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Research project

Integrating geospatial covariate capture and statistical processing in R to estimate extreme poverty

Project overview

To develop a geospatial back end for integration within the Estimating and Mapping Disaggregated Indicators (EMDI) package in the R statistical computing environment

Staff

Lead researcher

Dr Christopher Lloyd MSci, MSc, PhD, FGS

Senior Research Fellow

Research interests

  • GIS and Remote Sensing
  • Open Source Geospatial Tools
  • Building Classification using Machine Learning
Connect with Christopher

Email: C.T.Lloyd@soton.ac.uk

Collaborating research institutes, centres and groups

Southampton Geospatial

The Southampton Geospatial team has the tools and expertise to collect, combine and interpret datasets about locations.

WorldPop

We develop and implement open, robust and peer-reviewed geospatial methods. These are used for mapping population distributions, demographics and dynamics, with a principle focus on low and middle income countries.

Research outputs