Towards an open and synergistic framework for mapping global land cover

Jiyao Zhao; Le Yu; Han Liu; Huabing Huang; Jie Wang; Peng Gong

doi:10.7717/peerj.11877

Towards an open and synergistic framework for mapping global land cover

PeerJ. 2021 Aug 4:9:e11877. doi: 10.7717/peerj.11877. eCollection 2021.

Authors

Jiyao Zhao¹, Le Yu^{1

2}, Han Liu¹, Huabing Huang³, Jie Wang⁴, Peng Gong^{1

2

5}

Affiliations

¹ Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China.
² Ministry of Education Ecological Field Station for East Asia Migratory Birds, Tsinghua University, Beijing, China.
³ School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China.
⁴ State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China.
⁵ Department of Geography and Department of Earth Sciences, University of Hongkong, Hongkong, China.

Abstract

Global land-cover datasets are key sources of information for understanding the complex inter-actions between human activities and global change. They are also among the most critical variables for climate change studies. Over time, the spatial resolution of land cover maps has increased from the kilometer scale to 10-m scale. Single-type historical land cover datasets, including for forests, water, and impervious surfaces, have also been developed in recent years. In this study, we present an open and synergy framework to produce a global land cover dataset that combines supervised land cover classification and aggregation of existing multiple thematic land cover maps with the Google Earth Engine (GEE) cloud computing platform. On the basis of this method of classification and mosaicking, we derived a global land cover dataset for 6 years over a time span of 25 years. The overall accuracies of the six maps were around 75% and the accuracy for change area detection was over 70%. Our product also showed good similarity with the FAO and existing land cover maps.

Keywords: Global land cover change; Land cover series; Open and synergy mapping.

Associated data

figshare/10.6084/m9.figshare.14329025.v1

Grants and funding

This research was funded by the National Key R&D Program of China (grant number: 2017YFA0604401; 2019YFA0606601) and the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (EarthLab). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.