Comparison of population distributions and urban land uses

During my time as a geospatial researcher at University of Twente, I worked on a project with PBL Netherlands Environmental Assessment Agency to analyze global population dataset to gain more insight into their reliability. The study was conducted in Sao Paulo, Kumasi, Enschede, Jakarta, New York, Kabul and Cairo. I used advanced spatial analysis techniques to disaggregate census data into a regular 1 km grid and compared it to existing global gridded population dataset. Afterwards, I compared the spatial population data to land use maps and identified the causes of error in the global population dataset. Results showed diverse error rates and degrees depending on the geographic context. In general, cities in High-Income (HIC) and Upper-Middle-Income Countries (UMIC) had fewer model errors as compared to cities in Low- and Middle-Income Countries (LMIC). Gridded population data tend to underestimate population in slum areas. In addition the technical report, we published the results in a scientific journal.