• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.599-608
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• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

• Journal of Environmental Health Sciences
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• v.45 no.5
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• pp.487-496
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• 2019

Objective: The purpose of this study was to create soil contamination maps using QGIS (Quantum Geographic Information System) and suggest selection methods for soil pollution sources for preferential investigation in a soil contamination survey. Method: Data from soil contamination surveys over five years in Gyeonggi-do Province, South Korea (2013-2017) were used for making soil contamination maps and analyzing the density of survey points. By analyzing points exceeding the concern level of soil contamination, soil pollutant sources for priority management were identified and selection methods for preferred survey points were suggested through a study of the model area. Results: A soil contamination survey was conducted at 1,478 points over five years, with the largest number of surveys conducted in industrial complex and factory areas. Soil contamination maps for copper, zinc, nickel, lead, arsenic, fluoride, and total petroleum hydrocarbons were made, and most of the survey points were found to be below concern level 1 for soil contamination. The density of the survey points is similar to that of densely populated areas and factory areas. The analysis results of points exceeding the criteria showed that soil pollutant sources for priority management were areas where ore and scrap metals were used and stored, traffic-related facilities areas, industrial complex and factory areas, and areas associated with waste and recycling. According to the study of the model area, the preferred survey points were traffic-related facilities with 15 years or more since their construction and factories with a score of 10 or more for soil contamination risk. Conclusion: Soil contamination surveys should use GIS for even regional distribution of survey points and for the effective selection of preferred survey points. This study may be used as guidelines to select points for a soil contamination survey.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.354-354
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• 2019

기후변화에 따른 이상기후의 영향으로 과거 관측되지 않은 태풍, 가뭄, 폭우, 홍수 및 해일과 같은 재해의 빈도가 증가하고 있다. 특히, 가뭄은 장기간에 걸쳐 피해를 야기하여 대책을 장기적으로 고려하지 않으면 전 지구적으로 심각한 피해가 초래될 것으로 전망되고 있다. 많은 연구에서 가뭄에 따른 재해를 평가하기 위한 분석이 수행되고 있으며, 최근 연구에서는 토양수분을 통한 가뭄재해 분석이 대두되고 있다. 토양수분은 토양에 포함된 수분의 평균값을 의미하며 물 순환 관점에서 매우 중요한 수문변량 중 하나이다. 그러나 기존 연구에서 사용되고 있는 실측 토양수분은 자료의 기간이 짧고 검증이 수행되지 않아 분석 시 결과의 신뢰성이 결여되는 문제점이 있다. 일부 토양수분 연구에서는 위성 관측 자료를 통한 분석을 수행하였지만 실측 자료와의 상관성 문제로 인하여 모의된 결과의 활용은 어려운 실정이다. 이에 본 연구에서는 Quantile mapping 기반의 편의 보정 방법을 제시하여 용담 유역 내 6개 지점와 전국에 흩어져 있는 6개 지점(철원장흥, 수원, 대곡, 전주, 오창가곡, 춘천신북)의 실측자료와 위성 자료 기반의 재해석 토양수분 (re-analysis soil moisture data)에 따른 토양수분 모의 기법을 제시하였다. 본 연구에서 개발한 모형에 따른 결과는 가뭄재해 평가 시 기초자료로써 신뢰성 있는 정보로 활용할 수 있을 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1141-1180
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• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.2
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• pp.141-146
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• 1984

Variation of soil characteristics and purity were examined within mapping unit and estimates were given for the number of samples required to reach predetermined levels of accuracy for black soil, VDBr. soil, DBr. soil, and brown soil in Jeju. Variation of chemical properties except pH and CEC was higher than that of physical properties. Brown soil showed the lowest variation and hence required the smallest sample size. The soils examined were correctly classified with regard to brown soil at purity 74.1, to DBr. soil 60.8, to black soil 55.6, and to VDBr. soil 46.9%. Sample calculation was presented which showed approximate sample sizes required to detect the difference of 10 and 20% of the mean with 0.95 confidence level.

• Geomechanics and Engineering
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• v.13 no.6
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• pp.893-906
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• 2017

Automatic large scale soil model generation is very critical stage for earthquake hazard simulation of urban areas. Manual model development may cause some data losses and may not be effective when there are too many data from different soil observations in a wide area. Geographic information systems (GIS) for storing and analyzing spatial data help scientists to generate better models automatically. Although the original soil observations were limited to soil profile data, the recent developments in mapping technology, interpolation methods, and remote sensing have provided advanced soil model developments. Together with advanced computational technology, it is possible to handle much larger volumes of data. The scientists may solve difficult problems of describing the spatial variation of soil. In this study, an algorithm is proposed for automatic three dimensional soil and velocity model development of southern part of the European side of Istanbul next to Sea of Marmara based on GIS data. In the proposed algorithm, firstly bedrock surface is generated from integration of geological and geophysical measurements. Then, layer surface contacts are integrated with data gathered in vertical borings, and interpolations are interpreted on sections between the borings automatically. Three dimensional underground geology model is prepared using boring data, geologic cross sections and formation base contours drawn in the light of these data. During the preparation of the model, classification studies are made based on formation models. Then, 3D velocity models are developed by using geophysical measurements such as refraction-microtremor, array microtremor and PS logging. The soil and velocity models are integrated and final soil model is obtained. All stages of this algorithm are carried out automatically in the selected urban area. The system directly reads the GIS soil data in the selected part of urban area and 3D soil model is automatically developed for large scale earthquake hazard simulation studies.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.483-503
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• 2017

Uncertainty is a fact belonging to engineering practice. An important uncertainty that sets geotechnical engineering is the variability associated with the properties of soils or, more precisely, the characterization of soil profiles. The reason is due largely to the complex and varied natural processes associated with the formation of soil. Spatial variability analysis for the study of the stability of natural slopes, complementing conventional analyses, is able to incorporate these uncertainties. In this paper the characterization is performed in back-analysis for a case of landslide occurred to verify afterwards the presence of the conditions of shear strength at failure. This approach may support designers to make more accurate estimates regarding slope failure responding, more consciously, to the legislation dispositions about slope stability evaluation and future design. By applying different kriging techniques used for spatial analysis it has been possible to perform a 3D-slope reconstruction. The predictive analysis and the areal mapping of the soil mechanical characteristics would support the definition of priority interventions in the zones characterized by more critical values as well as slope potential instability. This tool of analysis aims to support decision-making by directing project planning through the efficient allocation of available resources.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Journal of Biosystems Engineering
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• v.31 no.6 s.119
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• pp.463-473
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• 2006

Automated sensing of soil macronutrients would allow more efficient mapping of soil nutrient spatial variability for variable-rate nutrient management. The capabilities of ion-selective electrodes for sensing macronutrients in soil extracts can be affected by the presence of other ions in the soil itself as well as by high concentrations of ions in soil extractants. Adoption of automated, on-the-go sensing of soil nutrients would be enhanced if a single extracting solution could be used for the concurrent extraction of multiple soil macronutrients. This paper reports on the ability of the Kelowna extractant to extract macronutrients (N, P, and K) from US Corn Belt soils and whether previously developed PVC-based nitrate and potassium ion-selective electrodes could determine the nitrate and potassium concentrations in soil extracts obtained using the Kelowna extractant. The extraction efficiencies of nitrate-N and phosphorus obtained with the Kelowna solution for seven US Corn Belt soils were comparable to those obtained with IM KCI and Mehlich III solutions when measured with automated ion and ICP analyzers, respectively. However, the potassium levels extracted with the Kelowna extractant were, on average, 42% less than those obtained with the Mehlich III solution. Nevertheless, it was expected that Kelowna could extract proportional amounts of potassium ion due to a strong linear relationship ($r^2$ = 0.96). Use of the PVC-based nitrate and potassium ion-selective electrodes proved to be feasible in measuring nitrate-N and potassium ions in Kelowna - soil extracts with almost 1 : 1 relationships and high coefficients of determination ($r^2$ > 0.9) between the levels of nitrate-N and potassium obtained with the ion-selective electrodes and standard analytical instruments.

• Asian Journal of Turfgrass Science
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• v.22 no.1
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• pp.85-100
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• 2008

Gray leaf spot (GLS) is a serious fungal disease caused by Pyricularia oryzae Cavara, recently reported on the important turf and forage species, perennial ryegrass (Lolium perenneL.). This fungus also causes rice blast, which is usually controlled by host resistance, but durability of resistance is a problem. Few instances of GLS resistance have been reported in perennial ryegrass. However, two major QTL for GLS resistance have been detected on linkage groups 3 and 6 in an Italian x perennial ryegrass mapping population. To confirm that those QTL are still detectable in the next generation and can function in a different genetic background, a resistant segregant from this population has been crossed with an unrelated susceptible perennial clone, to form a new mapping population segregating for GLS resistance. QTL analysis has been performed in the new population, using two different ryegrass field isolates and RAPD, RFLP, and SSR marker-based linkage maps for each parent. Results indicate the previously identified QTL on linkage group 3 is still significant in the new population, with LOD and percent of phenotypic variance explained ranging from 2.0 to 3.5 and 5% to 10%, respectively. Also two QTL were detected in the susceptible parent, with similar LOD and phenotypic variance explained. Although the linkage group 6 QTL was not detected, the major QTL on linkage group 3 appears to beconfirmed. These results will add to our understanding of the genetic architecture of GLS resistance in ryegrass, which will facilitate its use in perennial ryegrass breeding programs.