• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• The Journal of the Petrological Society of Korea
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• v.15 no.4 s.46
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• pp.180-193
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• 2006

The Gilan area in the central-northern part of Uiseong Block of Cretaceous Gyeongsang Basin is composed of Precambrian metamorphic rocks, Triassic Cheongsong granite, Early Cretaceous Hayans Group, and Late Cretaceous-Paleocene igneous rocks. In this area, the faults of various directions are developed: Oksan fault of $NS{\sim}NNW$ trend, Gilan fault of NW trend, Hwanghaksan fault of WNW trend, and Imbongsan fault of EW trend. Several fracture sets with various geometric indicators, which determine their relative timing (sequence and coexistence relationships) and shear sense, we well observed in the Cheongsong granite, the basement of Gyeongsang Basin. The aim of this study is to determine the development sequence of extension fractures and the movement sense of shear fractures in the Gitan area on the basis of detailed analysis of their geometric indicators (connection, termination, intersection patterns, and cross-cutting relations). This study suggests that the fracture system of the Gilan area was formed at least through seven different fracturing events, named as Pre-Dn to Dn +5 phases. The orientations of fracture sets show (W) NW, NNW, NNE, EW, NE in descending order of frequency. The orientation and frequency patterns are concordant with those of faults around and in the Gilan area on a geological map scale. The development sequence and movement sense of fracture sets are summarized as follows. (1) Pre-Dn phase: extension fracturing event of $NS{\sim}NNW$ and/or $WNW{\sim}ENE$ trend. The joint sets of $NS{\sim}NNW$ trend and of $WNW{\sim}ENE$ trend underwent the reactivation histories of sinistral ${\rightarrow}$dextral${\rightarrow}$sinistral shearing and of (dextral${\rightarrow}$) sinistral shearing with the change of stress field afterward, respectively. (2) Dn phase: that of NW trend. The joint set experienced the reactivations of sinistral${\rightarrow}$dextral shearing. (3) Dn + 1 phase: that of $NNE{\sim}NE$ trend. The joint set was reactivated as a sinistral shear fracture afterward. (4) Dn +2 phase: that of $ENE{\sim}EW$ trend. (5) Dn +3 phase: that of $WNW{\sim}NW$ trend. (6) Dn+4 phase: that of NNW trend. The joint set underwent a dextral shearing after this. (7) The last Dn +5 phase: that of NNE trend.

• Journal of the Korean GEO-environmental Society
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• v.11 no.8
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• pp.33-40
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• 2010

In this study, evaluation of basic unit of non-point pollutant, which is fundamental evaluation of non-point loading, was conducted using both road point and angle of intersection point in Maesong area, West coast highway by utilizing Event Mean Concentrations(EMC). Concentration of pollutants except heavy metals at these two points rapidly decreased in 30 minutes after start of runoff. According to the results of EMC, for both sampling points, it was determined that the concentrations of TSS(Total Suspended Solid), $BOD_5$(Biological Oxygen Demand), and DOC(Dissolved Organic Carbon) were higher than those of wastewater effluent standard in Korea, however, the concentrations of T-N(Total Nitrogen) and T-P(Total Phosphorus) were lower than those of the standard. In terms of heavy metals, Fe, Pb, and Zn showed higher concentrations than others. When compared with the units established by the Ministry of Environment in Korea, the basic units of $BOD_5$ and T-N in this study were lower. On the other hand, when compared with foreign units, Cu, Pb, and Zn showed approximately 10 times higher concentrations. It was estimated that a long term monitoring should be conducted for obtaining additional data and more reliable basic units for the non-point pollutnats based on the results from this study.

• 한국노년학
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• v.30 no.4
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• pp.1163-1177
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• 2010

This study was conducted to establish the appropriate facilities criteria of the Korean welfare devices center. We e-mail surveyed 194 welfare devices centers and analysed 13 blueprints of them. We established the following proper principles of facilities. First, consist type and area of room should depend on the type of welfare devices centers. Second, The flow of human and welfare devices should be simple. Third, the area calculated on the base of intent of center owner and the size of beds, wheelchairs, etc. Fourth, exhibit room facing with roadside may obtain advertising effect. Fifth, the storage and disinfecting room should use different entrance, and avoid the intersection of flow to prevent cross-contamination. Sixth, the access road to the exhibition and consulting room should be able to approach by the wheelchair. seventh, office room should be invisible to keep customer's privacy. Direct Cleaning-disinfecting type center on the premise that the maximum 165m², middle 150m², intermediate 140m², display at least Consultation, Cleaning-disinfecting room, storage (clean, contaminated), the office, equipped with a parking space. Entrust Cleaning-disinfecting type center on the premise that a maximum 134m², middle 119m², intermediate 109m² exhibited minimal activity room, consultation room, office, equipped with a parking space, collecting welfare when importing equipment warehouse (clean, pollution) have been proposed to equip up to.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.182-199
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• 2023

Since 2021, government departments have been promoting Automated Driving Technology Development and Innovation Project as national research and development(R&D) project. The automated vehicles and service technologies developed as part of these projects are planned to be subsequently provided to the public at the selected Living Lab City. Therefore, it is important to determine a spatial area and operation section that enables safe and stable automated driving, depending on the purpose and characteristics of the target service. In this study, the static Operational Design Domain(ODD) elements for Level 4 automated driving services were reclassified by reviewing previously published papers and related literature surveys and investigating field data. Spatial analysis techniques were used to consider the reclassified ODD elements for level 4 in the real area of level 3 automated driving services because it is important to reflect the spatial factors affecting safety related to real automated driving technologies and services. Consequently, a total of six driving mode changes(disengagement) were derived through spatial information analysis techniques, and the factors affecting the safety of automated driving were crosswalk, traffic light, intersection, bicycle road, pocket lane, caution sign, and median strip. This spatial factor analysis method is expected to be useful for determining special areas for the automated driving service.

• Journal of Korean Society of Forest Science
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• v.29 no.1
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• pp.20-53
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• 1976

For the purpose of detecting the capability of the trees to resist air pollution and of determining the tree species best suited for purification of polluted air, particularly with regard to $SO_2$ contamination, six following ornamental tree species were selected as experimental materials: i.e., Hibiscus syriacus L., Ginkgo biloba L., Forsythia koreana Nak., Syringa dilatata Nak., Larix leptolepis Gordon, and Pinus rigida Miller. The susceptiblities of the trees were observed and analyzed on the basis of area ratio of smoke injury spots to the total leaf area. The results of the experiments are as follows: I. The Susceptibilities to Sulfur Dioxide. (1) The decreasing order of tolerance to $SO_2$ by species was as follows: 1. Hibiscus syriacus 2. Ginkgo biloba, 3. Forsythia koreana, 4. Syringa dilatata, 5. Larix leptolepis, and 6. Pinus rigida. In general, Hibiscus syriacus and Ginkgo biloba can be grouped as the most resistant and Larix leptolepis and Pinus rigida as the least resistant and Forsythia koreana and Syringa dilatata as of intermediate resistance. (2) The sulfur content of the leaves treated by $SO_2$ increased in proportion to the increase of the concentration of the fumigation. The content in the coniferous species proved to be less than that of the broad-leaved species, but Ginkgo biloba proved to contain as much sulfur as broad-leaved species. (3) The earlier-stage leaves fumigated in June with the $SO_2$ concentration up-to-l-ppm showed that sulfur content increases in proportion to the increase of the concentration of the fumigation, but the difference between concentration was not so significant. (4) The later-stage leaves fumigated in October showed higher sulfur content than the earlier stage leaves, and a wider range of difference in sulfur content was detected among different concentrations. The limit of fumigation resulting in culmination of sulfur absoption in broad-leaved species, such as Syringa dilatata, Hibiscus syriacus, and Forsythia koreana proved to be around 0.6 ppm. (5) Due to the sprouting ability and the adventitious bud formation, the recovery from $SO_2$ fumigation was prominent in Hibiscus syriacus, Syringa dilatata, and Forsythia koreana. (6) The differences in the smoke spot color were recognized by species: namely, dirt-brown in Syringa dilatata, brilliant yellowish-brown in Pinus rigida and Ginkgo biloba, whitish-yellow in Hibiscus syriacus and reddish-brown in Forsythia koreana. (7) The leaf margins proved to be most susceptible, and the leaf bases of the mid-rib most tolerant. In both Ginkgo biloba and Larix leptolepis, the younger leaves were more resistant to $SO_2$ than the older ones. II. The ulfur Content of the Leaves of the Ornamental Trees Growing in the City of Seoul. (1) The sulfur contents in the leaves of the Seoul City ornamental trees showed a remarkably higher value than those of the leaves in the non-polluted areas. The sulfur content of the leaves in the non-polluted area proved to be in the following descending order: Salix pseudo-lasiogyne Leveille, Ginkgo biloba L., Alianthus altissima swingle, Platanus orientalis L., and Populus deltoides Marsh. (2) In respect to the sulfur contents in the leaves of the ornamental trees in the city of Seoul, the air pollution proved to be the worst in the areas of Seoul Railroad Station, the Ahyun Pass, and the Entrance to Ewha Womans University. The areas of Deogsu Palace, Gyeongbog Palace, Changdeog Palace, Changgyeong Park and the Hyehwa Intersection were least polluted, and the areas of the East Gate, the Ulchi Intersection and the Seodaemun Intersection are in the intermediate state.

• Economic and Environmental Geology
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• v.39 no.2 s.177
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• pp.163-171
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• 2006

This study is the case of groundwater development based on the geometrical fracture model of target area established only through geological fracture mapping technique. A fracture mapping of $9km^2$, eastern Munsan, has been conducted to determine geological and hydrological factors for new water well placement in the Gyeonggi gneiss complex. Geophysical exploration was not applicable because of small restricted area and dense underground utilities at the site. Form line mapping on the basis of foliation orientation and rock type revealed a synform of NS fold axis bearing to the south. An EW geological cross-section passed through the site area shows a F2 synform as a double-wall ice cream spoon shape. Three regional faults of $N20^{\circ}E,\;N30^{\circ}W$, and NS have been dragged into the site to help understand extensional fault paths. The $N20^{\circ}E$ fault with dextral sense is geometrically interpreted as a western fault of two flexural conjugate type-P shear faults in the F2 synformal fold. The NE cross-section reveals that a possible groundwater belt in the western limb of super-posed fold area is formed as a trigonal prism within 100 m depth of the intersectional space between the $N20^{\circ}E$ fault plane and the weakly sheared plane of transposed foliation. Another possible fault for water resource strikes $N40^{\circ}E$. Recommended sites for new water well placement are along the $N20^{\circ}E\;and\;N40^{\circ}E$ faults. As a result of fracture mapping, 145 ton/day of water can be produced at one well along the $N20^{\circ}E$ fault line. Exploration of groundwater in the area is succeeded only using with geological fracture mapping and interpretation of geological cross-section, without any geophysical survey. Intersection of fault generated with the F2 synformal fold and foliation supply space of groundwater reserver.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.33-44
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• 2001

The paper presents several satellite models and satellite image decomposition methods for inaccessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in $1^{st}$, $2^{nd}$ and $3^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\Phi$(phi) correlated highly with positional parameters could be assigned to constant values. For inaccessible area, satellite images were decomposed, which means that two consecutive images were combined as one image, The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1st order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.679-690
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• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.