Suchergebnisse

BACKGROUND: Outbreaks of vector-borne diseases (VBDs) impose a heavy burden on vulnerable populations. Despite recent progress in eradication and control, malaria remains the most prevalent VBD. Integrative approaches that take into account environmental, socioeconomic, demographic, biological, cultural, and political factors contributing to malaria risk and vulnerability are needed to effectively reduce malaria burden. Although the focus on malaria risk has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria risk including malaria vulnerability in a spatial explicit manner. METHODS: Building on a conceptual risk and vulnerability framework, we propose a spatial explicit approach for modeling relative levels of malaria risk - as a function of hazard, exposure, and vulnerability - in the United Republic of Tanzania. A logistic regression model was employed to identify a final set of risk factors and their contribution to malaria endemicity based on multidisciplinary geospatial information. We utilized a Geographic Information System for the construction and visualization of a malaria vulnerability index and its integration into a spatially explicit malaria risk map. RESULTS: The spatial pattern of malaria risk was very heterogeneous across the country. Malaria risk was higher in Mainland areas than in Zanzibar, which is a result of differences in both malaria entomological inoculation rate and prevailing vulnerabilities. Areas of high malaria risk were identified in the southeastern part of the country, as well as in two distinct "hotspots" in the northwestern part of the country bordering Lake Victoria, while concentrations of high malaria vulnerability seem to occur in the northwestern, western, and southeastern parts of the mainland. Results were visualized using both 1010 km(2) grids and subnational administrative units. CONCLUSIONS: The presented approach makes an important contribution toward a decision support tool. By decomposing malaria risk into its components, the approach offers evidence on which factors could be targeted for reducing malaria risk and vulnerability to the disease. Ultimately, results offer relevant information for place-based intervention planning and more effective spatial allocation of resources. ; DK W 1237-N23 ; (VLID)2434615

In the framework of Mine Action, the extent of Suspected Hazardous Areas (SHAs) is often overestimated. This study investigates the potential of Object‐Based Image Analysis (OBIA) for extracting Indicators of Mine Presence (IMP) to support a more precise delineation of SHAs, with the aim of ensuring an optimal use of demining resources. The study area is situated in the Svilaja mountain range in Croatia. Using 3K colour aerial photographs, we implemented two approaches for the extraction of dry stone walls located in an area that displays traces of military activities. The first approach uses object‐based class modelling, which describes an iterative process of segmentation and classification. The second approach implements supervised learning techniques based on advanced statistical classification methods, i.e. Support Vector Machines, Random Forests and Recursive Partitioning. The results are compared, the strengths and limitations of both approaches are discussed, and perspectives for further improvements are considered. ; info:eu-repo/semantics/published

Abstract. Droughts continue to affect ecosystems, communities and entire economies.
Agriculture bears much of the impact, and in many countries it is the most
heavily affected sector. Over the past decades, efforts have been made to
assess drought risk at different spatial scales. Here, we present for the
first time an integrated assessment of drought risk for both irrigated and
rainfed agricultural systems at the global scale. Composite hazard indicators were calculated for irrigated and rainfed systems separately
using different drought indices based on historical climate conditions (1980–2016). Exposure was analyzed for irrigated and non-irrigated crops. Vulnerability was assessed through a socioecological-system (SES) perspective, using socioecological susceptibility and lack of coping-capacity indicators that were weighted by drought experts from around the world. The analysis shows that drought risk of rainfed and irrigated agricultural systems displays a heterogeneous pattern at the global level, with higher risk for southeastern Europe as well as northern and southern Africa. By providing information on the drivers and spatial patterns of drought risk in all dimensions of hazard, exposure and vulnerability, the presented analysis can support the identification of tailored measures to reduce drought risk and increase the resilience of agricultural systems.