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References

1 
Alberg, A. J., Park, J. W., Hager, B. W., Brock, M. V. and Diener-West, M. (2004). “The use of ‘overall accuracy’ to evaluate the validity of screening or diagnostic tests.” Journal of General Internal Medicine, Springer, Vol. 19, No. 5, pp. 460-465, https://doi.org/10.1111/j.1525-1497.2004.30091.x.DOI
2 
Bar, S., Parida, B. R. and Pandey, A. C. (2020). “Landsat-8 and Sentinel-2 based Forest fire burn area mapping using machine learning algorithms on GEE cloud platform over Uttarakhand, Western Himalaya.” Remote Sensing Applications: Society and Environment, Elsevier, Vol. 18, 100324, https://doi.org/10.1016/j.rsase.2020.100324.DOI
3 
Choi, S. P., Kim, D. H. and Lee, S. K. (2006). “The abstaction of forest fire damage area using factor analysis from the satellite image data.” Journal of Korean Society for Geospatial Information System, KSIS, Vol. 14, No. 1, pp. 13-19.URL
4 
Chung, M. and Kim, Y. (2020). “Analysis on Topographic Normalization Methods for 2019 Gangneung-East Sea Wildfire Area Using PlanetScope Imagery.” Korean Journal of Remote Sensing, KSRS, Vol. 36, No. 2_1, pp. 179-197, https://doi.org/10.7780/KJRS.2020.36.2.1.7.DOI
5 
Cohen, J. (1960). “A coefficient of agreement for nominal scales.” Educational and Psychological Measurement, Sage, Vol. 20, No. 1, pp. 37-46, https://doi.org/10.1177/001316446002000104.DOI
6 
Cover, T. and Hart, P. (1967). “Nearest neighbor pattern classifica- tion.” IEEE Transactions on Information Theory, IEEE, Vol. 13, No. 1, pp. 21-27, https://doi.org/10.1109/TIT.1967.1053964.DOI
7 
Dennison, P. E., Brewer, S. C., Arnold, J. D. and Moritz, M. A. (2014). “Large wildfire trends in the western United States, 1984-2011.” Geophysical Research Letters, AGU, Vol. 41, No. 8, pp. 2928-2933, https://doi.org/10.1002/2014GL059576.DOI
8 
European Space Agency (2015). Sentinel-2 User Handbook. European Space Agency.URL
9 
Fix, E. and Hodges, J. L. (1989). “Discriminatory analysis. nonparametric discrimination: Consistency properties.” International Statistical Review /Revue Internationale de Statistique, ISI, Vol. 57, No. 3, pp. 238-247, https://doi.org/10.2307/1403797.DOI
10 
Fornacca, D., Ren, G. and Xiao, W. (2018). “Evaluating the best spectral indices for the detection of burn scars at several post-fire dates in a mountainous region of Northwest Yunnan, China.” Remote Sensing, MDPI, Vol. 10, No. 8, 1196, https://doi.org/10.3390/rs10081196.DOI
11 
Gascon, F., Bouzinac, C., Thépaut, O., Jung, M., Francesconi, B., Louis, J., Lonjou, V., Lafrance, B., Massera, S., Gaudel- Vacaresse, A., Languille, F., Alhammoud, B., Viallefont, F., Pflug, B., Bieniarz, J., Clerc, S., Pessiot, L., Trémas, T., Cadau, E., De Bonis, R., Isola, C., Martimort P. and Fernandez, V. (2017). “Copernicus Sentinel-2A calibration and products validation status.” Remote Sensing, MDPI, Vol. 9, No. 6, 584, https://doi.org/10.3390/rs9060584.DOI
12 
Hawbaker, T. J., Vanderhoof, M. K., Beal, Y.-J., Takacs, J. D., Schmidt, G. L., Falgout, J. T., Williams, B., Fairaux, N. M., Caldwell, M. K., Picotte, J. J., Howard, S. M., Stitt, S. and Dwyer, J. L. (2017). “Mapping burned areas using dense time-series of Landsat data.” Remote Sensing of Environment, Elsevier, Vol. 198, pp. 504-522, https://doi.org/10.1016/j.rse.2017.06.027.DOI
13 
Kara, L. Z., Laksaci, A., Rachdi, M. and Vieu, P. (2017). “Data-driven kNN estimation in nonparametric functional data analysis.” Journal of Multivariate Analysis, Elsevier, Vol. 153, pp. 176-188, https://doi.org/10.1016/j.jmva.2016.09.016.DOI
14 
Klebanov, L. B. (2016). “Big outliers versus heavy tails: What to use?” ArXiv:1611.05410 [Math, Stat], ArXiv, http://arxiv.org/abs/1611.05410.URL
15 
Knopp, L., Wieland, M., Rättich, M. and Martinis, S. (2020). “A Deep learning approach for burned area segmentation with Sentinel-2 data.” Remote Sensing, MDPI, Vol. 12, No. 15, 2422, https://doi.org/10.3390/rs12152422.DOI
16 
Landis, J. R. and Koch, G. G. (1977). “The measurement of observer agreement for categorical data.” Biometrics, International Biometric Society, Vol. 33, No. 1, pp. 159-174, https://doi.org/10.2307/2529310.DOI
17 
Lee, S. J., Kim, K. J., Kim, Y. H., Kim, J. W. and Lee, Y. W. (2017). “Development of FBI(Fire Burn Index) for Sentinel-2 images and an experiment for detection of burned areas in Korea.” Journal of the Association of Korean Photo-Geographers, The Association of Korean Photo-Geographers, Vol. 27, No. 4, pp. 187-202, https://doi.org/10.35149/JAKPG.2017.27.4.012 (in Korean).DOI
18 
Mithal, V., Nayak, G., Khandelwal, A., Kumar, V., Nemani, R. and Oza, N. (2018). “Mapping burned areas in tropical forests using a novel machine learning framework.” Remote Sensing, MDPI, Vol. 10, No. 1, 69, https://doi.org/10.3390/rs10010069.DOI
19 
National Fire agency (2021). 2020 Fire Statistical Yearbook, https://www.nfds.go.kr/bbs/selectBbsDetail.do?bbs=B21&bbs_ no=7948&pageNo=1 (in Korean).URL
20 
Nichols, T. R., Wisner, P. M., Cripe, G. and Gulabchand, L. (2010). “Putting the kappa statistic to use.” The Quality Assurance Journal, Vol. 13, Nos. 3-4, pp. 57-61, https://doi.org/10.1002/qaj.481.DOI
21 
Nigsch, F., Bender, A., van Buuren, B., Tissen, J., Nigsch, E. and Mitchell, J. B. O. (2006). “Melting point prediction employing k-nearest neighbor algorithms and genetic parameter optimization.” Journal of Chemical Information and Modeling, Vol. 46, No. 6, pp. 2412-2422, https://doi.org/10.1021/ci060149f.DOI
22 
Pinto, M. M., Libonati, R., Trigo, R. M., Trigo, I. F. and DaCamara, C. C. (2020). “A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images.” ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, Vol. 160, pp. 260-274, https://doi.org/10.1016/j.isprsjprs.2019.12.014.DOI
23 
Roteta, E., Bastarrika, A., Padilla, M., Storm, T. and Chuvieco, E. (2019). “Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa.” Remote Sensing of Environment, Elsevier, Vol. 222, pp. 1-17, https://doi.org/10.1016/j.rse.2018.12.011.DOI
24 
Roy, D. P., Huang, H., Boschetti, L., Giglio, L., Yan, L., Zhang, H. H. and Li, Z. (2019). “Landsat-8 and Sentinel-2 burned area mapping—A combined sensor multi-temporal change detection approach.” Remote Sensing of Environment, Elsevier, Vol. 231, 111254, https://doi.org/10.1016/j.rse.2019.111254.DOI
25 
Sim, S., Kim, W., Lee, J., Kang, Y., Im, J., Kwon, C. and Kim, S. (2020). “Wildfire severity mapping using sentinel satellite data based on machine learning approaches.” Korean Journal of Remote Sensing, KSRS, Vol. 36, No. 5_3, pp. 1109-1123, https://doi.org/10.7780/KJRS.2020.36.5.3.9 (in Korean).DOI
26 
Story, M. and Congalton, R. G. (1986). “Accuracy assessment: A user’s perspective.” Photogrammetric Egineering and Remote Sensing, American Society for Photogrammetry and Remote Sensing, Vol. 52, No. 3, pp. 397-399.URL
27 
Weaver, J., Moore, B., Reith, A., McKee, J. and Lunga, D. (2018). “A comparison of machine learning techniques to extract human settlements from high resolution imagery.” Proceedings of IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Valencia, Spain, pp. 6412-6415, https://doi.org/10.1109/IGARSS.2018.8518528.DOI
28 
Weber, K. T., Seefeldt, S., Moffet, C. and Norton, J. (2008). “Comparing fire severity models from post-fire and pre/post-fire differenced imagery.” GIScience & Remote Sensing, Taylor & Francis, Vol. 45, No. 4, pp. 392-405, https://doi.org/10.2747/1548-1603.45.4.392.DOI
29 
Won, M., Jang, K., Yoon, S. and Lee, H. (2019). “Change detection of damaged area and burn severity due to heat damage from gangwon large fire area in 2019.” Korean Journal of Remote Sensing, KSRS, Vol. 35, No. 6_2, pp. 1083-1093, https://doi.org/10.7780/KJRS.2019.35.6.2.5 (in Korean).DOI
30 
Won, M. S., Koo, K. S. and Lee, M. B. (2007). “An quantitative analysis of severity classification and burn severity for the large forest fire areas using normalized burn ratio of landsat imagery.” Journal of the Korean Association of Geographic Information Studies, KAGIS, Vol. 10, No. 3, pp. 80-92 (in Korean).URL