@article{ART002629637},
author={Youn Hyoungjin and Jeong, Jong Chul},
title={Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2},
journal={The Korea Spatial Planning Review},
issn={1229-8638},
year={2020},
volume={106},
pages={107-117},
doi={10.15793/kspr.2020.106..006}
TY - JOUR
AU - Youn Hyoungjin
AU - Jeong, Jong Chul
TI - Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2
JO - The Korea Spatial Planning Review
PY - 2020
VL - 106
IS - null
PB - 국토연구원
SP - 107
EP - 117
SN - 1229-8638
AB - This study applies machine learning techniques to forest fire damage area. The study area was Sokcho, Gangwon-do, which occurred forest fire damage on April 4, 2019. We used Sentinel-2 images for detecting forest fire area. We adjusted four cases for train model based on the dNBR severity level classes. We used 4 SVM kernels, because the accuracy may vary depending on the structure of the data to learning. The training results showed that in all four cases, the SVM RBF model showed the highest accuracy. The SVM RBF model with the highest training accuracy was used in the test area classification process. During the verification process, we created 300 GTP using KOMPSAT-3 for verification. Verification results show that the test results using the SVM RBF model classified (82.67%) was more affected than dNBR classification result (80.67%). The results of the study suggested a direction to incorporate mechanical learning in the analysis process for detecting and classifying forest fire damage areas.
KW - Forest Fire;Machine Learning;SVM;Sentinel-2;KOMPSAT-3
DO - 10.15793/kspr.2020.106..006
ER -
Youn Hyoungjin and Jeong, Jong Chul. (2020). Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2. The Korea Spatial Planning Review, 106, 107-117.
Youn Hyoungjin and Jeong, Jong Chul. 2020, "Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2", The Korea Spatial Planning Review, vol.106, pp.107-117. Available from: doi:10.15793/kspr.2020.106..006
Youn Hyoungjin, Jeong, Jong Chul "Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2" The Korea Spatial Planning Review 106 pp.107-117 (2020) : 107.
Youn Hyoungjin, Jeong, Jong Chul. Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2. 2020; 106 107-117. Available from: doi:10.15793/kspr.2020.106..006
Youn Hyoungjin and Jeong, Jong Chul. "Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2" The Korea Spatial Planning Review 106(2020) : 107-117.doi: 10.15793/kspr.2020.106..006
Youn Hyoungjin; Jeong, Jong Chul. Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2. The Korea Spatial Planning Review, 106, 107-117. doi: 10.15793/kspr.2020.106..006
Youn Hyoungjin; Jeong, Jong Chul. Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2. The Korea Spatial Planning Review. 2020; 106 107-117. doi: 10.15793/kspr.2020.106..006
Youn Hyoungjin, Jeong, Jong Chul. Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2. 2020; 106 107-117. Available from: doi:10.15793/kspr.2020.106..006
Youn Hyoungjin and Jeong, Jong Chul. "Classification of Forest Fire Damage Grade Using Machine Learning and Sentinel-2" The Korea Spatial Planning Review 106(2020) : 107-117.doi: 10.15793/kspr.2020.106..006
