• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.195-203
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• 2008

Burn severity is an important role for rehabilitation of burned forest area. This factor led to the pilot study to determine if high resolution IKONOS images could be used to classify and delinenate the bum severity over burned areas of Samchock Fire and Cheongyang-Yesan Fire. The results of this study can be summarized as follows: 1. The modified Normalized Bum Ratio (NBR) for IKONOS imagery can be evaluated using burn severity mapping. 2. IKONOS-derived NBR imagery could provide fire scar and detail mapping of burned areas at Samchock fire and Cheongyang-Yesan Burns.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1299-1308
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• 2023

Forest fires are becoming more frequent and larger around the world due to climate change. Remote sensing such as satellite images can be used as an alternative or assistance data because it reduces various difficulties of field survey. Forest burn severity (differenced normalized burn ratio, dNBR) is calculated through the difference in normalized burn ratio (NBR) before and after a forest fire. The images used in the NBR formula are based on Landsat's near-infrared (NIR) and short-wavelength infrared (SWIR) bands. South Korea's satellite images don't have a SWIR band. So domestic studies related to forest burn severity calculated dNBR using overseas images or indirectly using the normalized difference vegetation index (NDVI) using South Korea's satellite images. Therefore, in this study, dNBR was calculated by substituting the mid-wavelength infrared (MWIR) band of Kompsat-3A (K3A) instead of the SWIR band in the NBR formula. The results were compared with the dNBR results obtained through Landsat which is the standard for dNBR formula. As a result, it was shown that dNBR using K3A's MWIR band has a wider range of values and can be expressed in more detail than dNBR using Landsat's SWIR band. Therefore, it is considered that K3A images will be highly useful in surveying burn areas and severity affected by forest fires. In addition, this study used the K3A's MWIR band images degraded to 30 m. It is considered that much better results will be obtained if a higher-resolution MWIR band is used.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.80-92
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• 2007

Forest fire is the dominant large-scale disturbance mechanism in the Korean temperate forest, and it strongly influences forest structure and function. Moreover burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. Vegetation rehabilitation may specifically vary according to burn severity after fire. To understand burn severity and process of vegetation rehabilitation at the damaged area after large-fire is required a lot of man powers and budgets. However the analysis of burn severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. For classifying fire damaged area and analyzing burn severity of Samcheok fire area occurred in 2000, Cheongyang fire in 2002, and Yangyang fire in 2005 we utilized Normalized Burn Ratio(NBR) technique. The NBR is temporally differenced between pre- and post-fire datasets to determine the extent and degree of change detected from burning. In this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ imagery to compute the NBR and evaluate large-scale patterns of burn severity at 30m spatial resolution. 65% in the Samcheok fire area, 91% in the Cheongyang fire area and 65% in the Yangyang fire area were corresponded to burn severity class above 'High'. Therefore the use of a remotely sensed Differenced Normalized Burn Ratio(${\Delta}NBR$) by RS and GIS allows for the burn severity to be quantified spatially by mapping damaged domain and burn severity across large-fire area.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.231-237
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• 2007

To monitor process of vegetation rehabilitation at the damaged area after large-fire is required a lot of manpowers and budgets. However the analysis of vegetation recovery using satellite imagery can be obtaining rapid and objective result remotely in the large damaged area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. To classify fire damaged area and analyze burn severity of Samcheok fire area occurred in 2000, Cheongyang fire 2002, and Yangyang fire 2005 was utilized Landsat TM and ETM+ imagery. Therefore the objective of the present paper is to quantitatively classify fire damaged area and analyze burn severity using normalized burn index(NBR) of pre- and post-fire's Landsat satellite imagery.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1861-1869
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• 2022

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.

• Journal of The Geomorphological Association of Korea
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• v.28 no.1
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• pp.83-99
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• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.517-534
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• 2019

In abrupt fire disturbances, high quality images suitable for wildfire damage assessment can be difficult to acquire. Quantifying wildfire burn area and severity are essential measures for quick short-term disaster response and efficient long-term disaster restoration. Planetscope (PS) imagery offers 3 m spatial and daily temporal resolution, which can overcome the spatio-temporal resolution tradeoff of conventional satellites, albeit at the cost of spectral resolution. This study investigated the potential of augmenting PS imagery by integrating the spectral information from Sentinel-2 (S2) differenced Normalized Burn Ratio (dNBR) to PS differenced Normalized Difference Vegetation Index (dNDVI) using histogram matching,specifically for wildfire burn area and severity assessment of the Okgye wildfire which occurred on April 4th, 2019. Due to the difficulty in acquiring reference data, the results of the study were compared to the wildfire burn area reported by Ministry of the Interior and Safety. The burn area estimates from this study demonstrated that the histogram-matched (HM) PS dNDVI image produced more accurate burn area estimates and more descriptive burn severity intervals in contrast to conventional methods using S2. The HM PS dNDVI image returned an error of only 0.691% whereas the S2 dNDVI and dNBR images overestimated the wildfire burn area by 5.32% and 106%, respectively. These improvements using PS were largely due to the higher spatial resolution, allowing for the detection of sparsely distributed patches of land and narrow roads, which were indistinguishable using S2 dNBR. In addition, the integration of spectral information from S2 in the PS image resolved saturation effects in areas of low and high burn severity.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.58-67
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• 2008

Topography factors, as homeostasis variables at forest fire, affect the formation of fuel load patterns, atmospheric phenomena and forest fire behavior. Examination of the correlation between landforms and fire severity is important to decision making for fire hazard analysis and fighting strategies. In this study, fire severity was analyzed using Normalized Burn Ratio(NBR) derived from pre- and post-fire Landsat TM/+ETM images and landform were classified based on Topographic Position Index(TPI) in Samcheok(2000), Cheongyang(2002), and Yangyang(2005) forest fire regions. F-tests and Duncan's multi-range test between landform and fire severity showed that fire severities of headwater, high ridges, and upper slopes is higher than ones of local ridges, midslope ridges, and plains. Fire severity were more sensitive in coniferous forest than broadleaf forests.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.513-525
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• 2023

This study was conducted to compare the level of vegetation recovery based on the forest restoration techniques (natural restoration and artificial restoration) determined using the satellite imagery that targeted forest fire damaged areas in Goseong-gun, Gangwon-do. The study site included the area affected by the Goseong forest fire (1996) and the East Coast forest fire (2000). We conducted a time-series analysis of satellite imagery on the natural restoration sites (19 sites) and artificial restoration sites (12 sites) that were created after the forest fire in 1996. In the analysis of satellite imagery, the difference normalized burn ratio (dNBR) and normalized difference vegetation index (NDVI) were calculated to compare the level of vegetation recovery between the two groups. We discovered that vegetation was restored at all of the study sites (31 locations). The satellite image-based analysis showed that the artificial restoration sites were relatively better than the natural restoration sites, but there was no statistically significant difference between the two groups (p > 0.05). Therefore, it is necessary to select a restoration technique that can achieve the goal of forest restoration, taking the topography and environment of the target site into account. We also believe that in the future, accurate diagnosis and analysis of the vegetation will be necessary through a field survey of the forest fire-damaged sites.