Volunteered geographic information in natural hazard analysis : a systematic literature review of current approaches with a focus on preparedness and mitigation

With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural hazard analysis. Our systematic literature review aims at identifying current research and directions for future research in terms of Volunteered Geographic Information (VGI) within natural hazard analysis. Focusing on both the preparedness and mitigation phase results in eleven articles from two literature databases. A qualitative analysis for in-depth information extraction reveals auspicious approaches regarding community engagement and data fusion, but also important research gaps. Mainly based in Europe and North America, the analysed studies deal primarily with floods and forest fires, applying geodata collected by trained citizens who are improving their knowledge and making their own interpretations. Yet, there is still a lack of common scientific terms and concepts. Future research can use these findings for the adaptation of scientific models of natural hazard analysis in order to enable the fusion of data from technical sensors and VGI. The development of such general methods shall contribute to establishing the user integration into various contexts, such as natural hazard analysis

A grounding-based ontology of data quality measures

Data quality and fitness for purpose can be assessed by data quality measures. Existing ontologies of data quality dimensions reflect, among others, which aspects of data quality are assessed and the mechanisms that lead to poor data quality. An understanding of which source of information is used to judge about data quality and fitness for purpose is, however, lacking. This article introduces an ontology of data quality measures by their grounding, that is, the source of information to which the data is compared to in order to assess their quality. The ontology is exemplified with several examples of volunteered geographic information (VGI), while also applying to other geographical data and data in general. An evaluation of the ontology in the context of data quality measures for OpenStreetMap (OSM) data, a well-known example of VGI, provides insights about which types of quality measures for OSM data have and which have not yet been considered in literature

The codification of local knowledges through digital cartographic artefacts: A Case study of the Humanitarian OpenStreetMap Team in Dar es Salaam, Tanzania.

The Humanitarian OpenStreetMap Team, affectionately known as HOT, worked on mapping the city of Dar es Salaam between 2014 and 2020. The efforts of HOT were designed to not only build a map of the city that would ‘put people on the map’, but to also use these maps to aid in development and humanitarian interventions through one of Africa’s fastest growing cities, all while using participatory mapping practices. This thesis examines the extent to which HOT has been able to achieve the creation of a new map of Dar es Salaam, the influence this map had on development projects, and the degree to which the map was built using participatory methods. The research undertook a deep analysis of map completion and accuracy and used interviews to explore the interplay between technology and micro/macro politics around the mapping of Dar es Salaam. Findings suggest that HOT is still underdeveloped as an organization and lacks the maturity to create true participatory models of working. That many of their practices were exclusionary to the local population and that weak management structures and procedures allowed colonial and ‘outsider’ saviour complexes to grow within the organisation. The work concludes by noting that HOT has begun to change many of its practices since 2020 where this research ends

Citizen Science: Reducing Risk and Building Resilience to Natural Hazards

Natural hazards are becoming increasingly frequent within the context of climate change—making reducing risk and building resilience against these hazards more crucial than ever. An emerging shift has been noted from broad-scale, top-down risk and resilience assessments toward more participatory, community-based, bottom-up approaches. Arguably, non-scientist local stakeholders have always played an important role in risk knowledge management and resilience building. Rapidly developing information and communication technologies such as the Internet, smartphones, and social media have already demonstrated their sizeable potential to make knowledge creation more multidirectional, decentralized, diverse, and inclusive (Paul et al., 2018). Combined with technologies for robust and low-cost sensor networks, various citizen science approaches have emerged recently (e.g., Haklay, 2012; Paul et al., 2018) as a promising direction in the provision of extensive, real-time information for risk management (as well as improving data provision in data-scarce regions). It can serve as a means of educating and empowering communities and stakeholders that are bypassed by more traditional knowledge generation processes. This Research Topic compiles 13 contributions that interrogate the manifold ways in which citizen science has been interpreted to reduce risk against hazards that are (i) water-related (i.e., floods, hurricanes, drought, landslides); (ii) deep-earth-related (i.e., earthquakes and volcanoes); and (iii) responding to global environmental change such as sea-level rise. We have sought to analyse the particular failures and successes of natural hazards-related citizen science projects: the objective is to obtain a clearer understanding of “best practice” in a citizen science context

Nature-Based Solutions for Cities

Nature-based solutions (NBS) are increasingly being adopted to address climate change, health, and urban sustainability, yet ensuring they are effective and inclusive remains a challenge. Addressing these challenges through chapters by leading experts in both global south and north contexts, this forward-looking book advances the science of NBS in cities and discusses the frontiers for next-generation urban NBS

Ecology-based planning. Italian and French experimentations

This paper examines some French and Italian experimentations of green infrastructures’ (GI) construction in relation to their techniques and methodologies. The construction of a multifunctional green infrastructure can lead to the generation of a number of relevant bene fi ts able to face the increasing challenges of climate change and resilience (for example, social, ecological and environmental through the recognition of the concept of ecosystem services) and could ease the achievement of a performance-based approach. This approach, differently from the traditional prescriptive one, helps to attain a better and more fl exible land-use integration. In both countries, GI play an important role in contrasting land take and, for their adaptive and cross-scale nature, they help to generate a res ilient approach to urban plans and projects. Due to their fl exible and site-based nature, GI can be adapted, even if through different methodologies and approaches, both to urban and extra-urban contexts. On one hand, France, through its strong national policy on ecological networks, recognizes them as one of the major planning strategies toward a more sustainable development of territories; on the other hand, Italy has no national policy and Regions still have a hard time integrating them in already existing planning tools. In this perspective, Italian experimentations on GI construction appear to be a simple and sporadic add-on of urban and regional plans

Broad-scale flood modelling in the cloud : validation and sensitivities from hazard to impact

Broad-scale flood modelling is a growing research area with applications in insurance, adaption and response. This has been fuelled by increasing availability of continental-global datasets providing inputs to a mounting array of models. However, outputs vary greatly and validation is challenging. This research developed a novel, consistent methodology for assigning performance scores to models using a range of gridded datasets and an accurate numerical 2D hydrodynamic modelling system. Validation using both extent and discharge was conducted for Storm Desmond in Northern England and the global applicability of the methodology demonstrated across Europe and in Indonesia. To meet computational demands, a cloud computing framework was implemented using a PostgreSQL database. Visualisation of results was achieved using a newly designed web interface. Finally OpenStreetMap data was overlaid to demonstrate the sensitivity of impacts to flood model inputs. The main findings are that relative importance of precipitation and topographic data changes depending on the metrics used for validation. More variability in peak discharge error was found between models using different rainfall inputs (22-70%) than different DEMs (9-37%). Conversely, flood extent critical success index (CSI) was more sensitive to the choice of topography (25-32%) than rainfall (27-30%), though overall variability in CSI was low. This was echoed in the impacts analysis with higher sensitivity of feature inundation to topography than rainfall. Importantly, there was far more overall variability in discharge accuracy than extent which indicates that reproduction of peak discharge is a more powerful measure for assessing model performance. Models driven by globalcontinental precipitation products underestimated peaks more than those using Met Office rain gauge data, though better performance was demonstrated by replacing ERA-Interim with the updated ERA5 dataset. The research highlights a growing need for more robust validation of broad scale flood simulations, and the difficulties this presents. Strong influence of dataset choice on infrastructure inundation has consequences for insurance premiums, development planning and adaptation to climate change risks which should not be ignored.NERC for funding the research through the Data, Risk and Environmental Analytical Methods (DREAM) training centre