• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.209-214
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• 2004

Time Domain Reflectometry with multiplex system has been installed to configure the spatial and temporal characteristics of soil moisture in a mountainous hillslope. An intensive surveying was performed to build a refined digital elevation model and flow determination algorithms with inverse surveying have been applied to establish an efficient soil monitoring system. Steady state wetness index, quasi-dynamic wetness index and fully dynamic wetness index have been calculated. Continuous monitoring of soil moisture data were analyized with wetness indices. Limitations and hydrological interpretations of this approach have beer discussed.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.961-969
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• 2003

Formulation of quasi-dynamic wetness index was derived to predict the spatial and temporal distribution of the soil moisture. The algorithm of dynamic wetness index was developed through introducing the convolution integral with the rainfall input. The spatial and temporal behaviors of the wetness index of the Sulmachun Watershed was calculated using the digital elevation model(DEM) and the rainfall data for two years. The spatial distribution of the dynamic wetness index shows most dispersive feature of flow generation among the three assumptions of steady, quasi-dynamic and dynamic. The statistical distribution of the quasi-dynamic wetness index and the dynamic wetness index approximate to the steady state wetness index as the time step is increased. The dynamic wetness index shows mixed distribution of the normalized probability density function.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.587-596
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• 2014

Soil moisture is one of the most important interests in hydrological response and the interaction between the land surface and atmosphere. Estimation of Antecedent Wetness Conditions (AWC) which is soil moisture condition prior to a rainfall in the basin should be considered for rainfall-runoff prediction. In this study, Soil Wetness Index (SWI), Antecedent Precipitation Index ($API_5$), remotely sensed Soil Moisture ($SM_{rs}$), and 5 days ground Soil Moisture ($SM_{g5}$) were selected to estimate the AWC at four study area in the Korean Peninsula. The remotely sensed soil moisture data were taken from the AMSR-E soil moisture archive. The maximum potential retention ($S_{obs}$) was obtained from direct runoff and rainfall using Soil Conservation Service-Curve Number (SCS-CN) method by rainfall data of 2011 for each study area. Results showed the great correlations between the maximum potential retention and SWI with a mean correlation coefficient which is equal to -0.73. The results of time length representing the time scale of soil moisture showed a gap from region to region. It was due to the differences of soil types and the characteristics of study area. Since the remotely sensed soil moisture has been proved as reasonable hydrological variables to predict a wetness in the basin, it should be continuously monitored.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.251-261
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• 2003

The resolution issue of various soil moisture prediction parameters such as wetness index and curvatures is addressed. The sensitivities of various index are discussed on the base of the statistical aspects. The statistical analysis of three flow determination algorithms on the DEM is performed. The upslope area associated with SFD algorithm appear to more sensitive than the parameters of the other algorithms(MFD, DEMON). The wetness index shows relatively less variation both in resolution and the calculation Procedures.

• Spatial Information Research
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• v.10 no.3
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• pp.481-492
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• 2002

The severity and spatial Patterns of spring drought on the croplands arc investigated using satellite imagery(Landsat ETM+). It is necessary to analyze the area droughty conditions in order to decrease the damage and make the efficient policies. In this context, the information about soil moisture levels, which were fatal factors to the crop growth, was acquired from wetness calculated from Tasseled cap transformation. We confirmed that the wetness values have a strong correlation with NDVI and the principal components. The result showed that the intensity of vegetation covering the surface could be understood as the index of the impacts of drought on croplands and these relationships were effective to classify dry areas in satellite imagery.

• Journal of the Korean earth science society
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• v.25 no.8
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• pp.754-763
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• 2004

This study was aimed to examine the Landsat Enhanced Thematic Mapper Plus (ETM+) index, which matches well with the field survey data in the wildfire area of Gangneung, Gangweon Province, Korea. In the wildfire area NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index), and Tasseled Cap Transformation Index (Brightness, Wetness, Greenness) were compared with field survey data. NDVI and SAVI were very useful in detecting the difference between the wildfire and non-wildfire area, but not so in classify the soil types in the wildfire area. The soil plane based on the Tasseled Cap Transformation showed a better result in classifying the soil types in the wildfire areas than NDVI and SAVI, and corresponded well with field survey data. Using a linear function based on greenness and wetness in the Tasseled Cap Transformation is expected to provide a more efficient and quicker method to classify wildfire areas.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.73-82
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• 2018

In this study, we assessed meteorological and agricultural drought based on the SPI(Standardized Precipitation Index), SMP(Soil Moisture Percentile), and SMDI(Soil Moisture Deficit Index) indices using satellite-based TRMM(Tropical Rainfall Measuring Mission)/GPM(Global Precipitation Measurement) images at the province of Chungcheongbuk-do. The long-term(2000-2015) TRMM/GPM precipitation data were used to estimate the SPI values. Then, we estimated the spatially-/temporally-distributed soil moisture values based on the near-surface soil moisture data assimilation scheme using the TRMM/GPM and MODIS(MODerate resolution Imaging Spectroradiometer) images. Overall, the SPI value was significantly affected by the precipitation at the study region, while both the precipitation and land surface condition have influences on the SMP and SMDI values. But the SMP index showed the relatively extreme wet/dry conditions compared to SPI and SMDI, because SMP only calculates the percentage of current wetness condition without considering the impacts of past wetness condition. Considering that different drought indices have their own advantages and disadvantages, the SMDI index could be useful for evaluating agricultural drought and establishing efficient water management plans.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.272-276
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• 2004

화강암에 대한 화학적 풍화특성과 풍화 정도의 정량적으로 표현하기 위한 방법으로 조사지역의 지형자료에 기초한 습윤지수(wetness indes)를 산정하였으며, 중화속도 및 등급을 산정하였다. 습윤지수는 지형 고도를 이용하여 2-5m 크기의 격자로 구성 된 수치고도모형을 작성하여 계산하였으며 풍화속도와 등급은 Profile model을 이용하였다. 연구대상지역은 마산지역과 서부산지역으로 집수지형을 지시하는 습윤지수의 분포는 마산지역에서 다소 높은 지수 값을 보인다. 임계부하량(critical loads)에 의한 풍화등급은 마산 가포동 지역과 서부산 견마도 지역은 각각 3등급과 4등급에 해당하여 견마도 일원에서 높은 풍화 정도를 지시한다. 이와 같은 결과는 동일한 화강암 분포지의 경우에도 구성 광물의 비율과 기온과 강수량과 같은 지역적인 특성에 따라 상이한 풍화 경향이 나타남을 지시한다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.78-90
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• 2005

The spatial and temporal distribution of soil moisture was characterized from soil moisture data through the intensive monitoring using Time Domain Reflectometry (TDR). The recession of soil moisture after a rainfall event was characterized and the empirical equation was used in the recession curve analysis. Recession analysis provides features of soil moisture variation such as recharge and stability depending upon locations of monitoring. The wetness index was useful for explaining spatial and temporal distributions of soil moisture and recession characteristics at hillslope scale.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.583-590
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• 2008

This study presents a correlation between timber Age, image bands and vegetation indices for timber age estimation. Basically, this study used Landsat TM images of three difference years (1994, 1994, 1998) and difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED). Bands of 4, 5 and 7, Normalized Difference Vegetation Index (NDVI), Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SA VI) were obtained from Landsat TM images. Tasseled cap - greenness and wetness images were also made by Tasseled cap transformation. Finally, analysis of correlation between timber age, difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED), individual TM bands (4, 5, 7), Normalized Difference Vegetation Index (NDVI), Tasseled cap-Greenness, Wetness, Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SAVI) using regression model. In this study about 1,992 datasets were analyzed. The Tasseled cap - Wetness, Infrared Index (II) and Vegetation Condition Index (VCI) showed close correlation for timber age estimation.