• The Journal of Engineering Geology
• /
• v.26 no.4
• /
• pp.551-559
• /
• 2016

The chemical composition and noble gas isotopes of 10 deep groundwater samples were analyzed to know the circulation of groundwaters in the Yangsan fault and the Gampo fault. The chemical types of groundwaters show the $Ca-HCO_3$ type and $Ca-SO_4(Cl)$ type, and show indistinct relationship with geology. Noble gas isotopic data of most groundwaters were plotted along the air-crust mixing line on $^3He/^4He$ vs. $4^He/^{20}Ne$ diagram, and show dominant $^3He$ of air origin except one sample that shows helium mixing of crust origin. This indicates that groundwater actively circulates along fault, and fault could not play an role of upward pathway of a deep-seated helium gas. A comparatively high $^4He$ indicates that groundwater flows in an aquifer assuring relatively enough water-rock interaction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.6
• /
• pp.672-680
• /
• 2019

This paper proposes "A Smart Farm Environment Optimization and Yield Prediction Platform based on IoT and Deep Learning" which gathers bio-sensor data from farms, diagnoses the diseases of growing crops, and predicts the year's harvest. The platform collects all the information currently available such as weather and soil microbes, optimizes the farm environment so that the crops can grow well, diagnoses the crop's diseases by using the leaves of the crops being grown on the farm, and predicts this year's harvest by using all the information on the farm. The result shows that the average accuracy of the AEOM is about 15% higher than that of the RF and about 8% higher than the GBD. Although data increases, the accuracy is reduced less than that of the RF or GBD. The linear regression shows that the slope of accuracy is -3.641E-4 for the ReLU, -4.0710E-4 for the Sigmoid, and -7.4534E-4 for the step function. Therefore, as the amount of test data increases, the ReLU is more accurate than the other two activation functions. This paper is a platform for managing the entire farm and, if introduced to actual farms, will greatly contribute to the development of smart farms in Korea.

• Economic and Environmental Geology
• /
• v.43 no.4
• /
• pp.381-391
• /
• 2010

Probabilistic prediction methods of landslides which have been developed in recent can be reliable with premise of detailed survey and analysis based on deep and special knowledge. However, landslide susceptibility should also be analyzed with some reliable and simple methods by various people such as government officials and engineering geologists who do not have deep statistical knowledge at the moment of hazards. Therefore, this study suggests an evaluation chart of landslide susceptibility with high reliability drawn by accurate statistical approaches, which the chart can be understood easily and utilized for both specialists and non-specialists. The evaluation chart was developed by a quantification method based on canonical correlation analysis using the data of geology, topography, and soil property of landslides in Korea. This study analyzed field data and laboratory test results and determined influential factors and rating values of each factor. The quantification analysis result shows that slope angle has the highest significance among the factors and elevation, permeability coefficient, porosity, lithology, and dry density are important in descending order. Based on the score assigned to each evaluation factor, an evaluation chart of landslide susceptibility was developed with rating values in each class of a factor. It is possible for an analyst to identify susceptibility degree of a landslide by checking each property of an evaluation factor and calculating sum of the rating values. This result can also be used to draw landslide susceptibility maps based on GIS techniques.

• The Journal of Engineering Geology
• /
• v.22 no.2
• /
• pp.233-241
• /
• 2012

The objectives of this study were to test geothermal conductivity (k), water velocity, water quantity, and pipe pressure from a ground heat exchanger in the field, and then to analyze these data in relation to the effectiveness and economical efficiency for application of geothermal energy. After installation of the apparatus required for field tests, geothermal conductivity values were obtained from three different cases (second, third, and fourth). The k values of the second case (506 m depth) and third case (151 m depth) are approximately 2.9 and 2.8, respectively. The k value of the fourth case (506 m depth, double pipe) is 2.5, which is similar to the second and third cases. This result indicates that hole depth is a critical factor for geothermal applications. Analysis of the field data (k, water velocity, water quantity, and pipe pressure) reveals that a single geothermal system at 506 m depth is more economically efficient than three geothermal systems at depths intervals of 151 m. Although it is more expensive to install a geothermal system at 506 m depth than at 151 m depth, test results showed that the geothermal system of the fourth case (506 m, double pipe) is more economically efficient than the system at 151 m depth. Considering the optional cost of maintenance, which is a non-operational expense, the geothermal system of the fourth case is economically efficient. Large cities and areas with high land prices should make greater use of geothermal energy.

• The Journal of Engineering Geology
• /
• v.18 no.4
• /
• pp.537-543
• /
• 2008

To effectively delineate the foundation of stone relics by GPR and seismic refraction methods, a geological engineering model was constructed with alternating layer of soil and gravel to a depth of 3 m. This study was aimed at mapping the boundaries of model ground structure and interfaces of alternating layer using the various frequency antenna in GPR survey and seismic velocities. Compared to the resolution from the high frequency antenna, the image resolution from the survey using 100 Hz antenna is the lower, but with the deeper image coverage. On the contrast, the deeper structure was not mapped in the higher frequency data due to higher absorption effect, but the shallow layered zone was distinctively resolved. Therefore subsurface images were effectively provided by integrating the data with 100 MHz and 450 MHz antennas for the deep and shallow structures, respectively. Regarding the seismic refraction data, the boundaries of the model and interface of the alternating layers were not successfully mapped due to the limit of the survey length. However, the equivalent contours of low velocity extended deep as considerable velocity contrasts with surrounding ground.

• Geophysics and Geophysical Exploration
• /
• v.8 no.1
• /
• pp.26-33
• /
• 2005

Inversion of multi-mode surface-wave phase velocity for shallow engineering site investigation has received much attention in recent years. A sensitivity analysis and inversion of both synthetic and field data demonstrates the greater effectiveness of this method over employing the fundamental mode alone. Perturbation of thickness and shear-wave velocity parameters in multi-modal Rayleigh wave phase velocities revealed that the sensitivities of higher modes: (a) concentrate in different frequency bands, and (b) are greater than the fundamental mode for deeper parameters. These observations suggest that multi-mode phase velocity inversion can provide better parameter discrimination and imaging of deep structure, especially with a velocity reversal, than can inversion of fundamental mode data alone. An inversion of the theoretical phase velocities in a model with a low velocity layer at 20 m depth can only image the soft layer when the first higher mode is incorporated. This is especially important when the lowest measurable frequency is only 6 Hz. Field tests were conducted at sites surveyed by borehole and PS logging. At the first site, an array microtremor survey, often used for deep geological surveying in Japan, was used to survey the soil down to 35 m depth. At the second site, linear multichannel spreads with a sledgehammer source were recorded, for an investigation down to 12 m depth. The f-k power spectrum method was applied for dispersion analysis, and velocities up to the second higher mode were observed in each test. The multi-mode inversion results agree well with PS logs, but models estimated from the fundamental mode alone show f large underestimation of the depth to shallow soft layers below artificial fill.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.24 no.4
• /
• pp.341-353
• /
• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Journal of the Korean Geotechnical Society
• /
• v.25 no.9
• /
• pp.67-76
• /
• 2009

The problems of bearing capacity, settlement and shear deformation occur when constructing a structure such as harbor, airport and bridge on soft ground of marine clay, silty clay or sandy soil. Various ground improvement methods are applied to obtain preceding settlement of soft ground and strength increase. In this study, to analyze the applicability of PBD method in deep soft ground, the compound drainage capacity test was operated in comparison with SD. As a result of the test, a minimum drainage capacity of drain material was estimated to be more than $10\;cm^3/sec$ at a more than $400\;kN/m^2$ and less than $5\;cm^3/sec$ at a more than $500\;kN/m^2$ confining pressure in case of single core PBD. In case of double core PBD, it was estimated to be more than $10\;cm^3/sec$ at a more than $500\;kN/m^2$ confining pressure.

• Korean Journal of Environmental Biology
• /
• v.40 no.3
• /
• pp.325-334
• /
• 2022

Paspalum distichum and P. distichum var. indutum are perennial weeds of the family Poaceae that prefer moist environments such as waterfronts and waterways. The origin of both species is North America. P. distichum is distributed all over the world. However, P. distichum var. indutum occurs only in the United States, Japan, and Korea. For this reason, in many countries, P. distichum and P. distichum var. indutum are classified as the same species. In other words, P. distichum var. indutum is a different ecological type of P. distichum. Both species can reproduce and spread mainly by rhizome fragments rather than seeds. This rhizome has a characteristic that it does not germinate if it is buried in the ground with depth of more than 3 cm. As a management method for P. distichum and P. distichum var. indutum in agricultural lands (paddy fields), it is effective to combine cultural control and chemical control methods. In other words, combining deep plowing and harrowing can suppress the budding of water sparrow that has invaded paddy fields or fallow paddy fields. After that, these two species that germinate can be controlled by spraying soil treatment herbicides such as butachlor and thiobencarb or foliar treatment herbicides such as cyhalofop-butyl and fenoxaprop-p-ethyl.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1371-1388
• /
• 2023

Floods are becoming more severe and frequent due to global warming-induced climate change. Water disasters are rising in Korea due to severe rainfall and wet seasons. This makes preventive climate change measures and efficient water catastrophe responses crucial, and synthetic aperture radar satellite imagery can help. This research created 1,423 water body learning datasets for individual water body regions along the Han and Nakdong waterways to reflect domestic water body properties discovered by Sentinel-1 satellite radar imagery. We created a document with exact data annotation criteria for many situations. After the dataset was processed, U-Net, a deep learning model, analyzed water body detection results. The results from applying the learned model to water body locations not involved in the learning process were studied to validate soil water body monitoring on a national scale. The analysis showed that the created water body area detected water bodies accurately (F1-Score: 0.987, Intersection over Union [IoU]: 0.955). Other domestic water body regions not used for training and evaluation showed similar accuracy (F1-Score: 0.941, IoU: 0.89). Both outcomes showed that the computer accurately spotted water bodies in most areas, however tiny streams and gloomy areas had problems. This work should improve water resource change and disaster damage surveillance. Future studies will likely include more water body attribute datasets. Such databases could help manage and monitor water bodies nationwide and shed light on misclassified regions.