Changes in habitat and local extinctions are becoming major issues due to the increase in abnormal climate conditions and the long-term temperature increase caused by climate change. Although research on environmental niche modeling is increasing, most of it relies on machine learning that only considers environmental variables and often uses far-future climate change scenarios. In addition, conducting proper modeling is generally not easy because of the complexity of the data and programs required for a single study. To facilitate environmental niche modeling studies, this study aim to develop a program pipeline that can efficiently handle climate data transformation, visualization, and species distribution modeling.

1. INTRODUCTION

2. DATA AND METHODOLOGY

2.1 기후변화 시나리오 자료의 가공 및 시각화

2.2 특정 생물의 알려진 분포 획득

2.3 기후데이터를 사용한 미래 생물 서식지 및 분포 예측

2.4 생물 미래 분포 데이터의 시각화

3. RESEARCH RESULTS

4. CONCLUDING REMARKS

REFERENCES