Browse > Article
http://dx.doi.org/10.7780/kjrs.2022.38.6.3.10

Analysis of Burned Areas in North Korea Using Satellite-based Wildfire Damage Indices  

Kim, Seoyeon (Geomatics Research Institute, Pukyong National University)
Youn, Youjeong (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Jeong, Yemin (Geomatics Research Institute, Pukyong National University)
Kwon, Chunguen (Forest Fire and Landslide Division, National Institute of Forest Science)
Seo, Kyungwon (Forest Fire and Landslide Division, National Institute of Forest Science)
Lee, Yangwon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.38, no.6_3, 2022 , pp. 1861-1869 More about this Journal
Abstract
Recent climate change can increase the frequency and damage of wildfires worldwide. It can also lead to the deterioration of the forest ecosystem and increase casualties and economic loss. Satellite-based indices for forest damage can facilitate an objective and rapid examination of burned areas and help analyze inaccessible places like North Korea. In this letter, we conducted a detection of burned areas in North Korea using the traditional Normalized Burn Ratio (NBR), the Normalized Difference Vegetation Index (NDVI) to represent vegetation vitality, and the Fire Burn Index (FBI) and Forest Withering Index (FWI) that were recently developed. Also, we suggested a strategy for the satellite-based detection of burned areas in the Korean Peninsula as a result of comparing the four indices. Future work requires the examination of small-size wildfires and the applicability of deep learning technologies.
Keywords
Fire-burned area; Sentinel-2; North Korea;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Lee, S.J., K.J. Kim, Y.H. Kim, J.W. Kim, and Y.W. Lee, 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, 27(4): 187-202 (in Korean with English abstract).   DOI
2 Otsu, N., 1979. A threshold selection method from gray-level histograms, IEEE Transactions on Systems, Man, and Cybernetics, 9(1): 62-66. https://doi.org/10.1109/TSMC.1979.4310076   DOI
3 Roy, D.P., H. Huang, L. Boschetti, L. Giglio, L. Yan, H.H. Zhang, and Z. Li, 2019. Landsat-8 and Sentinel-2 burned area mapping-A combined sensor multi-temporal change detection approach, Remote Sensing of Environment, 231: 111254. https://doi.org/10.1016/j.rse.2019.111254   DOI
4 United Nations, 2022. Normalized Burn Ratio (NBR), https://un-spider.org/advisory-support/recommendedpractices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio, Accessed on Dec. 1, 2022.
5 Park, S.W., S.J. Lee, C.Y. Chung, S.R. Chung, I. Shin, W.C. Jung, H.S. Mo, S.I. Kim, and Y.W. Lee, 2019. Satellite-based forest withering index for detection of fire burn area: Its development and application to 2019 Kangwon wildfires, Korean Journal of Remote Sensing, 35(2): 343-346 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2019.35.2.13   DOI
6 Won, M.S., K.S. Koo, and M.B. Lee, 2007. A 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, 10(3): 80-92 (in Korean with English abstract).
7 Key, C.H. and N.C. Benson, 2005. Landscape assessment: remote sensing of severity, the normalized burn ratio and ground measure of severity, the composite burn index, FIREMON: Fire effects monitoring and inventory system, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ogden, UT, USA.