Reply To: Global Gridded Population Datasets Systematically Underrepresent Rural Population by Josias L\'ang-Ritter et al

TL;DR

This paper critically examines the claim that global gridded population datasets underrepresent rural populations, highlighting that methodological choices and historical allocation issues may explain observed biases rather than actual undercounting.

Contribution

It challenges the assumption that rural underrepresentation in population datasets is primarily due to undercounting, emphasizing the role of methodological and historical factors.

Findings

Bias figures may be due to methodological decisions

Historical misallocation affects population estimates

Underrepresentation claims need cautious interpretation

Abstract

The paper titled ''Global gridded population datasets systematically underrepresent rural population'' by Josias L\'ang-Ritter et al. provides a valuable contribution to the discourse on the accuracy of global population datasets, particularly in rural areas. We recognize the efforts put into this research and appreciate its contribution to the field. However, we feel that key claims in the study are overly bold, not properly backed by evidence and lack a cautious and nuanced discussion. We hope these points will be taken into account in future discussions and refinements of population estimation methodologies. We argue that the reported bias figures are less caused by actual undercounting of rural populations, but more so by contestable methodological decisions and the historic misallocation of (gridded) population estimates on the local level.