2021/08/18 by Pratyush Tripathy, Tripathy, Pratyush, Krishnachandran Balakrishnan +1
Environmental Science · #FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Impact of Light on Environment and Health #Land Use and Ecosystem Services #Physics and Society (physics.soc-ph) #Remote Sensing in Agriculture #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2108.08304
openalex publication_date 2021/08/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.