• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.429-438
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• 2011

LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.55-59
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• 2008

For effective mobility control of UGV(unmanned ground vehicle), the terrain cover classification is an important component as well as terrain geometry recognition and obstacle detection. The vision based terrain cover classification algorithm consists of pre-processing, feature extraction, classification and post-processing. In this paper, we present a method to classify terrain covers based on the color and texture information. The color space conversion is performed for the pre-processing, the wavelet transform is applied for feature extraction, and the SVM(support vector machine) is applied for the classifier. Experimental results show that the proposed algorithm has a promising classification performance.

• Explosives and Blasting
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• v.15 no.1
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• pp.44-60
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• 1997

The design of underground cavern is basically governed by the mechanical properties of ground mass distributed around excavation. It is seldom possible to consider all the factors of ground mass properties in the evaluation of ground mass behavior as well as to classify those factors to a simple category. Until computer sciences have developed to calculate complex and laborious mechanical simulation of underground openings, ground behavior was quantitatively and qualitatively evaluated using empirical classification system. In this paper, analysis methods of ground behavior for underground cavern using the prediction of loosening zone, empirical method derived from rock mass classification and element stress analysis are described with chronological sequence.

• The Journal of Engineering Geology
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• v.1 no.1
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• pp.38-53
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• 1991

The design of underground cavern is basically governed by the mechanical properties of ground mass distributed around excavation. It is seldom possible to consider all the factors of ground mass properties in the evaluation of ground mass behavior as well as to classify those factors to a simple category. Until computer sciences have developed to calculate complex and laborious mechanical simulation of underground openings, ground behavior was quantitatively and qualitatively evaluated using empirical classification system. In this paper, analysis methods of ground behavior for underground cavern using the prediction of loosening zone, empirical method derived from rock mass classification and element stress analysis are described with chronological sequence.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.41-47
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• 2011

Processing of the raw LiDAR data requires the high-end processor, because data form is a vector. In contrast, if LiDAR data is converted into a regular grid pattern by filltering, that has advantage of being in a low-cost equipment, because of the simple structure and faster processing speed. Especially, by using grid data classification, such as Quadtree, some of trees and cars are removed, so it has advantage of modeling. Therefore, this study presents the algorithm for automatic extraction of ground points using Quadtree and refion growing method from LiDAR data. In addition, Error analysis was performed based on the 1:5000 digital map of sample area to analyze the classification of ground points. In a result, the ground classification accuracy is over 98%. So it has the advantage of extracting the ground points. In addition, non-ground points, such as cars and tree, are effectively removed as using Quadtree and region growing method.

• Korean Journal of Materials Research
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• v.19 no.4
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• pp.212-219
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• 2009

A study on the dry beneficiation of sericite occurring in the Daehyun Mine of the Republic of Korea region as performed by applying selective grinding and air classification techniques. Quartz and sericite occurred in the raw ore as major components. The results of liberation using a ball mill and an impact mill showed that the contents of $R_2O$ were increased while $SiO_2$ was decreased in proportion to decreasing particle size. According to the XRD, XRF analysis and the EDS of SEM analysis, the ball mill gave a better grade product in $R_2O$ content than the impact mill when the particle size was the same. When the raw ore was ground by the impact mill with arotor speed 57.6 m/sec and then followed by 15,000rpm classification using an air classifier, the chemical composition of the over flowed product was 49.65wt% $SiO_2$, 32.15wt% $Al_2O_3$, 0.13wt% $Fe_2O_3$, 10.37wt% $K_2O$, and 0.14wt% $Na_2O$. This result indicates that the $R_2O$ contents were increased by 49.5% compared to that of the raw ore. From these results described above, it is suggested that hard mineral such as Quartz little ground by selective grinding using impact mill whereas soft mineral such as sericite easily ground to small size. As a result of that hard minerals can be easily removed from the finely ground sericite by air classification and the $R_2O$ grade of thus obtained concentrate was improved to higher than 10wt% which can be used for ceramics raw materials.

• Journal of the Korean Geotechnical Society
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• v.39 no.2
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• pp.5-17
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• 2023

In this study, a classification and uniaxial compression test of soil was conducted on 15 collapsed sites to use ground improvement with excellent protection effect owing to the increase of localized heavy rain in Korea. The Casagrande method and fall cone test were performed on the field soil to derive an expression for comparing liquid limit and plastic limit values, soil classification, and correlation between each other. By deriving the optimal mixing ratio of the ground improvement agent using uniaxial compressive strength for each soil classification, the classification of the fine-grained soil was not clear owing to the proficiency difference and test error. However, after classifying using the fall cone test, it was possible to suggest a clear optimal mixing ratio.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.255-261
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• 2018

In the field of excavation, it is important to recognize and analyze the factors that cause the ground collapse in order to predict and cope with the ground subsidence. However, it is difficult for field engineers to predict ground collapse due to insufficient knowledge of ground subsidence influence factors. Although there are many cases and studies related to the ground subsidence, there is no manual to help practitioners. In this study, we present the criteria for describing and quantifying the influential factors to help the practitioners understand the existing ground collapse cases and classification of the ground subsidence factors revealed through the research. This study aims to improve the understanding of the factors affecting the ground collapse and to provide a GSRp for the ground subsidence risk assessment which can be applied quickly in the field.

• Journal of The Geomorphological Association of Korea
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• v.19 no.3
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• pp.37-49
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• 2012

The objective of this paper is to propose a methodology for surface sediments classification in tidal flats that can combine ground survey data with high-resolution remote sensing data by multivariate kriging. Unlike conventional methodologies that have classified remote sensing data by using pre-classified sediment components, a new classification methodology presented in this paper first generates sediment component fraction maps and then classifies the sediments on a final stage. For generating sediment component fractions, regression kriging, as one of multivariate kriging algorithms, is applied to integrate ground survey data and remote sensing data. First, trend components of sand, silt, and clay are derived through regression analysis of ground survey data and spectral information from remote sensing data. Then, residuals at sample locations are computed and interpolated to generate residual components in the study area. Finally, the sediment component fractions are computed by adding the residuals to the trend components and are classified on a final stage. A case study at the Baramarae tidal flats with KOMPSAT-2 imagery is carried out to evaluate the classification capability of the proposed classification methodology. Through the case study, the proposed methodology showed the best classification accuracy, compared with the conventional classification methodologies. Especially, much improvement of classification accuracy for fine-grained sediments were also obtained. Therefore, it is expected that the presented classification methodology would be an effective one for surface sediments classification in tidal flats.

• Land and Housing Review
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• v.6 no.1
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• pp.31-39
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• 2015

Most landscape areas in apartment complex have been changing. Increasing the area of underground parking lots have an effect on apartment's circumstance. Natural ground was decreased so that the most space in apartment complex were converted into an artificial ground. To suggest the soil quality management, this study examined the actual situation about the soil quality of planting ground such as the quality standard as artificial soil, the difference of natural ground, and the difference of soil quality according to the work classification. As a result, the soil quality of the apartment complex with a large underground parking lot had low quality of soil. Soil physical properties were relatively fine but soil chemical properties needed the quality control. The soil quality of natural ground and artificial ground was not statistically significant and the soil quality by the work classification also had no statistical significance. Therefore, we established improvements about standards of the chemical properties for quality management, the soil quality in the natural ground and applying the equivalent standard according to the work classification.