Earticle

초록

영어

This study assesses the location suitability of disaster relief camps considering the increasing flood susceptibility under the climate change scenario, SSP3-7.0. It estimates the area and population coverage of these camps focusing on the Dhubri district in Assam, India. The methodology involved selecting 13 variables related to flood occurrence and flood data from 2019 were used to train models. The Random Forest model, showing superior performance (AUC=0.91), was chosen for final predictions. This model, incorporating topographical, climatic, and anthropogenic variables, was applied to predict flood susceptibility of Dhubri and evaluated the flood risk of existing relief camps. The study found that the population exposed to flood risk in Dhubri district will increase, with more than 50% likelihood that 104 out of 227 designated relief camps will be flooded by 2070. These findings can inform strategic planning for disaster preparedness and location selection of relief camps .

목차

Introduction
Methods
Study Area
Data and Method
Result
Evaluation of Flood Prediction Model Performance
Flood Susceptibility Prediction based on the Trained Model
Conclusion
References

키워드

저자

• Yeeun Choi [ Graduate School of Data Science, Seoul National University ]
• Hyunwoo Park [ Graduate School of Data Science, Seoul National University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2026

• 십진분류

  KDC 325 DDC 658