Catherine Linard graduated in Geographical Sciences at the Université catholique de Louvain (UCL), Belgium, in 2005. She completed her PhD thesis on spatial and integrated modelling of complex disease systems at the Department of Geography of the UCL in January 2009 and was then visiting researcher for 4 months at the department of Zoology (TALA research group), University of Oxford. She was then a post-doctoral fellow of the Wiener-Anspach Foundation for two years at the Department of Zoology of the University of Oxford, f ollowed by four years (2011-2015) as post-doctoral fellow of the Fonds National de la Recherche Scientifique (FNRS, Brussels, Belgium) at the Université libre de Bruxelles (ULB). She is now sharing her time between an half-time academic position at the department of Geography of the University of Namur and a half-time researcher position at the ULB.
Catherine's main projects are
- AfriPop/WorldPop: Fine resolution settlement and human population mapping for Africa (Wiener-Anspach Foundation, 2009-2011). [www.afripop.org]
- MAUPP: Modelling and forecasting African Urban Population Patterns for vulnerability and health assessments [maupp.ulb.ac.be]
- EDEN: Emerging Diseases in a changing European eNvironment (European Commission, 6th Framework Programme, 2005-2009). [http://www.eden-fp6project.net/]
Open population data for human and animal health, Thursday 10 December 2015
High spatial resolution data on the geographical distribution of populations have countless uses ranging from epidemics modelling to disaster management and environmental impact assessment. People and livestock also have a profound impact on the environment, which can be spatially informed thanks to high quality data on their number and distribution. Since several years, two different projects have aimed to collect, integrate and redistribute spatial data on people and livestock at continental and global scale. The Worldpop project initially aimed to process and disseminate human population spatial data in developing countries at a 100m spatial resolution, and has now expanded to distribute data on human movement patterns. The gridded livestock of the world (GLW) project was initiated by FAO and now covers six livestock species, at a global extent, and a spatial resolution of 1 km per pixel. Since their origin, both projects have adopted an Open data approach, and have been extensively used in epidemiological, environmental and socio-economic applications.