Mapping Ecosystem Functional Groups in the Republic of Korea Based on the IUCN Global Ecosystem Typology

Kyungil Lee, Haedam Baek, Chul Hyun Choi, Sang Hak Han, Seonyoung Park

Research output: Contribution to journalArticlepeer-review

Abstract

This study presents a national-scale mapping of Ecosystem Functional Groups (EFGs) in the Republic of Korea using the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology (GET), a hierarchical classification system, integrated with spatial datasets, satellite imagery, and a random forest (RF) classifier. By incorporating locally relevant ecological data, the original typology was refined to resolve issues of overgeneralization and spatial overlap. The resulting map delineates 20 distinct ecosystem types, offering improved spatial accuracy and better alignment with the actual land extent. To evaluate the potential of EFG classification, the RF model was trained on seasonal satellite composites and environmental variables, achieving an overall accuracy of 80%. Elevation and temperature were found to be the most influential predictors, effectively distinguishing ecological patterns across diverse landscapes. This integrated approach supports consistent tracking of ecosystem changes and helps address the limitations of static or infrequently updated spatial datasets. The developed EFG map supports biodiversity conservation by providing a practical foundation for national spatial planning and contributing to the Red List of Ecosystems assessments, which is in line with the goals of the Global Biodiversity Framework.

Original languageEnglish
Article number1659
JournalRemote Sensing
Volume17
Issue number10
DOIs
StatePublished - May 2025

Keywords

  • biodiversity
  • ecosystem extent
  • IUCN GET
  • random forest
  • remote sensing

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