ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. Forest Management
Volume 8 - 2025 | doi: 10.3389/ffgc.2025.1627998
Accuracy and Consistency Assessment of Forest Cover Datasets: A Comparative Study of Two Provinces in China
Provisionally accepted
- 1Hunan University of Science and Technology, Xiangtan, China
- 2Central South University, Changsha, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Forests play a crucial role in maintaining the ecological balance of the Earth. While existing publicly available datasets typically offer high accuracy in identifying large-scale forest concentrations, discrepancies arise in forest extraction within smaller regions. This variation complicates the selection of appropriate forest cover datasets for specific areas. This study focuses on the southern and northern regions of China, represented by Hunan Province and Heilongjiang Province, respectively. It systematically evaluates the performance of eight forest cover datasets from 2020 in terms of forest area estimation, spatial consistency, and classification accuracy. Through confusion analysis of classification in low-consistency areas, the study identifies the confusion patterns between forests and other land cover types in different regions. Additionally, the study explores the causes of discrepancies between datasets by considering topographic factors and human activities. The results show that the CRLC 2020 outperforms others in terms of both area estimation and classification accuracy, achieving classification accuracies of 90.88% in Hunan Province and 91.69% in Heilongjiang Province. High-consistency areas (levels 6-8) in Hunan account for 69.4%, lower than Heilongjiang's 77%. This comprehensive analysis provides valuable insights for forestry practitioners in selecting appropriate forest cover datasets in areas with complex land cover, offering reliable recommendations for forest cover mapping and the formulation of sound mapping strategies.
Keywords: forest mapping products, land cover and land use, spatial consistency, accuracy assessment, Validation
Received: 13 May 2025; Accepted: 18 Jun 2025.
Copyright: © 2025 Zhu, Lin, Fu, Zhang, Li, Wang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dongfang Lin, Hunan University of Science and Technology, Xiangtan, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.