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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 researchers

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: [email protected]

Professor Nikos Tzavidis PhD

Professor of Statistical Methodology

Research interests

  • Small Area Estimation and official statistics
  • Outlier robust inference; Quantile and M-quantile models
  • Geospatial data; Poverty mapping; Statistical inference under data aggregation and displacement
Connect with Nikos

Email: [email protected]

Dr Jessica Steele

Senior Enterprise Fellow
Connect with Jessica

Email: [email protected]

Collaborating research institutes, centres and groups

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.

Southampton Geospatial

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

Research outputs