• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.345-352
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• 2020

Forest fires generate many types of risk as well as a wide and varied range of damage. Various studies and systems have emerged in response to wildfire disasters. International wildfire disaster safety management systems apply advanced technologies such as utilizing big data, GIS-based systems, and decision-making systems. This study analyzes South Korea's and other countries' forest fire disaster safety management systems, and suggests alternatives for wildfire disaster safety management in Korea. First, a means of integrating information, including field information, obtained by domestic agencies is proposed. Second, a method of applying big data to the disaster response system is proposed. Third, a decision-making system is applied to an existing GIS-based system. When applying the above countermeasures to Korea's existing disaster safety management system, various information and data can be visualized and thus more easily identified, leading to more effective decision-making and reduced fire damage.

• Atmosphere
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• v.20 no.2
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• pp.173-186
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• 2010

The impact of the precipitation has been focused on losses in social and economical sectors. However, as growing the concerns of the future water shortage caused by the climate change, the precipitation should be consider in various views for an effective planning in the water resource management. A precipitation case occurred from 20 to 21 April 2009 was recorded as a welcome rain because it reduced the severe drought continued in Korea from winter season of 2008. In this study, economic values of the event was calculated with positive aspects in various sectors. The estimation is based on four major parts such as a secure of water resources, the improvement of air quality, the decrease of forest fires, and the reduction of the drought impact. The water resources only considered inflow waters into dams and the reservoirs managed by Korean public institutions and their economic values accounts for 5.92 billion won. Decreases of four air pollutants($PM_{10}$, $NO_2$, CO, and $SO_2$) were considered as the positive effects of the rainfall and estimated 175.4 billion won. The preventive effect of the forest fire after the rainfall results in 0.48 billion won. Finally, the rainfall during the drought period is effective to reduce the social costs of 108.65 billion won. Although the economic values estimated in this study explain parts of the positive effects of the precipitation, it can help to develop a comprehensive and systematic valuation system for the whole process of the precipitation. For doing this, various rainfall types should be analyzed in social-economic terms including economics, environments and hydrology.

• 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.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.121-129
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• 2012

The edge area with burn severity is known as significant factor that has great effects on the ecosystem recovery. However, there is little study on the edge area and its effects in the South Korea. Thus, this study aimed to analyze immediate responses of vegetation following forest fires due to combined effect of burn severity and edge-interior effect. Burn Severity (BS), or ${\Delta}NBR$ values were computed using satellite images of pre and post-forest fire in Samcheock areas. The burn forest was classified 231 $1-km^2$ girds and these grids were further reclassified into 4 groups by BS type (low BS and high BS areas) and forest areas (edge areas and interior areas). These four groups of grids including low BS-interior (group A), low BS-edge (group B), high BS-interior (group C) and high BS-edge (group D). Post-fire vegetation responses measured with (${\Delta}NDVI$) among four groups were then compared and tested by T-test. The results indicated that group C (${\Delta}NDVI$=0.047) and D (${\Delta}NDVI$ = 0.059) showed considerably greater vegetation regeneration than those of low BS areas including group A (${\Delta}NDVI$ = -0.039) and group B (${\Delta}NDVI$ = -0.036). It was also observed that edges areas showed greater vegetation regeneration than interior areas when BS is the same. Group B (${\Delta}NDVI$ = -0.036) showed greater (${\Delta}NDVI$) values than group A (${\Delta}NDVI$ = -0.039) in low BS condition. Similar relationship is observed between group C and group D in high BS condition. Thus adequate restoration practices for burned areas might need to pay close attention to interior areas with low BS to minimize the secondary damages and to rehabilitate the burned forests.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• Korean Journal of Environment and Ecology
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• v.38 no.2
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• pp.178-188
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• 2024

The dynamics of suspended sediment (SS) in forested catchments vary depending upon human or natural disturbances, including land use change, forestry activity, forest fires, and landslides. Understanding the dynamics of SS originating from the potential sources within a forested catchment is crucial for establishing an effective water quality management strategy. Therefore, to suggest a systematic method for interpreting SS dynamics, we evaluated the performance and applicability of ten methods for calculating the hysteresis index based on observed hydrological data and two calculation models (Lawler's method and Lloyd's method) with five sampling intervals (50th, 25th, 10th, 5th, and 1st percentiles). Our results showed that Lloyd's method, which used a sampling interval at the 1st percentile, had the largest number of analyzable runoff events and exhibited the best performance. The results of this study can contribute to quantifying the hysteresis in the relationship between discharge and SS and provide useful information for interpreting SS dynamics.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.569-572
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• 2002

Terra MODIS is one of the few space-borne sensors currently capable of acquiring radiometric data over the range of view angles. Institute of Industrial Science, University of Tokyo, has been receiving Terra MODIS data at Tokyo since May 2001 and Asian Institute of Technology at Bangkok since May 2001. They can cover whole East Asia and is expected to monitor environmental changes regularly such as deforestation, forest fires, floods and typhoon. Over eight hundred scenes have been archived in the storage system and they occupy 2 TB of disk space so far. In this study, MODIS data processing system on WWW is developed including following functions: spectral subset (250m, 500m, 1000m channels), radiometric correction to radiance, spatial subset of geocoded data as a rectangular area with latitude-longitude grid system in HDF format, generation of a quick look file in JPEG format. Users will be notified just after all the process have finished via e-mail. Using this system enables us to process MODIS data on WWW with a few input parameters and download the processed data by FTP access. An easy to use interface is expected to promote the use of MODIS data. This system is available via the Internet on the following URL from September 1 2002, "http : //webmodis.iis.u-tokyo.ac.jp/".