EO to support climate-related health risk assessment in Africa
Datasets of environmental data are now available globally and with long time series, allowing an intensive data mining and use. It is possible to access about 100TB (more than 60 collections) of data in real time and a multi-scale analysis of the climate-health relationship. EOCHA Portal - Earth Observation for Climate-related Health risk in Africa- will collect meteorological and climate parameters from heterogeneous data sources (satellite, in-situ, model) fully dedicated to climate-health analysis. The Earth Observation data will be associated with epidemiological data (information about diseases, outbreaks and other kind of social-health data) to analyze the impact and the cause-effect dynamics that link meteo-climate parameters which are observable from space to human and animal health.The platform will collect information to address the occurrences and spread of four diseases: Rift Valley Fever, Epidemic malaria, Meningitis and Chikungunya which were selected based on their prevalence in East Africa (Ethiopia, Kenya and Uganda) and the availability of consolidated EO products such as temperature. soil moisture, NDVI, rainfall, Sea Surface Temperature, land cover, water bodies and more. The EOCHA portal provides access to time series of satellite observations, numerical model simulations and in-situ observations. The project has developed an API allowing European EO datasets to be accessed through the World Bank’s Climate Change Knowledge Portal (http://climateknowledgeportal.worldbank.org). Two European EO datasets: Sea-Level anomaly data (from the ESA Climate Change Initiative) and Sea-Surface Temperature (from the Group for High-Resolution Sea Surface Temperature – GHRSST) were integrated to enhance data availability. |
Technical Officer: Pierre-Philippe Mathieu |
Starting Date: 2014-05-19 |
Suppliers: Meteorological and Environmental Earth Observation as supplier - prime |
Users: World Bank as user - partner/collaborator |
Services: climate variables monitoring (Meteorological) |