• Tunnel and Underground Space
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• v.29 no.6
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• pp.508-522
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• 2019

Because of the slope failure, not only property damage but also human damage can occur, slope stability analysis should be conducted to predict and reinforce of the slope. This paper, defines the ground areas that can be characterized in terms of slope failure such as Rockmass jointset, Rockmass fault, Soil, Leakage water and Crush zone in sloped images. As a result, it was shown that the deep learning instance segmentation network can be used to recognize and automatically segment the precise shape of the ground region with different characteristics shown in the image. It showed the possibility of supporting the slope mapping work and automatically calculating the ground characteristics information of slopes necessary for decision making such as slope reinforcement.

• Spatial Information Research
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• v.19 no.1
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• pp.13-19
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• 2011

As an urbanization is in progress, the change of the planimetric features and topography including high-rise residential buildings commonly occur. The change of the planimetric features and topography causes occurrence of the strong wind and wind speed increase or decrease due to the effect of planimetric features and topography on the windward side even though the wind blows with the same speed. In the design standard, this change by wind speed is defined as the velocity pressure exposure coefficient, the value of coefficient is estimated and reflected by ground surface roughness, but in a reality, ground surface roughness is determined in accordance with the subjective judgement of designer and then the velocity pressure exposure coefficient is estimated, moreover the research and data for classification of ground surface roughness are insufficient. In this paper, we will estimate the velocity pressure exposure coefficient by the quantified method for classifying ground surface roughness by using GIS according to the height of a building targeting area where high-rise residential buildings are built lately. When the structure subjected to wind load is designed, reasonability of design and safety of structure will be more improved by using the estimation method of velocity pressure exposure coefficient presented in this study.

• Spatial Information Research
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• v.11 no.2
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• pp.101-117
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• 2003

High resolution satellite image analysis has been recognized as an effective technique for monitoring local land-cover and atmospheric changes. In this study, a new high resolution map for land-cover was generated using both high-resolution IKONOS image and conventional land-use mapping. Fuzzy classification method was applied to classify land-cover, with minimum operator used as a tool for joint membership functions. In separateness analysis, the values were not great for all bands due to discrepancies in spectral reflectance by seasonal variation. The land-cover map generated in this study revealed that conifer forests and farm land in the ground and tidal flat and beach in the ocean were highly changeable. The kappa coefficient was 0.94% and the overall accuracy of classification was 95.0%, thus suggesting a overall high classification accuracy. Accuracy of classification in each class was generally over 90%, whereas low classification accuracy was obtained for classes of mixed forest, river and reservoir. This may be a result of the changes in classification, e.g. reclassification of paddy field as water area after water storage or mixed use of several classification class due to similar spectral patterns. Seasonal factors should be considered to achieve higher accuracy in classification class. In conclusion, firstly, IKONOS image are used to generated a new improved high resolution land-cover map. Secondly, IKONOS image could serve as useful complementary data for decision making when combined with GIS spatial data to produce land-use map.

• The Research Journal of the Costume Culture
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• v.6 no.2
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• pp.153-162
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• 1998

The bodice of character is classification in three period. The Fitted bodice in bustle style is characteristics, and is named as Cuirass Bodice. The Cuirass Bodice form the ground work in modern costume. So the purpose of this study is to understand background on the Cuirass Bodice, and is to analize periodical character. The Method of This study refer to literature, used illustration, and make actually Cuirass Bodice.

• Korean Journal of Remote Sensing
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• v.2 no.1
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• pp.3-11
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• 1986

The current methods of estimating contest distribution function in contextual clarifier are to "classify and count", GTGM (ground-truth-guided-method) and unbiased estimator. In this paper we propose a new contextual classifier echoes context distribution is replaced by context probability that is estimated from transition probability. The classification accuracy increases considerably compared with the classical one.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5C
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• pp.293-301
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• 2008

Soil profiling is one of the most important work among geotehnical engineering practice. Generally, soil profile is estimated from the observation of soil samples during subsurface exploration but such estimation also includes some experiencing aspects such as flushed water from the borehole, slime colour, boring speed and so on. In addition, since the capacity of hydraulic drill rig is significantly increased, thin layers might be easily missed. So, continuous soil profile is almost impossible over all depth to be bored from conventional subsurface exploration. While CPT or CPTu can serve continuous soil profile information over all depth generally in 5cm interval. Many charts or methods for soil profile from CPT result have been proposed during last several decades over the world. However they have not been verified in local ground condition in Korea. In this research, CPT results and soil classification results based on USCS were compiled from 17 sites over the Korea. Soil classification results by using 7 CPT soil classification charts were compared with those of USCS for the compiled database. Most proper CPT soil classification chart for Korean soil characteristics was evaluated and effective parameters for the soil classification from CPT were discussed. Finally interrelationship between CPT soil classification chart and USCS soil classification was evaluated.

• Atmosphere
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• v.17 no.2
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• pp.159-169
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• 2007

A comparison of the three land cover data sets (United States Geological Survey: USGS, International Geosphere Biosphere Programme: IGBP, and University of Maryland: UMd), derived from 1992-1993 Advanced Very High Resolution Radiometer(AVHRR) data sets, was performed over the Asian continent. Preprocesses such as the unification of map projection and land cover definition, were applied for the comparison of the three different land cover data sets. Overall, the agreement among the three land cover data sets was relatively high for the land covers which have a distinct phenology, such as urban, open shrubland, mixed forest, and bare ground (>45%). The ratios of triple agreement (TA), couple agreement (CA) and total disagreement (TD) among the three land cover data sets are 30.99%, 57.89% and 8.91%, respectively. The agreement ratio between USGS and IGBP is much greater (about 80%) than that (about 32%) between USGS and UMd (or IGBP and UMd). The main reasons for the relatively low agreement among the three land cover data sets are differences in 1) the number of land cover categories, 2) the basic input data sets used for the classification, 3) classification (or clustering) methodologies, and 4) level of preprocessing. The number of categories for the USGS, IGBP and UMd are 24, 17 and 14, respectively. USGS and IGBP used only the 12 monthly normalized difference vegetation index (NDVI), whereas UMd used the 12 monthly NDVI and other 29 auxiliary data derived from AVHRR 5 channels. USGS and IGBP used unsupervised clustering method, whereas UMd used the supervised technique, decision tree using the ground truth data derived from the high resolution Landsat data. The insufficient preprocessing in USGS and IGBP compared to the UMd resulted in the spatial discontinuity and misclassification.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.2
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• pp.43-56
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• 1993

The laboratory tests are performed on how the liquefaction potential of the sea dike structures on the saturated sand or silty sand seabed could be affected due to earthquake before and after construction results are given as follows ; 1. Earthquake damages to sea dike structures consist of lateral deformation, settlement, minor abnormality of the structures and differential settlement of embankments, etc. It is known that severe disasters due to this type of damages are not much documented. Because of its high relative cost of the preventive measures against this type of damages, the designing engineer has much freedom for the play of judgement and ingenuity in the selection of the construction methods, that is, by comparing the cost of the preventive design cost at a design stage to reconstruction cost after minor failure. 2. The factors controlling the liquefaction potential of the hydraulic fill structure are magnitude of earthquake(max. surface velocity), N-value(relative density), gradation, consistency(plastic limit), classification of soil(G & vs), ground water level, compaction method, volumetric shear stress and strain, effective confining stress, and primary consolidation. 3. The probability of liquefaction can be evaluated by the simple method based on SPT and CPT test results or the precise method based on laboratory test results. For sandy or silty sand seabed of the concerned area of this study, it is said that evaluation of liquefaction potential can be done by the one-dimensional analysis using some geotechnical parameters of soil such as Ip, Υt' gradation, N-value, OCR and classification of soils. 4. Based on above mentioned analysis, safety factor of liquefaction potential on the sea bed at the given site is Fs =0.84 when M = 5.23 or amax= 0.12g. With sea dike structures H = 42.5m and 35.5m on the same site Fs= 3.M~2.08 and Fs = 1.74~1.31 are obtained, respectively. local liquefaction can be expected at the toe of the sea dike constructed with hydraulic fill because of lack of constrained effective stress of the area.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.233-244
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• 2021

This study investigated the application of terrestrial light detection and ranging (LiDAR) to inspect the defects of the vegetated levee. The accuracy of vegetation filtering techniques was compared by applying filtering techniques on photogrammetric point clouds of a vegetated levee generated by terrestrial LiDAR. Representative 10 vegetation filters such as CIVE, ExG, ExGR, ExR, MExG, NGRDI, VEG, VVI, ATIN, and ISL were applied to point cloud data of the Imjin River levee. The accuracy order of the 10 techniques based on the results was ISL, ATIN, ExR, NGRDI, ExGR, ExG, MExG, VVI, VEG, and CIVE. Color filters show certain limitations in the classification of vegetation and ground and classify grass flower image as ground. Morphological filters show a high accuracy of the classification, but they classify rocks as vegetation. Overall, morphological filters are superior to color filters; however, they take 10 times more computation time. For the improvement of the vegetation removal, combined filters of color and morphology should be studied.

• Economic and Environmental Geology
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• v.41 no.6
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• pp.747-761
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• 2008

In order to experiment the acoustic remote classification of seabed sediment, we achieved ground-truth data(i.e. video and grab samples, etc.) and developed post-processing for automatic classification procedure on the basis of 300 kHz MultiBeam Echo Sounder(MBES) backscattering data, which was acquired using KONGBERG Simrad EM3000 at Sock-Cho Port, East Sea of South Korea. Sonar signal and its classification performance were identified with geo-referenced video imagery with the aid of GIS (Geographic Information System). The depth range of research site was from 5 m to 22.7 m, and the backscattering amplitude showed from -36dB to -15dB. The mean grain sizes of sediment from equi-distanced sampling site(50 m interval) varied from 2.86$(\phi)$ to 0.88(\phi). To acquire the main feature for the seabed classification from backscattering amplitude of MBES, we evaluated the correlation factors between the backscattering amplitude and properties of sediment samples. The performance of seabed remote classification proposed was evaluated with comparing the correlation of human expert segmentation to automatic algorithm results. The cross-model perception error ratio on automatic classification algorithm shows 8.95% at rocky bottoms, and 2.06% at the area representing low mean grain size.