Technical assistance and training on spatial population modelling to support census processes in Thailand - Phase II
Project lead: Chris Nnanatu
Team: Natalia Tejedor Garavito, Assane Gadiaga, Alexandra Frosch
Funding: UNFPA
Start: Sep 2023
Completion: Dec 2023
Building on last years’ successful engagement with the Thailand National Statistical Office (TNSO), our team are providing a further tranche of support and training, comprising initial online training in Basic R programming and GIS skills followed by in-person training in Thailand in GIS and Statistical Modelling Skills in R.
The focus of the in-person training will be to further strengthen the capacity of the TNSO staff on the development and implementation of advanced spatial hierarchical population modelling methods within Bayesian inference framework. The workshop will feature practical exercises on bespoke population modelling approaches and GIS skills as well as co-design and co-development of the various methodological frameworks required to address the population data needs of Thailand. Ultimately, this will lead to the co-production of key population estimates including very detailed population estimates required for the construction of an updated national sampling frame for Thailand in preparation to the upcoming population and housing census in 2025.
About Us
The WorldPop research programme, based in the School of Geography and Environmental Sciences at the University of Southampton, is a multi-sectoral team of researchers, technicians and project specialists that produces data on population distributions and characteristics at high spatial resolution.
Initiated in October 2013 to combine The AfriPop Project, AsiaPop and AmeriPop projects, we have a diverse portfolio of projects, including large multi-million-pound collaborative projects with partner organisations, commercial data providers and international development organisations.
WorldPop develops and publishes open, high-resolution population datasets to support social, economic, and environmental development, humanitarian response, and the Sustainable Development Goals. This data is not intended, and should not be used, for purposes that discriminate against, exploit, surveil, or otherwise harm individuals or vulnerable populations; users are expected to apply it responsibly, assess the risks of their own analyses (particularly when combining it with other datasets) and are solely responsible for how they use it.
