Assessing equity in disaster risk governance (DRG) policies

This dataset relates to the code and data for analysing equity in disaster risk governance (DRG) policies produced during the analysis for Ulbrich et al. (2023). The dataset includes Taguette (free and open text analysis software) code, and the results (.xls

Application of an object-based verification method to ensemble forecasts of 10‑m wind gusts during winter storms

The object-based method SAL (Structure, Amplitude and Location) was adapted for investigating the errors of forecasts of extreme 10‑m wind gusts associated with winter storms in Germany. It has been applied to a statistically downscaled version of the 51 member ECMWF (European Centre for Medium Range Weather Forecasts) operational ensemble forecast. The horizontal resolution of both downscaled data and of the German weather service's operational analysis data used for verification is 7 km. Forecast errors are subdivided in terms of storm intensity, location and extent. After identifying a set of storm events, objects of moderate and intense 10‑m wind gusts were identified with a local percentile-based threshold (90th percentile for moderate and 98th percentile for intense gust objects). Depending on the intensity of the storm, the gust objects differ in terms of size, shape and intensity. The characteristics of the ensemble forecasts of 10‑m wind gusts can basically be assessed in two different ways. Individual forecast members can be evaluated with respect to the location, intensity and extent of the gust field, and then address the ensemble characteristics by the score distributions. Alternatively, the gust fields' location, intensity and extent can be evaluated by directly using the ensemble mean forecast instead of the individual members. The results of the identified set of storms clearly indicate a high case-to-case variability in the predictability of 10‑m wind gusts objects, particularly when focusing on the structure of intense wind gust objects. It is found, that the gust fields' location and overall intensity can be better estimated from the ensemble mean forecast, compared to the individual forecast members. From a forecaster's perspective this means, that a storms' location and intensity can be well estimated by considering the ensemble mean wind forecasts. Considering the structure of the gust objects, results are different. While for longer lead times, there also seems to be a benefit from applying ensemble averaging, at short lead times the ensemble mean forecast performs equally or worse than most of the individual forecast members. The amplitude error is often the smallest component of the three error types. The findings are particularly relevant when deriving warning information, by giving guidance to forecasters when interpreting ensemble forecasts for severe storms

Locating the sustainability and resilience multiple : a cross-scalar case study of the transformative impacts of Sustainable Development Goal 11 localisation

There is little doubt about the correlation between hazard exposure, and urban marginality and informality. Recent global development and risk reduction frameworks, such as the 2015 Sustainable Development Goals (SDGs) and Sendai Framework for Disaster Risk Reduction, encourage urban policymakers to address this risk-development nexus by integrating policy siloes and develop interventions that simultaneously promote social and environmental justice. Localised implementation of such globally defined policy goals, notably through participatory exercises with community members and other stakeholders, was an integral methodological aspect of these frameworks. Yet, the localisation approach for the implementation of policies and interventions is not mirrored in monitoring progress towards achieving those goals. Currently, the tendency to rely on centrally defined methods and concepts for monitoring, easily measurable proxies and centrally produced datasets with little meaningful community engagement limits the extent to which evaluation of implementation is transformative at the neighbourhood level. Such a fragmented view of risk reduction and urban development in turn perpetuates intra-urban inequalities. This problem is exacerbated in many cities in the global South where rapid and informal urbanisation processes where risk and intersecting inequalities are highly correlated, and with adopted monitoring approaches commonly based on western conceptualisations and assumptions. As a result, monitoring is not informed by local knowledge and misses opportunities to recalibrate and enhance the frameworks’ local relevance. Moving from the global to the local scale, and based on interviews with global, national and municipal monitoring stakeholders, detailed discussions with community leaders and observational research in three neighbourhoods in Medellín, this thesis investigates how global urban development and resilience monitoring frameworks are localised, and unpacks the extent to which they have resulted in a representative and inclusive picture of urban marginalised communities’ situation in terms of sustainable development and resilience. Overall, the study has produced a set of methodological factors to consider when implementing such monitoring frameworks at the different scales, alongside a surfacing of approaches that might enhance the ability to meaningfully and dialogically translate between the different monitoring scales and strengthen context-relevant and endogenous resilience

Towards a participatory methodology for community data generation to analyse urban health inequalities : a multi-country case study

This paper presents results from the application of a methodological framework developed as part of an ongoing research project focused on understanding inequalities in the healthcare access of slum residents of cities in four countries: Bangladesh, Kenya, Pakistan and Nigeria. We employ a systematic approach to produce, curate and analyse volunteered geographic information (VGI) on urban communities, based on a combination of collaborative satellite-imagery digitization and participatory mapping, which relies upon geospatial open-source technologies and the collaborative mapping platform OpenStreetMap. Our approach builds upon and extends humanitarian mapping practices, in order to address the twofold challenge of achieving equitable community engagement whilst generating spatial data that adheres quality standards to produce rigorous and trusted evidence for policy and decision making. Findings show that our method generated promising results both in terms of community engagement and the production of high-quality data on communities to analyse urban inequalities

Towards a Participatory Methodology for Community Data Generation to Analyse Urban Health Inequalities: A Multi-Country Case Study

This paper presents results from the application of a methodological framework developed as part of an ongoing research project focused on understanding inequalities in the healthcare access of slum residents of cities in four countries: Bangladesh, Kenya, Pakistan and Nigeria. We employ a systematic approach to produce, curate and analyse volunteered geographic information (VGI) on urban communities, based on a combination of collaborative satellite-imagery digitization and participatory mapping, which relies upon geospatial open-source technologies and the collaborative mapping platform OpenStreetMap. Our approach builds upon and extends humanitarian mapping practices, in order to address the twofold challenge of achieving equitable community engagement whilst generating spatial data that adheres quality standards to produce rigorous and trusted evidence for policy and decision making. Findings show that our method generated promising results both in terms of community engagement and the production of high-quality data on communities to analyse urban inequalities

Slum health mapping as catalyst for a collaborative agenda for research, practice, local citizens and volunteers

Background and purpose. Following the paradigmatic examples of the use of OSM for crisis mapping, there have been sustained efforts to use OSM for mapping preventively vulnerable communities in the global South. This includes, for instance, participatory mapping in the slums of sub-Saharan Africa (Hagen, 2017) and the Missing Maps project. Researchers have also started to study these mapping activities (e.g. Albuquerque et al. 2016; Herfort et al. 2017). However, a collaborative agenda in this area is missing that is able to reflect views and needs of researchers, OSM volunteers, humanitarian organisation practitioners and local communities. Methodology and Findings. After a brief review of existing methods used for mapping disadvantaged communities and slums, we introduce the approach and report on preliminary results from an ongoing large-scale project (NIHR Global Health Unit on Improving Health in Slums), which uses OSM for mapping slums in five cities: Dhaka (Bangladesh), Karachi (Pakistan), Nairobi (Kenya), Ibadan and Lagos (Nigeria). Our methods are based on the combination of satellite imagery digitisation with ground-truthing and participatory mapping. The maps produced will result in enhanced information regarding environmental features of the slums and the location of healthcare facilities, which will also be used as a basis for the health-science surveys of the project. In this manner, our approach is aimed at achieving a threefold goal: (a) participation and inclusion of local stakeholders as a strategy to build resilience; (b) worldwide collaboration, connecting to the global Humanitarian OSM network and student mapping societies; (c) quality evaluation mechanisms for generating high-quality data that can also be used for scientific research. Final discussion/Impact. We would like to discuss the approach and results of our project as a basis to invite OSM researchers, practitioners and volunteers to join us in defining a collaborative agenda towards improving methods and practice for mapping vulnerable communities in OSM. This should include challenges from an interdisciplinary perspective that account for technical, methodological, social and ethical issues. As a result, we would like to contribute to the emergence of an OSM research agenda that goes beyond solely using OSM geographic data for research, but also includes ways of engaging the OSM community and local communities in the research process

Assessing equity in disaster risk governance in Brazil and Colombia

Purpose Disasters continue to be most prevalent and severe for marginalised communities. To reach those furthest behind first, as the global community pledges in the 2030 Agenda, a critical assessment of equity in disaster risk governance is necessary. Yet, the understanding of factors that mediate the capacity of the governance processes to achieve equity ambitions is limited. This paper addresses this gap by proposing and testing a conceptual framework to assess equity in disaster risk governance. Design/methodology/approach The framework analyses the extent to which institutional relationships and data in risk governance support inclusion and diversity of voice and enable the equitable engagement of communities. The study applied the framework to key risk policies across governance levels in Brazil and Colombia. Findings The study finds that institutional awareness of cross-sectoral and -scalar coordination clearly exists. Yet, the engagement of actors further down the governance scale is framed reactively at all scales in both countries. The analysis of the risk data practices indicates that although data integration and sharing are key policy priorities, the policies frame the relations of disaster risk data actors as hierarchical, with data needs determined from the top down. Originality/value A key contribution of this framework is that its equity view results in a nuanced analysis, thus pointing to the differences between the two countries concerning the factors that mediate these challenges and providing specific entry points for strengthening equity in risk governance policies

Cartographic resources for equitable university-community interaction in slum areas

Cartographic resources play a crucial role in facilitating communication across various sectors, including research projects focused on low-income communities. Despite this, some researchers still adhere to colonialist and exploitative approaches. This study aims to promote equitable university–community interaction though cartographic resources, aid academic and vulnerable community users in choosing a better platform for their work, and provide insights to developers for improving the platforms to better serve the user profiles of community members. To achieve this, we examined the use of cartographic resources in five projects within low-income communities (commonly referred to as favelas or so-called “slums”) in three Brazilian cities, all guided by equitable principles. The study unfolds in four stages: (i) data collection from documents and interviews; (ii) systematization into seven analytical categories—cartographic resources, data, personnel, processes, equipment, general objectives, and specific objectives; (iii) analysis of eight cartographic resources; and (iv) a critical examination of the outcomes. The synthesis of the collected information identified 65 characteristics/demands, with 17 common to all projects, including vector feature creation, thematic map design, printed map usage, and satellite imagery. We also identified 53 geographic information system (GIS) functionalities required for the projects, predominantly related to vector data generation and editing. The outcomes demonstrate the benefits of project methodologies, contributing to a decolonial university–community praxis. Additionally, they underscore the potential of digital cartographic resources, functioning not solely as data collection tools but also as powerful instruments that empower slum residents to advocate for improvements and foster local development

Understanding climate change projections for precipitation over western Europe with a weather typing approach

Precipitation over western Europe (WE) is projected to increase (decrease) roughly northward (equatorward) of 50°N during the 21st century. These changes are generally attributed to alterations in the regional large-scale circulation, e.g., jet stream, cyclone activity, and blocking frequencies. A novel weather typing within the sector (30°W–10°E, 25–70°N) is used for a more comprehensive dynamical interpretation of precipitation changes. A k-means clustering on daily mean sea level pressure was undertaken for ERA-Interim reanalysis (1979–2014). Eight weather types are identified: S1, S2, S3 (summertime types), W1, W2, W3 (wintertime types), B1, and B2 (blocking-like types). Their distinctive dynamical characteristics allow identifying the main large-scale precipitation-driving mechanisms. Simulations with 22 Coupled Model Intercomparison Project 5 models for recent climate conditions show biases in reproducing the observed seasonality of weather types. In particular, an overestimation of weather type frequencies associated with zonal airflow is identified. Considering projections following the (Representative Concentration Pathways) RCP8.5 scenario over 2071–2100, the frequencies of the three driest types (S1, B2, and W3) are projected to increase (mainly S1, +4%) in detriment of the rainiest types, particularly W1 (−3%). These changes explain most of the precipitation projections over WE. However, a weather type-independent background signal is identified (increase/decrease in precipitation over northern/southern WE), suggesting modifications in precipitation-generating processes and/or model inability to accurately simulate these processes. Despite these caveats in the precipitation scenarios for WE, which must be duly taken into account, our approach permits a better understanding of the projected trends for precipitation over WE