Back to Search Start Over

Consistency Analysis and Accuracy Evaluation of Multi-Source Land Cover Data Products in the Eastern European Plain

Authors :
Guangmao Jiang
Juanle Wang
Kai Li
Chen Xu
Heng Li
Zongyi Jin
Jingxuan Liu
Source :
Remote Sensing, Vol 15, Iss 17, p 4254 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Land-use and land-cover changes in the Eastern European Plain have important implications for regional and global ecological environments, food security, and socio-economic development. Here, three 30 m resolution global land cover data products (FROM_GLC, GlobeLand30, and GLC_FCS30) from the Eastern European Plain were analyzed and evaluated for component similarity, type confusion degree, spatial consistency, and accuracy verification. The research found that the three products provided consistent descriptions of land-cover types in the East European Plain. There was a strong correlation in the type area between the different products, with a correlation coefficient >0.85. Medium-to-high-consistency areas represented 92.31% of the total plains area. The low-consistency areas were mainly concentrated on Yuzhny Island, Kola Peninsula, and Pechora River Basin. The comparison revealed high consistency among the three products in identifying forest, cropland, water, and permanent ice/snow types. However, the consistency was poor for shrubs, wetlands, and bare land. Using the GLCVSS_V1 validation dataset, the highest overall accuracy among the assessed land cover data products was observed in the FROM_GLC (73.96%), followed by GlobeLand30 (69.80%) and GLC_FCS30 (67.29%). The FROM_GLC dataset is suitable for studying forests, tundra, water, and providing an overall representation of the region’s land cover. The GLC_FCS30 dataset is more suitable for agricultural research. The differences between products arise from the differences in classification systems, algorithms, and data correction. In the future, it will be necessary to utilize the advantages of different products for data fusion, focusing on areas with high heterogeneity and easily confused types, and improving the reliability of land-cover data products.

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
17
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.5a0f61f54922438ca4bea80309426fea
Document Type :
article
Full Text :
https://doi.org/10.3390/rs15174254