Analyzing the Uncertainty of Degree Confluence Project for Validating Global Land-Cover Maps Using Reference Data-Based Classification Schemes

Qian Tana, Fujii M., Kinoshita Tsuguki, Bao Yuhai
2020.12.1

論文情報

 Analyzing the Uncertainty of Degree Confluence Project for Validating Global Land-Cover Maps Using Reference Data-Based Classification Schemes

著者: Qian Tana, Fujii M., Kinoshita Tsuguki, Bao Yuhai
年:2020
掲載誌:Remote Sens., 12(16), 2589;


論文へのリンク(英文のみ)

キーワード

climate changes; global land-cover maps; accuracy assessment; volunteer-based validation data; Degree Confluence Project; citizen science; classification scheme

要旨

Global land-cover products play an important role in assisting the understanding of climate-related changes and the assessment of progress in the implementation of international initiatives for the mitigation of, and adaption to, climate change. However, concerns over the accuracies of land-cover products remain, due to the issue of validation data uncertainty. The volunteer-based Degree Confluence Project (DCP) was created in 1996, and it has been used to provide useful ground-reference information. This study aims to investigate the impact of DCP-based validation data uncertainty and the thematic issues on map accuracies. We built a reference dataset based on the DCP-interpreted dataset and applied a comparison for three existing global land-cover maps and DCP dataset-based probability maps under different classification schemes. The results of the obtained confusion matrices indicate that the uncertainty, including the number of classes and the confusion in mosaic classes, leads to a decrease in map accuracy. This paper proposes an informative classification scheme that uses a matrix structure of unaggregated land-cover and land-use classes, and has the potential to assist in the land-cover interpretation and validation processes.

Fig. The agreement rates between DCP-derived reference data and three existing maps:(a) MCD12Q1 2005, (b) GlobCover 2009, (c) GLNMO 2005. The numbers in the columns and rows represent classification schemes of the maps (row) and classification schemes of DCP-derived validation data (column).3.1.1. Forest Classes.