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 rise in the number of flood-affected people and areas has increased the interest in new methods and concepts that account for this change. Citizens are integrated into disaster risk reduction processes through participatory approaches and can provide valuable up-to-date local knowledge. During a field study in Eberbach (Baden–Wuerttemberg, Germany) sketch maps and questionnaires were used to capture local knowledge about flooding. Based on a previous study on urban flooding in Santiago de Chile, the tools were adapted and applied to river flooding in the city of Eberbach, which is regularly flooded by the Neckar River, a major river in southwest Germany. The empirical database of the study comprises 40 participants in the study area and 40 in a control area. Half of the participants in each group are residents and half are pedestrians. Purposive sampling was used, and the questionnaires aimed to gather demographic information and explore what factors, such as property, influence the risk perception of the study participants. The results show that residents identify a larger spatial area as at risk than pedestrians, and owning property leads to higher risk awareness. The flood type influenced the choice of the base maps for the sketch maps. For river flooding, one map with an overview of the area was sufficient, while for urban flooding a second map with more details of the area also enables the marking of small streets. The information gathered can complement authoritative data such as from flood models. This participatory approach also increases the communication and trust between local governments, researchers, and citizens.

OpenStreetMap (OSM) currently represents the most popular project of Volunteered Geographic Information (VGI): geodata are collected by common people and made available for public use. Airborne Laser Scanning (ALS) enables the acquisition of high-resolution digital elevation models that are used for many applications. This study combines the advantages of both ALS and OSM, offering a promising new approach that enhances data quality and allows change detection: the mainly up-to-date 2D data of OSM can be combined with the high-resolution – but rarely updated – elevation information provided by ALS. This case study investigates building objects of OSM and ALS data of the city of Bregenz, Austria. Data quality of OSM is discerned by the comparison of building footprints using different true positive definitions (e.g. overlapping area). High quality of OSM data is revealed, yet also limitations of each method with respect to heterogeneous regions and building outlines are identified. For the first time, an up-to-date Digital Surface Model (DSM) combining 2D OSM and ALS data is achieved. A multitude of applications such as flood simulations and solar potential assessments can directly benefit from this data combination, since their value and reliability strongly depend on an up-to-date DSM.

The fact that an increasing number of people and local authorities are affected by natural hazards, especially floods, highlights the necessity of adequate mitigation and preparedness within disaster management. Many governments, though, have only insufficient monetary or technological capacities. One possible approach to tackle these issues is the acquisition of information by sketch maps complemented by questionnaires, which allows to digitally capture flood risk perception. We investigate which factors influence information collected by sketch maps and questionnaires in case studies in an area prone to pluvial flooding in Santiago de Chile. Our aim is to gain more information about the methods applied. Hereby, we focus on the spatial acquisition scale of sketch maps and personal characteristics of the participants, for example, whether they live at this very location of the survey (residents) or are pedestrians passing by. Our results show that the choice of the acquisition scale of the base map influences the amount and level of detail of information captured via sketch maps. Thus, detail base maps lead to more precise results when compared to reference data, especially in the case of residents. The results also reveal that the place of living of the respondents has an effect on the resulting information because on the neighborhood level the risk perception of residents is more detailed than the one of pedestrians. The study suggests that the integration of citizens via sketch maps can provide information about flood risk perception, and thus can influence the flood mitigation in the area.