• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.141-141
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• 2019

토양수분은 수문 분석에 있어 매우 중요한 인자 중 하나이며 최근 기후변화로 인한 가뭄, 홍수 및 산불발생과 같은 물 관련 재해 발생에 직 간접적으로 영향을 미치기 때문에 지표 토양수분산정은 매우 중요하다. Sentinel-1 SAR(Synthetic Aperture Radar)는 능동형 위성으로 10m의 공간해상도로 제공되기 때문에 기존의 토양수분 전용위성인 SMOS(Soil Moisure and Ocean Salinity), SMAP(Soil Moisture Active Passive) 및 GCOM-W1(Global Change Observation Mission Water) 등 다르게 고해상도 토양수분 산정이 가능하다. 그러나 Sentinel-1 SAR 센서에서는 고해상도 지표 관측 이미지 자료만 제공하며, 토양수분 자료를 직접적으로 제공하지 않는다. 따라서 본 연구에서는 2018년도 Sentinel-1 A/B IW(Interferometric Wide swath) 모드의 VH(Vertical Transmit - Horizontal Receive) 편파 영상과 Sentinel-1 SAR 위성자료 전처리 도구인 SNAP(Sentinel Application Platform)을 이용하여 후방산란계수를 산정하였으며, 산정된 후 방산란계수와 농촌진흥청에서 제공하는 65개 지점의 실측 TDR(Time Domain Reflectrometry) 토양수분의 관계를 이용하여 회귀모형을 도출 및 토양수분 공간분포를 산정하였다. 비록 불확실성은 어느정도 발생 하였으나, 전체적으로 TDR 관측값과 $10m{\times}10m$ 해상도의 Sentinel-1 SAR 기반 토양수분이 일치하는 경향을 보였다. 본 연구 결과는 수문, 농업, 산림, 재해 등 다양한 분야에 활용될 수 있을 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• The Korean Journal of Soil Zoology
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• v.5 no.2
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• pp.47-62
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• 2000

This study investigated the effect of soil animals at forest fire area, and it carried out the mountain located at Jundae Ri, Houeng-chen Myen, Ha-dong Gun, Kyoung-Nam Province, southern part of Korea, where burned out about 50 hectars on April 11, 1997. Vegetation of the examined area absolutely dominated with the pines of 7-14 cm in diameter and 20 to 30 years old and the rest were covered with mixed forest with a shrub such as the oak (Quereus mongolia Fisch, Quereus variabilis BI, Quereus dentana Thunb), snowbell(Styrax japonica, S, et, z), lacquer tree (Rhus trichocarpa Mig), azalea (Rhododendron mucronulatum Turcz), etc. And there were simple area organized as a herbaceous plant, and the burnt area was poor experimental sites, where litter layer and herbaceous plant disappeard due to fire, and the unburnt area was rich in surface plant, dead leaves, twigs, etc. But the ground cover vegetations were poor in the unburnt area. The distribution of each animal groups, the seasonal fluctuation in population density, the biomass of meso$.$macroarthropods and the relationship between soil animal and some environmental factors were investigated and analyzed at each experimental area. The result are summarized as follow: 1. Identificated 257,087 individuals of soil microarthropods were classified into 7 classes and 24 orders of Arachinida, Insecta, Chilopoda, Symphyla, Diplopoda, Isopoda and Oligochaeta., and identified 8,006 individuals of the total meso$.$macroarthropods were classified into 7 classes and 20 orders of Arachinida, Insecta, Chilopoda, Symphyla, Diplopoda, Isopoda and Oligochaeta. 2. Among the total soil microarthropods, Arachinida formed 70.9%, followed by Insecta for 28.4% and among the total meso$.$macroarthropod , Insecta formed 57.6%, followed by Chilopoda for 23.8%.

• Applied Chemistry for Engineering
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• v.21 no.6
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• pp.664-669
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• 2010

The forest area of domestic is 6370304 ha, which covers 70% of the whole country, and especially Gangwon-do is remarkably larger than other Province. A thick forest of the country has the most basic component among other natural environments as well as it has invaluable worth to human being such as scientific research and educational value. However due to the breakout of forest fire since 1990s, the loss of trees, destruction of natural environment and ecology, economic damage have been occurring and its scale also has become larger. The causes of becoming larger in scale are resulted from forest components which mainly consist of needle leaf trees, wide leaf trees, fallen leaves, herbaceous plants so that it has been a direct cause for forest fire. However, few research on combustion and pyrolysis characteristics has been done in domestic and abroad. The study on the combustion and pyrolysis for Pinus densiflora which are typical needle leaf trees has been tried using TGA. Pinus desiflora started to being ignited at around $162^{\circ}C$ and pyrolysis was done at around $197^{\circ}C$. Differential method was applied to calculate activation energy and frequency factor according to the variation of conversion. Activation energy in pyrolysis was increased from 79 kJ/mol to 487 kJ/mol with increasing conversion and average activation energy was 195 kJ/mol. The activation energy in combustion was decreased from 148 kJ/mol to 133 kJ/mol.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.311-311
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• 2022

전 세계적으로 기후변화 및 산업화로 인해 대규모 홍수, 가뭄, 폭염, 산불 등의 재해가 빈번하게 발생하고 있으며, 이러한 재해 및 재난을 조기에 발견하고 최소화를 위한 대응 체계 및 관리방안의 필요성이 증대되고 있다. 이러한 자연재해들의 특징은 추가 재해를 유발할 수 있다는 것으로 재해의 강도가 증가할 뿐만 아니라 여러 가지 재난 및 재해를 동시에 유발하는 형태로 변화하기 때문에, 단일자연재해 평가 기술을 바탕으로 복합자연재해에 대한 분석 및 감지가 진행되어야 한다. 최근 기후변화로 인한 기상 패턴의 변화 및 가뭄 발생빈도의 증가가 뚜렷하며, 국외에서는 폭염과 가뭄을 고려한 복합자연재해로 'Flash Drought'로 정의된 돌발가뭄에 대한 연구가 이루어지고 있다. 폭염과 가뭄은 단순 강우 부족으로 인한 가뭄, 높은 기온으로 인한 폭염 등이 서로 독립적으로 발생하는 경우와 강우부족과 폭염의 지속으로 인한 상호연관성이 존재하는 복합자연재해 등으로 구분할 수 있다. 돌발가뭄은 강수 부족 또는 폭염이 지속되거나 강도가 높아질 경우, 지면온도가 상승하여 토양수분이 필요 이상으로 증발하여 단기간에 발생하는 초단기 가뭄으로 복합자연재해에 해당하며, 이러한 돌발가뭄은 농업분야에서 작물 생장 및 영농기 활동에 큰 영향을 미치기 때문에 모니터링 및 감지 기술이 필요하다. 본 연구에서는 수문기상학적 요소를 활용하여 폭염 및 가뭄을 고려한 복합자연재해에 대한 상관분석을 수행하였다. 기상청에서 제공하는 기상자료(일최고기온/평균기온/최저기온, 강수량, 상대습도, 일조량 등)에 대한 전국 76개소 대상 기상자료를 구축하였으며, Sentinel, Landsat, MODIS(Moderate Resolution Imaging Spectroradiometer) 등과 같은 위성영상 자료를 구축하여 폭염과 가뭄에 대한 각각의 인자를 선정하고 상관 관계를 분석하였다. 본 연구의 결과는 향후 복합자연재해 감지 및 예측 기술 개발에 활용하여 재해 예방 및 대응에 대한 기초자료로 활용될 수 있을 것으로 판단된다.

• Journal of Korean Society of Forest Science
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• v.83 no.3
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• pp.322-330
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• 1994

The Universal Soil Loss Equation (USLE) has been widely used to predict long-term soil loss by incorporating several erosion factors, such as rainfall, soil, topography, and vegetation. This study is aimed to introduce the LISLE within geographic information system(GIS) environment. The Kwangneung Experimental Forest located in Kyongki Province was selected for the study area. Initially, twelve years of hourly rainfall records that were collected from 1982 to 1993 were processed to obtain the rainfall factor(R) value for the LISLE calculation. Soil survey map and topographic map of the study area were digitized and subsequent input values(K, L, S factors) were derived. The cover type and management factor (C) values were obtained from the classification of Landsat Thematic Mapper(CM) satellite imagery. All these input values were geographically registered over a common map coordinate with $25{\times}25m^2$ ground resolution. The USLE was calculated for every grid location by selecting necessary input values from the digital base maps. Once the LISLE was calculated, the resultant soil loss values(A) were represented by both numerical values and map format. Using GIS to run the LISLE, it is possible to pent out the exact locations where soil loss potential is high. In addition, this approach can be a very effective tool to monitor possible soil loss hazard under the situations of forest changes, such as conversion of forest lands to other uses, forest road construction, timber harvesting, and forest damages caused by fire, insect, and diseases.

• Atmosphere
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• v.33 no.2
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• pp.223-246
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• 2023

This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.