Earticle

초록

영어

This study aimed to improve the spatial prediction accuracy of Species Distribution Models (SDMs) by applying and comparing area-weighted sampling and simple random sampling for Korean Red Pine (Pinus densiflora). We employed Random Forest (RF) and Maximum Entropy Model (MaxEnt) as the SDMs and evaluated their performance differences and spatial suitability under each sampling regime. The results showed that simple random sampling improved the model’s generalization ability by uniformly reflecting presence points across the entire study area, thereby ensuring overall spatial homogeneity. Meanwhile, in the case of area-weighted sampling, samples were concentrated in areas with high actual occurrence density, such as the East coast region and southern forest zones. This enhanced spatial concentration and resulted in higher predictive reliability in these high-density regions, but it also led to a relative increase in True Negatives (TN) and False Positives (FP). These findings indicate that sampling alters not only the numerical balance of the data but also the representativeness of the spatial patterns learned by the model. Consequently, the selection of a sampling method requires a strategic choice, contingent on whether the objective prioritizes global predictive stability or precision within core distribution areas.

목차

Abstract
Introduction
Materials and Methods
Scope of research
Species distribution model (SDM)
Model evaluation indicators and verification
Results and Discussion
Results of presence points and SDMs
Results of spatial consistency verification
Conclusion
Acknowledgements
References

키워드

저자

• Bomin Kim [ Department of Heritage Science and Technology Studies, Graduate School of Korea Heritage, Korea National University of Heritage, Buyeo 33115, Republic of Korea ]
• Kangmin Kim [ Department of Heritage Science and Technology Studies, Graduate School of Korea Heritage, Korea National University of Heritage, Buyeo 33115, Republic of Korea ]
• Sunyong Sung [ Department of Traditional Landscape Architecture, College of Science and Technology, Korea National University of Heritage, Buyeo 33115, Republic of Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Journal of Forest and Environmental Science [산림과학연구]

• 간기

  계간

• pISSN

  2288-9744

• eISSN

  2288-9752

• 수록기간

  1981~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 526 DDC 634