes prioritizing specific services, developing tailored valuation approaches, and quantifying the influences of landscape configuration and composition. Addressing discrepancies between actual and intended land use remains critical for advancing the understanding of ecosystem services in urban environments. This approach underscores the importance of leveraging remote sensing data and fostering local stakeholder engagement for effective ecosystem service management in deprived urban areas.

Accurate population data is crucial for assessing exposure in disaster risk assessments. In recent years,there has been a signifcant increase in the development of spatially gridded population datasets.Despite these datasets often using similar input data to derive population fgures, notable diferencesarise when comparing them with direct ground-level observations. This study evaluates the precisionand accuracy of food exposure assessments using both known and generated gridded populationdatasets in Sweden. Specifcally focusing on WorldPop and GHSPop, we compare these datasetsagainst ofcial national statistics at a 100 m grid cell resolution to assess their reliability in foodexposure analyses. Our objectives include quantifying the reliability of these datasets and examiningthe impact of data aggregation on estimated food exposure across diferent administrative levels.The analysis reveals signifcant discrepancies in food exposure estimates, underscoring the challengesassociated with relying on generated gridded population data for precise food risk assessments.Our fndings emphasize the importance of careful dataset selection and highlight the potential foroverestimation in food risk analysis. This emphasises the critical need for validations against groundpopulation data to ensure accurate food risk management strategies.

The concept of vulnerability has obtained increased research interest due to the ongoing climate change. The concept has a broad and general meaning which makes it necessary to specify what it actually means in any specific context. In exposure to climate risks, it is important to highlight who and what is vulnerable to climate-related hazards. The concept of social vulnerability derives from ongoing research in disaster, developmental, and socio-geographic sciences. Social vulnerability emphasises the social dimension of vulnerability and how different factors in interaction contribute to influence who is vulnerable. This scoping review is part of a larger project that aimed at increasing the understanding of social vulnerability in a Swedish and Nordic context. The review explores what Nordic literature on vulnerability related to climate hazards has identified as relevant for social vulnerability. 32 articles were included and underwent content analysis. The analysis process was characterised by the involvement of the project group in an iterative cross-disciplinary approach to the topic. This study concludes that social vulnerability is a dynamic process in both time and space; the degree of spatial resolution of vulnerability assessments impacts the possibility to detect vulnerable groups; it is in the combination of factors that social vulnerability emerges; and that the finding of risk perception re-emphasises the agency of the individual. 

Background: Closing delivery units increases travel time for some women. Whether increased travel time is associated with maternal outcomes is important for understanding the consequences of such closures. Previous studies are limited in measuring travel time and restricted to the outcome of caesarean section. Methods: Our population-based cohort includes data from the Swedish Pregnancy Register for women giving birth between 2014 and 2017 (N = 364,630). We estimated travel time from home to the delivery ward using coordinate pairs of actual addresses. The association between travel time and onset of labour was modelled using multinomial logistic regression, and logistic regression was used for the outcomes postpartum haemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Findings: Over three-quarters of women had ≤30 min travel time (median 13.9 min). Women who travelled ≥60 min arrived to care sooner and laboured there longer. Women with further to travel had increased adjusted odds ratio (aOR) of having an elective caesarean section (31–59 min aOR 1.11; 95% confidence interval [CI] 1.07–1.16; ≥60 min aOR 1.25; 95% CI 1.16–1.36) than spontaneous onset of labour. Women (at full term with spontaneous onset) living ≥60 min away had reduced odds of having a PPH (aOR 0.84; 95% CI 0.76–0.94) or OASIS (aOR 0.79; 95% CI 0.66–0.94). Interpretation: Longer travel time increased the odds of elective caesarean section. Women with furthest to travel arrived sooner and spent more time in care; although they had a lower risk of PPH or OASIS, they also tended to be younger, have a higher body mass index and were Nordic born. 

Cloudburst flash floods cause big casualties and economic losses. This study primarily investigated if a cloudburst catastrophe (cat) model could be constructed to meaningfully assess such a hazard, exposure and vulnerability in Swedish urban context. Rainfall intensity was used directly as hazard measure, bypassing hydraulic water-level modelling, to predict vulnerability. The Splash (Swedish pluvial modelling analysis and safety handling) cloudburst-disaster model was constructed using the Oasis Loss Modelling Framework, and was based on individual property values and building locations, property-level insurance-loss data, high-resolution geographical data, and rainfall data from a dense municipal gauge network in the city of Jönköping. One major cloudburst event was used to derive a vulnerability curve. The following two events were used for validation and supported the hypothesis that the vulnerability curve changed with time because of municipal flood-risk-reduction measures after the first event. A faulty rain gauge during the first event, replaced by a trustworthy private gauge, clarified the very high sensitivity to cloudburst input. Given the limited amount of loss data, our results were uncertain but they pointed towards possible ways to further this study with other loss data at other locations, possibly using more easily available aggregated loss data. We concluded that a cat model based only on rainfall intensity provided acceptable results, thus providing an opening for future, simplified cloudburst cat models applicable in most geographical contexts where reliable cloudburst data are available, especially in cities with limited topographic data and hydraulic-modelling capacity.

Rapid urbanization in developing countries often results in uncontrolled urban growth. In order to support sustainable urban development, reliable and up-to-date information on urban land cover changes and their environmental impact is needed. In this study, we aim at evaluating the potential of Sentinel-2 (S-2) Multi-spectral Instrument (MSI) data for urban land cover change monitoring and for analyzing resulting impacts on Ecosystem Services (ES) provision in Kigali, Rwanda. Land cover classification into eight distinct urban classes (84% overall accuracies, 0.8 Kappa) was performed on data from 2016 and 2021 using a hybrid approach combining Random Forest with a U-Net-based impervious surface segmentation that improved the delineation of urban areas. The bi-temporal land cover maps were then analyzed regarding landscape structure using Landscape Metrics (LM). Ecosystem service bundles were derived for both years and their changes were summarized. Service providing areas were further evaluated in terms of changes in spatial attributes and structure of patches. ES were aggregated into eight bundles and grouped into provisioning, regulating and supporting services. The bundles were further analyzed using a matrix spatially linking landscape units with service supply and demand budgets. The results illustrated that three urban development scenarios can be distinguished including infill through housing and infrastructures development in core urban areas, urban sprawl in fringe zones and the development of urban patches at distant locations intercepted by cropland. The results revealed that the changes in LM negatively affected ES supply mainly through a decrease in cropland and forest. The expansion of built-up areas resulted in a high demand for provisioning and regulating services, especially food and water provision, surface runoff mitigation and erosion control. This is the first study demonstrating that detailed monitoring of urbanization and resulting environmental impacts can be performed with open access S-2 MSI data in Sub-Saharan Africa. Moreover, the framework developed in this study has the potential to be transferred to other Sub-Saharan cities.

Denna rapport, som redovisar del 2 av projektet Social sårbarhet för klimatrelaterade hot, syftar till att ta fram ett generellt sårbarhetsindex för Sverige, men också specifika index för tre olika naturhot: översvämning (älv respektive kust), skogsbrand och ras/skred/erosion. För dessa specifika index har sårbarheten kombinerats med en bedömd exponering för de tre olika hoten. Analysen är gjord på kommun- och RegSO-nivå.

Att förstå och sätta mått på sårbarheter hos människor och samhälle är centralt för att reducera risker. I denna rapport utforskas social sårbarhet för olika klimathot i Norden i tre delar: en litteraturstudie av den vetenskapliga kunskapen i en nordisk kontext, en sammanställning av grå litteratur inom området, och ett speciellt fokuskapitel som belyser rättvisedimensionen kopplat till social sårbarhet.