• 대한토목학회논문집
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• 제36권6호
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• pp.1011-1021
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• 2016

본 연구에서는 유역에서의 잠재적인 홍수위험도를 예측하기 위해서 지형도, 토양도, 토지이용도를 조합하여 해석하였다. 유역에서의 표고자료, 토양도자료 및 토지이용자료 등을 활용하여 유출생성지도와 유출누적지도를 작성하였고, 이를 홍수위험지도 작성에 활용하였다. 유출생성지도 작성을 위해 토지이용, 토양두께, 불투수성, 토양침식도, 그리고 지형기복을 유출인자로 고려하였고, 유출누적지도 작성을 위해 토지이용, 경사도, 유출 천이점, 그리고 저지대분석 결과를 이용하였다. 지도 작성을 위해 다기준의사결정법의 하나인 TOPSIS 기법을 적용하였고, 유출생성 및 누적과 관련한 인자들을 평가기준으로, 각 분석지역의 격자들을 대안으로 고려하였다. 제안된 방법론을 낙동강의 감천유역에 적용하였으며, 기존의 홍수위험지도 작성방법과 비교하여 합리적인 범위내에서 잘 일치하는 것을 확인할 수 있었다. 본 연구에서 제안한 방법론은 다양한 홍수위험지도 작성시 가이드라인으로 제시될 수 있으며, 국토계획 수립이나 비상대처계획 수립시 홍수에 대한 위험지역 선정을 위한 사전검토 단계에서 활용될 수 있을 것으로 판단된다.

• 대한원격탐사학회지
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• 제28권3호
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• pp.297-305
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• 2012

This study was performed to estimate forest canopy density (FCD) using airborne hyperspectral data acquired in the Independence Hall of Korea in central Korea. The airborne hyperspectral data were obtained with 36 narrow spectrum ranges of visible (Red, Green, and Blue) and near infrared spectrum (NIR) scope. The FCD mapping model developed by the International Tropical Timber Organization (ITTO) uses vegetation index (VI), bare soil index (BI), shadow index (SI), and temperature index (TI) for estimating FCD. Vegetation density (VD) was calculated through the integration of VI and BI, and scaled shadow index (SSI) was extracted from SI after the detection of black soil by TI. Finally, the FCD was estimated with VD and SSI. For the estimation of FCD in this study, VI and SI were extracted from hyperspectral data. But BI and TI were not available from hyperspectral data. Hyperspectral data makes the numerous combination of each band for calculating VI and SI. Therefore, the principal component analysis (PCA) was performed to find which band combinations are explanatory. This study showed that forest canopy density can be efficiently estimated with the help of airborne hyperspectral data. Our result showed that most forest area had 60 ~ 80% canopy density. On the other hand, there was little area of 10 ~ 20% canopy density forest.

• 자원환경지질
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• 제37권5호
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• pp.521-532
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• 2004

본 연구의 목적은 강릉지역에 대해 산사태 취약성을 GIS와 원격탄사를 이용하여 평가하는 것이다. 이를 위해 산사태 위치는 위성영상 해석 및 현지 조사를 통해 확인되었고, GIS와 원격탐사를 이용하여 지형도, 토양도, 지질도, 선구조도, 토지피복도 등이 수집되고, 처리된 후 공간 데이터베이스로 구축되었다. 확률 기법인 빈도비 모델을 이용하여 산사태와 경사, 경사방향, 곡률, 수계, 지형종류, 토질, 토양모재, 토양배수, 유효토심, 임상종류, 임상경급, 임상영급, 임상밀도, 암상, 토지피복도, 선구조도 등 산사태 발생 요인들과의 관계를 계산하여 빈도비를 구하였다. 그리고 이러한 빈도비를 모두 더하여 산사태 취약성 지수를 계산하였으며, 이러한 취약서 지수를 모두 더하여 취약성도를 작성하였다. 그 결과는 실제 산사태 위치자료를 이용하여 검증 및 교차 검증되었고, 그 검증 결과는 산사태 취약성도와 산사태 위치와 밀접한 관계가 있었다.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 총회 및 춘계학술발표회
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• pp.97-99
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• 2003

Lineament density maps can be used for the quantitative evaluation of relationship between lineaments and groundwater occurrence. There are several kinds of lineament density maps including lineament length density, lineament cross-points density, and lineament counts density maps. This paper reports the usefulness of the representative elementary area (REA) concept for lineament analysis. This concept refers to the area size of the unit circle to calculate the lineament density factors distributed within the circle: length, counts and cross-points counts. The circle is a unit circle that calculates the sum of the lineament length, lineament counts and the number of cross-points within it. The REA is needed to obtain the best representative lineament density map prior to the analysis of relation between lineaments and groundwater well yield or other groundwater characteristics. A basic lineament map for the Yongsangang-Seomjingang watershed of Korea, drawn from aerial black-and-white photographs of 1/20, 000 scale was used for demonstrating the concept. From this study, the conclusions were as follows: (1) the REA concept can be efficiently applied to the lineament density analysis and mapping, (2) for whole Yongsangang-Seomjingang watershed which has 6, 502 lineaments with an average lineament length of 3.3 km, the lower limits of each REA used for drawing the three density maps were about 1.77 $\textrm{km}^2$ (r=750 m) for lineament length density, 7.07 $\textrm{km}^2$ (r=1, 500 m) for lineament counts density, and 4.91 $\textrm{km}^2$ (r=1, 250 m) for lineament cross-points density, respectively, (3) the lineament densities are inversely proportional to the size of REA, and the REA can be calculated with this inversely linear regression model, (4) if the average lineament density values for the whole study area are known, the most accurate density maps can be drawn using the REAs obtained from each linear regression model, and (5) but critical attention should be paid to draw lineament counts density and lineament cross-points density maps because.

• 한국지하수토양환경학회지:지하수토양환경
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• 제16권6호
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• pp.66-78
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• 2011

It is getting difficult to manage water resources in South Korea because more than half of annual precipitation is concentrated in the summer season and its intensity is increasing due to global warming and climate change. Artificial recharge schemes such as well recharge of surface water and roof-top rainwater harvesting can be a useful method to manage water resources in Korea. In this study, potential artificial recharge site is evaluated using geographic information system with hydrogeological and social factors. The hydrogeological factors include annual precipitation, geological classification based on geological map, specific capacity and depth to water level of national groundwater monitoring wells. These factors were selected to evaluate potential artificial recharge site because annual precipitation is closely related to source water availability for artificial recharge, geological features and specific capacity are related to injection capacity and depth to water is related to storage capacity of the subsurface medium. In addition to those hydrogeological factors, social aspect was taken into consideration by selecting the areas that is not serviced by national water works and have been suffered from drought. These factors are graded into five rates and integrated together in the GIS system resulting in spatial distribution of artificial recharge potential. Cheongsong, Yeongdeok in Gyeongsangbuk-do and Hadong in Gyeongsangnam-do, and Suncheon in Jeollanam-do were proven as favorable areas for applying artificial recharge schemes. Although the potential map for artificial recharge in South Korea developed in this study need to be improved by using other scientific factors such as evaporation and topographical features, and other social factors such as water-curtain cultivation area, hot spring resorts and industrial area where groundwater level is severely lowered, it can be used in a rough site-selection, preliminary and/or feasibility study for artificial recharge.

• Structural Engineering and Mechanics
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• 제66권1호
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• pp.15-25
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• 2018

Post-construction subgrade settlement especially differential settlement, has become a key issue in construction and operation of non-ballasted track on high-speed railway soil subgrade, which may also affect the dynamic performance of passing trains. To estimate the effect of differential subgrade settlement on the mechanical behaviors of the vehicle-slab track system, a detailed model considering nonlinear subgrade support and initial track state due to track self-weight is developed. Accordingly, analysis aiming at a typical high-speed vehicle coupled with a deteriorated slab track owing to differential subgrade settlement is carried out, in terms of two aspects: (i) determination of an initial mapping relationship between subgrade settlement and track deflections as well as contact state between track and subgrade based on a semi-analytical method; (ii) simulation of dynamic performance of the coupled system by employing a time integration approach. The investigation indicates that subgrade settlement results in additional track irregularity, and locally, the contact between the concrete track and the soil subgrade is prone to failure. Moreover, wheel-rail interaction is significantly exacerbated by the track degradation and abnormal responses occur as a result of the unsupported areas. Distributions of interlaminar contact forces in track system vary dramatically due to the combined effect of track deterioration and dynamic load. These may not only intensify the dynamic responses of the coupled system, but also have impacts on the long-term behavior of the track components.

• 한국토양비료학회지
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• 제49권5호
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• pp.495-502
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• 2016

Italian Ryegrass (IRG), which is known as high yielding and the highest quality winter annual forage crop, is grown in mid-south area in Korea. The objective of this study was to evaluate the use of unmanned aerial vehicle (UAV) for the monitoring IRG growth. Unmanned aerial vehicle imagery obtained from middle March to late May in Nonsan, Chungcheongnam-do. Unmanned aerial vehicle imagery corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). We analyzed the relationships between $NDVI_{UAV}$ of IRG and biophysical measurements such as plant height, fresh weight, and dry weight over an entire IRG growth period. The similar trend between $NDVI_{UAV}$ and growth parameters was shown. Correlation analysis between $NDVI_{UAV}$ and IRG growth parameters revealed that $NDVI_{UAV}$ was highly correlated with fresh weight (r=0.988), plant height (r=0.925), and dry weight (r=0.853). According to the relationship among growth parameters and $NDVI_{UAV}$, the temporal variation of $NDVI_{UAV}$ was significant to interpret IRG growth. Four different regression models, such as (1) Linear regression function, (2) Linear regression through the origin, (3) Power function, and (4) Logistic function were developed to evaluate the relationship between temporal $NDVI_{UAV}$ and measured IRG growth parameters. The power function provided higher accurate results to predict growth parameters than linear or logistic functions using coefficient of determination. The spatial distribution map of IRG growth was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to power function. From these results, $NDVI_{UAV}$ can be used as a new tool for monitoring IRG growth.

• 한국지형학회지
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• 제27권3호
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• 한국지형학회지
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• 제26권3호
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.259-259
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• 2022

Soil salinity is a major factor that reduces crop yields. The amount of soil affected by salinity is about 83 million hectares (FAO 2000), which is increasing due to the effects of climate change. In soybean [Glycine max (L.) Merr.], nutritional properties such as protein, starch, and sucrose content together with biomass and yield tends to reduce due to excessive salt. As a result of QTL mapping using the 169 F_2:3 population from the KA-1285 (salt-tolerant) × Daepung (salt-sensitive) in a previous study, two major QTLs (Gm03_39796778 and Gm03_40600088) related to salt tolerance were found on chromosome 3. In this study, the CDS region of the Gmsalt3 gene was analyzed using the ABI 3730x1 DNA Analyzer (Macrogen, Korea). The sequence of Gmsalt3 gene in KA-1285 was compared with Williams 82.a4.vl and PI483463 (Glycine soja). Two transversions were found at exon6 in KA-1285 and PI483463. Currently, whole genome sequencing and variation analysis using the Illumine Novaseq 6000 machine (Illumina, USA) are in progress. The results of this study can provide useful molecular markers for the selection of salt-tolerant soybeans and can be used as basic data for future salt-tolerant gene research.