• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.119-121
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• 2012

수문순환과정의 시공간적 거동의 해석 및 정량화는 효율적인 수자원 관리 및 계획을 위해서 반드시 선행되어야 하는 연구이다. 그러나 현재 국내의 수문순환과정을 분석하는 연구는 매우 미비한 실정이다. 특히 수문기상인자 중 토양수분은 지표와 대기에서 물과 에너지를 연결해주는 중요한 인자중 하나로 그 중요성 대두되고 있지만 관측시설의 제한과 큰 시공간 변동성을 가지고 있을 값을 추정하는데 어려움이 있다. 최근에는 이를 보완하기 위하여 선진국을 중심으로 연구되고 있는 원격탐사 기술을 도입하였다. 특히 원격탐사를 통해 산정된 Normilized Difference vegetation Index (NDVI) 와 토양수분과의 관계를 파악하기 위한 많은 연구들이 진행되어 왔다. NDVI는 토양수분에 직, 간접적인 영향을 주는 식생의 활동을 나타내는 인자이다. 이러한 이유로 많은 연구에서 NDVI와 토양수분과의 관계에 대해 규명해 왔으며, NDVI를 통한 토양수분의 추정 및 검증이 이루어졌다. 본 연구에서는 Moderate Resolution Imaging Spectroradiometer (MODIS) 에서 산정된 식생지수와 토양수분의 실측데이터를 이용하여 관측지에서의 식생지수와 토양수분의 관계를 규명한 후, 이 관계를 이용하여 관측 지역 이외의 장소의 토양수분 값을 추정 할 것이다.

• 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.

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.53-59
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• 2013

The purpose of this study was to analyze the topographic effect of the LAI (Leaf Area Index), which has been widely used as an index that quantifies the structure of forest vegetation in Deogyusan National Park. With this aim, the study was conducted through a regression analysis which took as explanation the following variables: the elevation, slope, aspect, and soil moisture conditions. The LAI was taken as the response variable. Overall, the correlation between the Field-LAI and topographic factors was less than 0.5, which was relatively low. Except for topographic altitude, there was no statistical significance regarding the correlation with other factors. Meanwhile, regarding the orientation of the correlation, the higher the attitude, the steeper slope, the lower the soil moist, the lower the LAI value. The topographic altitude was found as a statistically significant explanation variable. The TWI (Topographic Wetness Index), which was used in this study to explain the soil moisture conditions, was not significantly related to the LAI distribution. The results of this study are expected to be utilized as basic data in more accurate forecasting the LAI distribution using remote sensing data.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.5
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• pp.507-512
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• 2005

This research focuses on the development and application of a method for the detection of m-toluate in soils using a genetically engineered bioluminescent bacteria, Pseudomonas putida mt-2 KG1206. KG1206 produces light by direct (m-toluate and benzoate) and indirect (toluene analogs) inducers. For detection of m-toluate in soil system, 9.9 mL strain was amended with 0.1 mL soil ethanol extractant. A high correlation ($r^2>0.97$) was observed between bioluminescence and m-toluate concentration. The unknown concentrations of m-toluate in soil samples were pre-determined using a method developed based on bioluminescence activity of strain with extracted inducers. Values between by LC analysis and bioluminescence activity show moderate statistical results. These results demonstrate the feasibility of recombinant bioluminescent microorganism, engineered to generate a quantifiable bioluminescence signal in response to specific pollutants, may serve as combined sensing and reporting tools in environmental monitoring.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.34-44
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• 2024

Recently, due to abnormal climate caused by climate change, natural disasters such as floods, landslides, and soil outflows are rapidly increasing. In Korea, more than 63% of the land is vulnerable to slope disasters due to the geographical characteristics of mountainous areas, and in particular, Quarry mines soil and rocks, so there is a high risk of landslides not only inside the workplace but also outside.Accordingly, this study built a DEM using UAV and aviation LiDAR for monitoring the quarry, conducted a time series change analysis, and proposed an optimal DEM construction method for monitoring the soil collection site. For DEM construction, UAV and LiDAR-based Point Cloud were built, and the ground was extracted using three algorithms: Aggressive Classification (AC), Conservative Classification (CC), and Standard Classification (SC). UAV and LiDAR-based DEM constructed according to the algorithm evaluated accuracy through comparison with digital map-based DEM.

• Korean Journal of Environmental Agriculture
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• v.27 no.2
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• pp.120-132
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• 2008

Remotely sensed images from a satellite can be applied for detecting and quantifying spatial and temporal variations in terms of landuse & landcover, crop growth, and disaster for agricultural applications. The purposes of this study were to analyze topography using DEM(digital elevation model) and classify landuse & landcover into 10 classes-paddy field, dry field, forest, bare land, grass & bush, water body, reclaimed land, salt farm, residence & building, and others-using Landsat TM images in North Korea. Elevation was greater than 1,000 meters in the eastern part of North Korea around Ranggang-do where Kaemagowon was located. Pyeongnam and Hwangnam in the western part of North Korea were low in elevation. Topography of North Korea showed typical 'east-high and west-low' landform characteristics. Landcover classification of North Korea using spectral reflectance of multi-temporal Landsat TM images was performed and the statistics of each landcover by administrative district, slope, and agroclimatic zone were calculated in terms of area. Forest areas accounted for 69.6 percent of the whole area while the areas of dry fields and paddy fields were 15.7 percent and 4.2 percent, respectively. Bare land and water body occupied 6.6 percent and 1.6 percent, respectively. Residence & building reached less than 1 percent of the country. Paddy field areas concentrated in the A slope ranged from 0 to 2 percent(greater than 80 percent). The dry field areas were shown in the A slope the most, followed by D, E, C, B, and F slopes. According to the statistics by agroclimatic zone, paddy and dry fields were mainly distributed in the North plain region(N-6) and North western coastal region(N-7). Forest areas were evenly distributed all over the agroclimatic regions. Periodic landcover analysis of North Korea based on remote sensing technique using satellite imagery can produce spatial and temporal statistics information for future landuse management and planning of North Korea.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.19-31
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• 2024

Ports are vital social infrastructures that significantly influence both people's lives and a country's economy. In South Korea, the aging of port infrastructure combined with the increased frequency of various natural disasters underscores the necessity of displacement monitoring for safety management of the port. In this study, the time-series displacements of Yeongilman Port and surrounding areas in Pohang, South Korea, were measured by applying Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) to Sentinel-1 SAR images collected from the satellite's ascending (February 2017-July 2023) and descending (February 2017-December 2021) nodes, and the displacement associated with the 2017 Pohang earthquake in the port was analyzed. The southern (except the southernmost) and central parts of Yeongilman Port showed large displacements attributed to construction activities for about 10 months at the beginning of the observation period, and the coseismic displacement caused by the Pohang earthquake was up to 1.6 cm of the westward horizontal motion and 0.5 cm of subsidence. However, little coseismic displacement was observed in the southernmost part of the port, where reclamation was completed last, and in the northern part of the oldest port. This represents that the weaker the consolidation of the reclaimed soil in the port, the more vulnerable it is to earthquakes, and that if the soil is very weakly consolidated due to ongoing reclamation, it would not be significantly affected by earthquakes. Summer subsidence and winter uplift of about 1 cm have been repeatedly observed every year in the entire area of Yeongilman Port, which is attributed to volume changes in the reclaimed soil due to temperature changes. The ground of the 1st and 2nd General Industrial Complexes adjacent to Yeongilman Port subsided during the observation period, and the rate of subsidence was faster in the 1st Industrial Complex. The 1st Industrial Complex was observed to have a westward horizontal displacement of 3 mm and a subsidence of 6 mm as the coseismic displacement of the Pohang earthquake, while the 2nd Industrial Complex was analyzed to have been little affected by the earthquake. The results of this study allowed us to identify the time-series displacement characteristics of Yeongilman Port and understand the impact of earthquakes on the stability of a port built by coastal reclamation.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.353-365
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• 1998

Light absorption coefficient per unit mass of particles, i.e., specific absorption coefficient, is important as one of the main parameters in developing algorithms for ocean color remote sensing. Specific absorption coefficient of chlorophyll ($a^*_{ph}$) and suspended sediment ($a^*_{ss}$) were analyzed with a spectrophotometer using the "wet filter technique" and "Kishino method" for the seawater collected in the Yellow and Mediterranean Sea. An improved data-recovery method for the filter technique was also developed using spectrum slopes. This method recovered the baselines of spectrum that were often altered in the original methods. High $a^*_{ph}({lambda})$ values in the oligotrophic Mediterranean Sea and low values in the Yellow Sea were observed, ranging 0.01 to 0.12 $m^2$/mg at the chlorophyll maximum absorption wavelength of 440 nm. The empirical relationship between $a^*_{ph}$(440nm) and chlorophyll concentrations () was found to fit a power function ($a^*_{ph}$=0.039 $^{-0.369}$), which was similar to Bricaud et al. (1995). Absorption specific coefficients for suspended sediment ($a^*_{ss}$) did not show any relationship with concentrations of suspended sediment. However, an average value of $a^*_{ss}$ ranging 0.005 - 0.08 $m^2$/g at 440nm, was comparable to the specific absorption coefficient of soil (loess) measured by Ahn (1990). The morepronounced variability of $a^*_{ss}$ than $a^*_{ph}$ was determined from the variable mixing ratio values between particulate organic matter and mineral. It can also be explained by a wide size-distribution range for SS which were determined by their specific gravity, bottom state, depth and agitation of water mass by wind in the sea surface.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.325-338
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• 2023

Korean fir (Abies koreana Wilson) is one of the most important environmental indicator tree species for assessing climate change impacts on coniferous forests in the Korean Peninsula. However, due to the nature of alpine and subalpine regions, it is difficult to conduct regular field surveys of Korean fir, which is mainly distributed in regions with altitudes greater than 1,000 m. Therefore, this study analyzed the vegetation change trend of Korean fir using regularly observed remote sensing data. Specifically, normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), land surface temperature (LST), and precipitation data from Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievalsfor GPM from September 2003 to 2020 for Hallasan and Jirisan were used to analyze vegetation changes and their association with environmental variables. We identified a decrease in NDVI in 2020 compared to 2003 for both sites. Based on the NDVI difference maps, areas for healthy vegetation and high mortality of Korean fir were selected. Long-term NDVI time-series analysis demonstrated that both Hallasan and Jirisan had a decrease in NDVI at the high mortality areas (Hallasan: -0.46, Jirisan: -0.43). Furthermore, when analyzing the long-term fluctuations of Korean fir vegetation through the Hodrick-Prescott filter-applied NDVI, LST, and precipitation, the NDVI difference between the Korean fir healthy vegetation and high mortality sitesincreased with the increasing LST and decreasing precipitation in Hallasan. Thissuggests that the increase in LST and the decrease in precipitation contribute to the decline of Korean fir in Hallasan. In contrast, Jirisan confirmed a long-term trend of declining NDVI in the areas of Korean fir mortality but did not find a significant correlation between the changes in NDVI and environmental variables (LST and precipitation). Further analyses of environmental factors, such as soil moisture, insolation, and wind that have been identified to be related to Korean fir habitats in previous studies should be conducted. This study demonstrated the feasibility of using satellite data for long-term monitoring of Korean fir ecosystems and investigating their changes in conjunction with environmental conditions. Thisstudy provided the potential forsatellite-based monitoring to improve our understanding of the ecology of Korean fir.