Accuracy assessment of Global Human Settlement Layer (GHSL) built-up products over China

Feng Liu; Shuai Wang; Yi Xu; Qing Ying; Fukun Yang; Yuchu Qin

doi:10.1371/journal.pone.0233164

Accuracy assessment of Global Human Settlement Layer (GHSL) built-up products over China

PLoS One. 2020 May 29;15(5):e0233164. doi: 10.1371/journal.pone.0233164. eCollection 2020.

Authors

Feng Liu^{1

2}, Shuai Wang^{1

2}, Yi Xu^{1

2}, Qing Ying³, Fukun Yang^{1

2}, Yuchu Qin¹

Affiliations

¹ State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
² School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China.
³ Department of Geographical Sciences, University of Maryland, College Park, Maryland, United States of America.

Abstract

Building a density map over large areas could provide essential information of land development intensity and settlement condition. It is crucial for supporting studies and planning of human settlement environment. The Global Human Settlement Layer (GHSL) is a comprehensive data set of mapping human settlement at a global scale, which was produced by the Joint Research Centre (JRC), European Commission. The built-up density is an important layer of GHSL data set. Currently, the validation of the GHSL built-up area products was preliminarily conducted over the United States and European countries. However, as a typical East Asian region, China is quite different from the United States, Europe, and other regions in terms of building forms and urban layouts. Therefore, it is necessary to perform an accuracy assessment of GHSL data set in Asian countries like China. With individual building footprint data of 20 typical cities in China, this paper presents our effort to validate the GHSL built-up area products. The aggregation mean and neighborhood search based algorithms are adopted for matching building footprint data and the GHSL products, through the regression analysis at per-pixel level, the building density map in raster format are generated as validation data. The accuracy index of GHSL built-up area was calculated for the study areas, and the validation methods were explored for GHSL built-up products at large scale. The results show that the built-up layer aggregated by the building footprint have the highest correlation with the coarse resolution GHSL built-up products, but GHSL tends to underestimate the building density of low-density areas and overestimate the areas with high density. This study suggests that GHSL built-up area products in 20 representative Chinese cities of China could provide quantitative information about built-up areas, but the product accuracy still need to be improved in the regions with heterogeneous formations of human settlements like China. There is a big picture of mapping high accuracy built-up density of China with the training data set acquired by the study.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

China
Cities
Humans
Models, Theoretical*

Grants and funding

This research was funded by the National Key R&D Program of China (Grant No. 2018YFC0506901) and the 100 Talents Program of the Chinese Academy of Sciences. The acquisition is Yuchu Qin who is the Correspondence of this manuscript. The author Yuchu Qin defined the research theme and supervised the research work. And checked the experimental results and revised the manuscript.