• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.99-102
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• 2012

지표면 온도는 토지피복의 상태, 식생의 분포 상태, 토양수분, 증발산 등의 영향으로 많은 차이를 가지게 되며, 지면-대기의 상호순환의 중요한 인자로써 기후모델 및 농업 등의 기본적인 데이터로 사용되고 있다. 이러한 지표면의 온도를 정확하게 파악하는 것은 수문학적 관점 및 기상적인 관점에서 매우 중요하다. 기존에 LST (Land Surface Temperature, 지표면온도), ET (EvapoTranspiration, 증발산), NDVI (Normalized Difference Vegetation Index, 정규식생지수) 등의 검증이 많이 이루어진 MODIS위성의 Terra/Aqua센서는 한반도를 스캔하고 지나갈 때의 순간적인 데이터를 산출된다. 공간적인 면에서는 많은 이점이 있으나 시간적인 면에서는 시간에 따른 인자들의 변동성을 파악 하는데는 많은 문제가 있다. 그렇기 때문에 시 공간적으로 변화양상을 측정 할 수 있는 정지궤도위성의 중요성이 대두되고 있다. 본 연구에서는 국내에서 2010년 6월 27일 발사된 정지궤도위성인 천리안의 데이터를 활용하였다. 천리안 위성은 기상 센서와 해양관측 센서 그리고 통신센서를 가진 위성이다. 천리안 위성의 기상 센서는 MTSAT-1 위성과 같은 적외선 센서를 탑재하고 있으며, 평시에는 15분 단위의 데이터를 산출하게 된다. 천리안에서 제공되는 많은 Product(강우강도, 해수면온도, 가강수량, 지구방출복사 등)는 수자원 및 기상에 관련된 데이터가 제공된다. 하지만 아직 검증이 많이 이루어지지 못하였다. 그래서 천리안 위성 데이터인 지표면 온도자료를 이용하여 천리안 위성의 효율성에 대해서 알아보고자 하며, 기존의 검증이 많이 이루어진 MODIS의 데이터와의 상관성을 분석하고 지상과의 관계를 검증 및 비교하여 천리안 위성의 활용성에 대해서 알아보려고 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.208-208
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• 2016

수문순환과정의 시공간적 거동을 해석하고 이를 정량화 하는 것은 효율적인 수자원 관리 및 계획을 위해 반드시 선행되어야 하는 연구이다. 특히 토양수분은 물 에너지 순환에서 지표면과 대기 사이의 복잡한 관계를 이해하기 위한 중요한 수문인자로, 이를 정확하게 측정하기 위한 방법들이 다각도로 발전되어 왔다. 그 중 위성 데이터를 활용한 토양수분 산정은 미계측 지역의 토양수분을 지속적이고 광역적이게 관측할 수 있는 선진 기술로 각광받고 있다. 그러나 대부분의 위성 자료들이 가지고 있는 공간 해상도는 복잡한 지형 환경을 대상으로 한 지역의 원격 탐사로서는 국지적인 수문학적 현상들을 분석하는데 어려움을 가지고 있다. 특히 우리나라의 경우 국토의 70% 정도가 산지로 이루어져 있으며 경사도가 $5^{\circ}$ 이하의 평탄한 지역은 약 23%에 그치는 등 복잡한 식생 지형 환경을 가지고 있다. 따라서 인공위성의 해상도와 식생 투과도를 고려할 때 저 해상도의 위성 토양수분만으로는 우리나라와 같이 면적에 비해 복잡한 환경에 기반 한 수문학적 현상들을 충분히 분석하는데 한계점이 있다. 따라서 본 연구에서는 support vector machine (SVM) 기계학습을 활용하여 ASCAT과 AMSR2 위성 토양수분의 상세화를 수행하여 고해상도의 토양수분을 산정하였고, 이를 지점관측 자료와 비교해 상세화도 자료의 신뢰성을 평가하였다. 검증된 고해상도 토양수분 데이터는 향후 자연재해 분석에 있어 예측의 정확성을 높이고 수문순환 및 기후 모델링에 있어서 중요한 입력 인자로 활용될 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.72-72
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• 2021

가뭄은 수개월, 수년 이상에 걸쳐 서서히 발생 및 지속되며, 식생에 대한 피해가 발생할 때까지 확실한 인식이 어렵다. 최근에는 기후변화로 인하여 가뭄의 발생빈도가 증가하고 있으며, 기상 이상에 따른 다양한 형태의 가뭄이 발생하고 있다. 미국에서 정의한 'Flash Drought'는 비교적 짧은 기간 동안 표면온도의 상승과 비정상적으로 낮고 빠르게 감소하는 토양수분으로 인하여 식생에 대한 극심한 스트레스를 유발하면서 광범위한 작물 손실 및 용수공급 감소 등에 대한 피해를 야기하는 가뭄이다. 국내에서는 Flash Drought에 대한 모니터링이 활성화되지 않았기 때문에 본 연구에서는 '돌발가뭄'이라는 새로운 정의를 제시하면서 토양수분, 증발산량, 강수량, 기온 등의 가뭄 관련 주요인자를 활용하여 국내에서 발생한 돌발가뭄 (Flash Drought)를 감지하고 분석하고자 하였다. 돌발가뭄을 분석하기 위하여 선행연구에서 제시한 가뭄 관련 주요인자 기준 유형, 증발산량 기반 가뭄지수를 활용한 유형 등을 활용하였으며, 지상관측자료로는 국내 76개 종관기상관측 자료를 활용하였다. 또한, 토양수분 자료는 GRACE (Gravity Recovery and Climate Experiment) 위성영상 자료를 취득한 후 5 km 공간해상도 자료로 활용하였다. 가뭄지수의 경우 증발산 기반 가뭄지수 중 표준강수증발산지수 SPEI (Standardized Precipitation Evapotranspiration), 증발스트레스지수 ESI (Evaporative Stress Index) 등을 활용하여 국내 돌발가뭄 유형에 대한 분석에 적용하였다. 본 연구를 통하여 아직 명확하게 정의되지 않은 돌발가뭄에 대한 유형별 분석 및 국내 돌발가뭄의 수문기상학적 특성을 분석하고자 한다.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.144-154
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• 2017

The riparian vegetation is one of corridor type ecosystems, an ecotone and able to improve the ecological soundness by structural and functional link. And they act as habitats, sources and sinks of species, conduits, filters and barriers. This study was carried out to develop the vegetation model for the fluctuation areas of lake reservoirs consider of hydrologic and soil environments according to the vegetation structure of the reference ecosystem. To develop the case study, 2 sites within 10degree slope of the Daecheong Lake were selected. The riparian vegetation models were built by the results of GIS analysis, remote satellite analysis, field survey results, consider of water level, flooded frequency, soil and topographic index, land cover or land use etc. 1) study area varied from FWL to -5m of NFWL, 2) slope 10% below, 3) vegetations flooded below 100days yearly are Salix koreensis, Salix chaenomeloides, Salix gracilistyla, 4)land cover type classified wildlife grassland, abandoned paddy field, cropland according to landuse (or landcover), 5)finally model was constructed as ecological landscape forest. The model designs were suggested by 2 types in Daecheong lake reservoir. The model for the riparian vegetation corridors could be the basic and useful data to improve the ecological and landscape properties.

• Journal of Ecology and Environment
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• v.29 no.6
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• pp.521-529
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• 2006

This study was carried out to classify all forest vegetation types in Ulleung Island, Korea using the methodology of the Z.-M. school's phytosociology, and map out the spatial distribution patterns of those vegetation types. The forest vegetation was classified into the mountain forest type (Acer okamotoanum community group) and maritime forest type (Artemisia scoparia community group). Vegetation units at the community level were divided into three categories; six communities, sixteen groups, and seven subgroups, giving a total of 22 communities. Total area for mapping was 5,544.9 ha, of which Fagus engleriana community accounted for 1,952 ha (35.2%), Hedera rhambea community ror 1,196 ha (21.6%), Camellia japonica community for 1,104 ha (19.9%), Sambucus sieboldiana var. pendula community for 612 ha (11.0%), Aster spathulifolius community for 506 ha (9.1%), and Tsuga sieboldii - Pinus parviflora community for 174 ha (3.1%). According to canonical correspondence analysis (CCA), variables such as $Mg^{2+}$, pH, $Ca^{2+}$ were positively correlated in maritime vegetation types, and variables such as total nitrogen, carbon content, C/N ratio and ration exchange capacity (CEC) were highly correlated in mountain vegetation types, respectively. The sea level and the slope direction were not showing regular trend as a factor to decide on species diversity, evenness and richness in this research area. But it seems to be affected by topography, slope degree and dominance vegetation.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.450-457
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• 2001

This study aimed to clarify the influencing site factors of the mesopore ratio on a pore geometry of surface soil in deciduous stands as an index of the water retention capacity. Fifteen factors including site conditions and soil properties were analyzed by spss/pc+ for the data collected during March to October of 1994. The factors influencing the mesopore ratio(pF2.7) on the surface soil were as follows; tree height, under vegetation coverage and organic matter contents of soil. And influencing factor on the ratio of mesopore in the soil surface was correlated with surface soil hardness shows high negative significance. Also, multiple regression equations for mesopore ratios of surface soil hardness, organic matter contents of soils show high significance($R^2=0.84$). In deciduous stands, it is effective in promoting development on the ratio of mesopore that forest practice for enhancing of the water resource retention capacity should be carried out when the under vegetation coverage rates of stands are maintained from 30 to 80 percentages.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1995.12a
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• pp.22-32
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• 1995

The purpose of this study is to estimate not only the watershed soil loss but also its temporal changes of Kyungan River basin, the study area, due to the land development. To analyze the soil loss of the river basin, USLE was employed. GIS and remote sensing were also utilized to estimate the soil loss. The data for this analysis consist of a series of thematic map and remotely sensed data. The remotely sensed images for this study are Landsat TM(Oct, 28, 1997 & Sep. 22, 1992), In Kyungan River basin, not only the detection of temporal changes of land use and GVI, but also the estimation of soil loss provided very significant factors that affect to the watershed environment quality. The management of the factors of vegetative cover, slope steepness and length were the keys to reduce soil loss and solve conservation and protection issues of Kyungan River basin. GIS application with USLE to the watershed analysis allows the planner to recognize sensitive sites and to plan strategies to minimize soil loss.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.1
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• pp.27-37
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• 2001

Soil erosion by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. As the interest in environment is increasing lately, soil erosion is considered as a serious problem, whereas the systematic regulation and analysis for that have not established yet. This research shows the method of extracting factor entered model which expects soil erosion by GSIS. There are several erosion model such as ANSWER, WEPP, RUSLE. The research used RUSLE erosion model which could expect general soil erosion connected easily with GSIS data. RUSLE's input factors are composed of rainfall runoff factor(R). soil erodibility factor(K), slope length factor(L), slope steepness factor(S), cover management factor(C) and support practice factor(P). The general equation used to extract L, S factor on the RUSLE to be oriented for agricultural area has some limitation to apply whole watershed. So, on this study we used a revised empirical equation applicable to the watershed by grid on the GSIS. Also, we analyzed RUSLE factors by watershed being analyzed with watershed extraction algorithm. Then we could calculate the minimum, maximum. mean and standard deviation of RUSLE factors by watershed.

• Journal of Wetlands Research
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• v.12 no.2
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• pp.59-65
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• 2010

Wetlands are a well known ecosystem which have high spatial-temporal heterogeneity of chemical characteristics. This high heterogeneity induces diverse biogeochemical processes, such as aerobic decomposition, denitrification, and plant productivity in wetlands. Understanding the dynamics of dissolved organic carbon (DOC) and inorganic nitrogen in wetlands is important because DOC and inorganic nitrogen are main factors controlling biological processes in wetlands. In this study, we assessed spatial distribution of DOC and inorganic nitrogen with relation to the different hydrology and vegetation in created wetlands. Both DOC and nitrate contents were significantly higher in vegetated areas than open areas. Different water levels also affected DOC contents and their quality. Average DOC contents were $0.37mg{\cdot}g^{-1}$ in deep riparian (DR) and $0.31mg{\cdot}g^{-1}$ in shallow riparian (SR). These results appeared to be related to the interaction between carbon supply by vegetation and microbial decomposition. On the other hand, inorganic nitrogen contents were not affected by water level differences. This result indicates that presence/absence of vegetation could be a more important factor than hydrology in the spatial dynamics of inorganic nitrogen. In conclusion, we observed that vegetation and hydrology differences induced spatial distribution of carbon and nitrogen which are directly related to biogeochemical processes in wetlands.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.81-91
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• 2021

Synthetic Apreture Radar (SAR) is attracting attentions with its possibility of producing high resolution data that can be used for soil moisture estimation. High resolution soil moisture data enables more specific observation of soil moisture than existing soil moisture products from other satellites. It can also be used for studies of wildfire, landslide, and flood. The SAR based soil moisture estimation should be conducted considering vegetation, which affects backscattering signals from the SAR sensor. In this study, a SAR based soil moisture estimation at regions covered with various vegetation types on the middle area of Korea (Cropland, Grassland, Forest) is conducted. The representative backscattering model, Water Cloud Model (WCM) is used for soil moisture estimation over vegetated areas. Radar Vegetation Index (RVI) and in-situ soil moisture data are used as input factors for the model. Total 6 study areas are selected for 3 vegetation types according to land cover classification with 2 sites per each vegetation type. Soil moisture evaluation result shows that the accuracy of each site stands out in the order of grassland, forest, and cropland. Forested area shows correlation coefficient value higher than 0.5 even with the most dense vegetation, while cropland shows correlation coefficient value lower than 0.3. The proper vegetation and soil moisture conditions for SAR based soil moisture estimation are suggested through the results of the study. Future study, which utilizes additional ancillary vegetation data (vegetation height, vegetation type) is thought to be necessary.