Global Built-up and Population Datasets: Which ones should you use for India?

TL;DR

This study evaluates the accuracy of various global built-up and population datasets for India, identifying the most suitable datasets for different applications and demonstrating IDC-POP's superior performance in Bihar.

Contribution

It provides a comprehensive accuracy assessment of multiple global datasets for India and introduces IDC-POP as a new, more accurate population dataset for Bihar.

Findings

GHS-BUILT-S2 is the most suitable built-up dataset for India (2015-2020).

HRSL outperforms other global population datasets in Bihar.

IDC-POP surpasses global datasets in accuracy for Bihar.

Abstract

Multiple global land cover and population distribution datasets are currently available in the public domain. Given the differences between these datasets and the possibility that their accuracy may vary across countries, it is imperative that users have clear guidance on which datasets are appropriate for specific settings and objectives. Here we assess the accuracy of three global 10m resolution built-up datasets (ESRI, GHS-BUILT-S2 and WSF) and three population distribution datasets (HRSL 30m, WorldPop 100m, GHS-POP 250m) for India. Among built-up datasets, the GHS-BUILT-S2 is the most suitable for India for the 2015-2020 time period. To assess accuracy of population distribution datasets we use data from the 2011 Census of India at the level of 37,137 village and town polygons for the state of Bihar in India. Among the global datasets, HRSL has the best results. We also compute error metrics for IDC-POP, a 30m resolution population dataset generated by us at the Indian Institute for Human Settlements. For Bihar, IDC-POP outperforms all three global datasets.