• Korean Journal of Remote Sensing
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• 제38권6_1호
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• pp.1479-1488
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• 2022

Accidents in which oil spills occur intermittently in the ocean due to ship collisions and sinkings. In order to prepare prompt countermeasures when such an accident occurs, it is necessary to accurately identify the current status of spilled oil. To this end, the Coast Guard patrols the target area with a fixed-wing airplane or helicopter and checks it with the naked eye or video, but it was difficult to determine the area contaminated by the spilled oil and its exact location on the map. Accordingly, this study develops a technology for direct ortho-rectification by automatically geo-referencing aerial images collected by the Coast Guard without individual ground reference points to identify the current status of spilled oil. First, meta information required for georeferencing is extracted from a visualized screen of sensor information such as video by optical character recognition (OCR). Based on the extracted information, the external orientation parameters of the image are determined. Images are individually orthorectified using the determined the external orientation parameters. The accuracy of individual orthoimages generated through this method was evaluated to be about tens of meters up to 100 m. The accuracy level was reasonably acceptable considering the inherent errors of the position and attitude sensors, the inaccuracies in the internal orientation parameters such as camera focal length, without using no ground control points. It is judged to be an appropriate level for identifying the current status of spilled oil contaminated areas in the sea. In the future, if real-time transmission of images captured during flight becomes possible, individual orthoimages can be generated in real time through the proposed individual orthorectification technology. Based on this, it can be effectively used to quickly identify the current status of spilled oil contamination and establish countermeasures.

• Korean Journal of Remote Sensing
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• 제38권6_1호
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.

• Journal of Korean Home Economics Education Association
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• 제34권3호
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• pp.101-116
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• 2022

This study aims to apply the problem-based learning method to a college course on 'Consumer Studies' in a teacher education program. The participants of this study were 27 undergraduate students who were enrolled in the course. The PBL class was implemented for seven weeks using two problems: proposing special lectures on economic concepts and financial consulting. The effectiveness of PBL was analyzed through self-reflective journals, self-assessment, and a learning satisfaction survey of students. The result of this study was as follows. Students achieved the learning objectives and strengthened their collaboration and communication skills with team members during the PBL process. Moreover, students improved their self-directed learning and problem-solving ability through the PBL class. The results of self-assessment, in terms of learning task performance, active interaction, and self-directed learning were generally high at 4.63 points. In addition, the overall learning satisfaction level was very high, with a score of 4.75. The results will provide effective information on PBL classes to instructors and prospective teachers and will be used as data for learner-centered PBL classes.

• Journal of Korean Tunnelling and Underground Space Association
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• 제23권6호
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• pp.549-558
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• 2021

In order to keep infrastructures such as tunnels and underground facilities safe, cracks of concrete lining in tunnel should be detected by regular inspections. Since regular inspections are accomplished through manual efforts using maintenance lift vehicles, it brings about traffic jam, exposes works to dangerous circumstances, and deteriorates consistency of crack inspection data. This study aims to provide methodology to automatically extract cracks from tunnel concrete lining images generated by the existing tunnel image acquisition system. Specifically, we train a deep learning based semantic segmentation model with open dataset, and evaluate its performance with the dataset from the existing tunnel image acquisition system. In particular, we compare the model performance in case of using all of a public dataset, subset of the public dataset which are related to tunnel surfaces, and the tunnel-related subset with negative examples. As a result, the model trained using the tunnel-related subset with negative examples reached the best performance. In the future, we expect that this research can be used for planning efficient model training strategy for crack detection.

• Ecology and Resilient Infrastructure
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• 제9권1호
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• pp.15-23
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• 2022

This study was conducted to investigate in relation to characteristic of macroinvertebrates in conventional and organic paddy fields. The investigation was conducted five times a year for Suwon, Ansung, Boeun, Gunsan, Gimje, Hamyang, divide into conventional paddy fields and organic paddy fields from 2009 to 2011. The macroinvertebrates collected from the surveyed between conventional and organic paddy fields belonged to 84 species, 47 families, 16 orders, and 6 classes in 3 phyla. In the habitat orientied groups, climbers, swimmers and sprawlers were considerably occupied in conventional and organic paddy fields. In relation to the functional feeding groups, predators such as Odonata, Coleoptera, and Hemiptera were only the highest in paddy field ecosystem, regardless of cultivation method. As a result of community stability analysis, orgainc paddy fields has been identified much as species high resistance and resilience to environmental change in paddy field ecosystem. Species belonging to the I groups is considered to be important in organic paddy field such as Sternolophus rufipes, Hydrochara affinis, Helochares nipponicus, which has high mobility. In conclusion, it was found that the introduction of coleoptera as a food source was higher than that of conventional paddy fields in organic paddy field where primary consumers were abundant such as Chironomidae spp. and Dixidae sp..

• Journal of IKEEE
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• 제26권3호
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• pp.483-487
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• 2022

In this paper, we design a self-powered Arduino system for solar energy harvesting and explain its operation. To perform the operation, the Arduino system senses the amount of solar energy that changes every moment and adjusts the ratio of the active mode and sleep mode operation time according to a given solar light intensity. If the intensity of sunlight is strong enough, the Arduino system can be continuously driven in active mode and receive sufficient power from sunlight. If not, the system can run in sleep mode to minimize power consumption. As a result, it can be seen that energy consumption can be minimized by reducing power consumption by up to 81.7% when using sleep mode compared to continuously driving active mode. Also, when the light intensity is at an intermediate level, the ratio between the active mode and the sleep mode is appropriately adjusted according to the light intensity to operate. The method of self-control of the operating time ratio of active mode and sleep mode, proposed in this paper, is thought to be helpful in energy-efficient operation of the self-powered systems for wearables and bio-health applications.

• Korean Journal of Agricultural and Forest Meteorology
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• 제24권3호
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• pp.179-189
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• 2022

Ice and water droplets rise and fall above the freezing altitude under the effects of strong updrafts and downdrafts, grow into hail, and then fall to the ground in the form of balls or irregular lumps of ice. Although such hail, which occurs in a local area within a short period of time, causes great damage to the agricultural and forestry sector, there is a paucity of domestic research toward predicting hail. The objective of this study was to introduce Land-Atmosphere Modeling Package (LAMP) hail prediction and measure its performance for 50 hail events that occurred from January 2020 to July 2021. In the study period, the frequency of occurrence was high during the spring and during afternoon hours. The average duration of hail was 15 min, and the average diameter of the hail was 1 cm. The results showed that LAMP predicted hail events with a detection rate of 70%. The hail prediction performance of LAMP deteriorated as the hail prediction time increased. The radar reflectivity of actual cases of hail indicated that the average maximum reflectivity was greater than 40 dBZ regardless of altitude. Approximately 50% of the hail events occurred when the reflectivity ranged from 30~50 dBZ. These results can be used to improve the hail prediction performance of LAMP in the future. Improved hail prediction performance through LAMP should lead to reduced economic losses caused by hail in the agricultural and forestry sector through preemptive measures such as net coverings.

• Korean Association of Arts Management
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• 제53호
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• pp.101-125
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• 2020

This paper presents the problems and improvement methods in estimating demand and benefit, which have been controversial in the feasibility study of building cultural facilities. Although there are justifications for supplying cultural facilities by expanding leisure time and increasing income, the economic burden from the insolvent operation after construction is high. Feasibility studies can prevent these problems in advance. In order to estimate the demand for cultural facilities, similar facilities were selected and the gravity model was used to estimate the demand. In the future, it is necessary to prepare the criteria for setting the reference facility to increase the accuracy of the demand estimation. In addition, in the case of cultural facilities constructed through feasibility study, it is necessary to induce and enforce the disclosure of operational data and information, and to establish a database so that it can be used as a reference facility for demand estimation in future feasibility study on cultural facility. Accurate benefit estimation requires multiple CVM surveys. In addition to the current CVM survey, this paper suggest that supplementary online non-face-to-face surveys is considered. Furthermore, this research suggests that the use of video media for explanation of alternative materials for cultural facilities to be constructed because the WTP may be excessive due to lack of alternatives for survey respondents in the current CVM survey.

• Korean Journal of Agricultural and Forest Meteorology
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• 제24권4호
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• pp.234-243
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• 2022

In Korea, hail damage occurs every year, and in the case of agriculture, it causes severe field crop and cultivation facility losses. Therefore, it is necessary to develop a hail information service system customized for Korea's primary production and crop-growing areas to minimize hail damage. However, the observation of hail is relatively more difficult than that of other meteorological variables, and the available data are also spatially and temporally variable. A hail information service system was developed to understand the temporal and spatial distribution of hail occurrence. As part of this, a hail observation database was established that integrated the observation data from Korea Meteorological Administration with the information from newspaper reports. Furthermore, a hail risk map was produced based on this database. The risk map presented the nationwide distribution and characteristics of hail showers from 1970 to 2018, and the northeastern region of South Korea was found to be relatively dangerous. Overall, hail occurred nationwide, especially in the northeast and some inland areas (Gangwon, Gyeongbuk, and Chungbuk province) and in winter, mainly on the north coast and some inland areas as graupel (small and soft hail). Analyzing the time of day, frequency, and hailstone size of hail shower occurrences by region revealed that the incidence of large hail stones (e.g., 10 cm at Damyang-gun) has increased in recent years and that showers occurred mainly in the afternoon when the updraft was well formed. By integrating multidisciplinary data, the temporal and spatial gap in hail data could be supplemented. The hail risk map produced in this study will be helpful for the selection of suitable crops and growth management strategies under the changing climate conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• 제24권4호
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.