• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.943-960
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• 2009

This study suggests an algorithm for generating TMY(typical meteorological year) for the Korean peninsula, and generates the TMY based on the algorithm using 11 years(1998~2008) wind data observed at 77 sites of Regional Meteorological Offices(RMO). The algorithm consists of computing TMM scores based on the various statistics defined by the Fikenstein-Shafer statistical model and, in turn, generating TMY based on the TMM scores. Also the algorithm has two stages designed to yield the best representation of the regional wind characteristics appeared during the 11 years(1998~2008). The first stage is designed for the representation of each of 77 regions of RMO and the second is for the Korean peninsula. Various comparison studies are provided to demonstrate the properties of the TMY like its utility and typicality.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.345-356
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• 2010

In this paper, we introduce the linear regression model taking the parametric spatial association structure into account and employ it to five-year averaged wind speed data measured at 460 meteorological monitoring stations in South Korea. From the prediction map obtained by the model with spatial association parameters, we can see that inland area has smaller wind speed than coastal regions. When comparing the spatial linear regression model with classical one by using one-leave-out cross-validation, the former outperforms the latter in terms of similarity between the observations and the corresponding predictions and coverage rate of 95% prediction intervals.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.28-41
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• 2023

The objective of the study was to develop an Urban Windway Forest Creation Planning Technique for the Improvement of the Urban Environment using the case of Daejeon Metropolitan City. Through a spatial analysis of fine dust and heat waves, a basin zone, in which the concentration was relatively serious, was derived, and an area with the potential of cold air flow was selected as the target area for the windway forest development by analyzing the climate and winds in the relevant zone. Extreme fine dust areas included the areas of the Daejeon Industrial Complex Regeneration Business District in Daedeok-gu and Daedeok Techno Valley in Yuseong-gu. Heat wave areas included the areas of Daedeok industrial Complex in Moksang-dong, the Daejeon Industrial Complex Regeneration Business District in Daehwa-dong, and the high-density residential area in Ojeong-dong. As a result of measuring the wind speeds in Daejeon with an Automatic Weather System, the average wind speeds during the day and night were 0.1 to 1.7 m/s,, respectively. So, a plan of for a windway forest that smoothly induces the movement of cold air formed in outer forests at night is required. The fine dust/heat wave intensive management zones of Daejeon Metropolitan City were Daejeoncheon, Yudeungcheon, Gapcheon-Yudeungcheon, and Gapcheon. The windway forest formation plan case involved the old city center of Daejeon Metropolitan City among the four zones, the Gapcheon-Yudeungcheon area, in which the windway formation effect was presumed to be high. The Gapcheon-Yudeungcheon area is a downtown area that benefits from the cold and fresh air generated on Mt. Gyejok and Mt. Wuseong, which are outer forests. Accordingly, the windway forest was planned to spread the cold air to the city center by connecting the cold air generated in the Seosa-myeon forest of Mt. Gyejok and the Namsa-myeon forest of Mt. Wuseong through Gapcheon, Yudeungcheon, and street forests. After selecting the target area for the wind ventilation forest, a climate map and wind formation function evaluation map were prepared for the area, the status of variation wind profiles (night), the status of fine dust generation, and the surface temperature distribution status were grasped in detail. The wind ventilation forest planning concept and detailed target sites by type were identified through this. In addition, a detailed action plan was established according to the direction of creation and setting of the direction of creation for each type of wind ventilation forest.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.2
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• pp.104-110
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• 1997

Increase of marine transpotation in coastal area frequently yields oil spill accidents due to collision or grounding of oil tankers, which affects great deal of damages on ocean environments. Exact prediction of oil pollution area in time domain, which is called oil map, is very important for effective and efficient oil recovery and minimization of environmental damage. The prediction is carried out by considering the two distinct processes which are initial diffusion on the still water surface and advection due to tide, wind wave induced surface currents. In the present paper, only the initial diffusion is dealt with. Somewhat new simulation model and its numerical scheme are proposed to predict it. Simple diffusion experiment is also carried out to check the validity of the present method. Furthermore, some example simulations are performed for virtual oil spill accident. Quite realistic oil map including oil thickness distributions can be obtained by the present model.

• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.12-23
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• 2019

This study aims to suggest analysis schemes of urban forests acting as wind ventilation corridor(wind ventilation forest). For this purpose, wind corridor forests were classified into three types: wind-generating forests(WGF), wind-spreading forests (WSF), and wind-connecting forests(WCF), and they were classified into three grades. WGF, WSF and WCF were classified based on the density of forest type map, vegetation index, and ventilation networks, respectively. As a result of analyzing wind corridor forests for Daegu Metropolitan City(883.56㎢), the area of WGF was classified as 443.1㎢ and distributed in the northern and southern regions of Daegu Metropolitan City. Among them, the first grade of WGF occupied the largest area(345.59㎢) and the highest rate(54.44%) in Dalseong-gun. On the other hand, WGF was not found in Jung-gu, because this administrative district is isolated from the forest area. WSF was 32.4㎢, which included representative urban parks of Daegu Metropolitan City, and WSF were found relatively much in Suseong-gu and Dalseong-gun. However, WSF were distributed throughout Metropolitan City, and the vegetation index was not high. The ventilation network that can form WCF included major rivers and roads in Daegu Metropolitan City, but this network was not connected to the urban park from the outer forest. Therefore, it was judged that the formation of WCF connecting WGF outside the city and WSF inside the city would be important. The results of this study can be used as a basic data for systematic wind corridor forest projects, and can be used as basic data for establishing guidelines for wind corridor forest analysis at national and local levels.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.188.2-188.2
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• 2010

북한은 자급자족의 형태로 지하자원과 수력을 이용하여 에너지원으로 사용하고 수입연료를 자제하는 실정이다. 하지만 기존의 발전 설비들의 노후화와 지하자원의 확보의 어려움이 증가 되어 신재생에너지의 개발을 확대하고 있다. 이에 우리나라에서는 남북의 기술교류 확대 및 미래 에너지 자원의 확보를 위하여 북한 자원자원에 대한 연구가 이뤄지고 있다. 기존의 연구에서는 북한지역의 관측값을 활용하거나 저해상도의 바람지도들이 작성되었다. 북한 지역의 바람의 분포를 세밀히 파악하기 위하여 기존의 바람지도 보다 상세한 풍력-기상자원지도가 필요하기 때문에 연구를 진행하였다. 북한의 풍력-기상자원지도를 개발하기 위해 미국 NCAR에서 개발한 중규모 모형인 WRF(Weather Research & Forcasting)을 활용하였다. 좋은 풍력자원을 갖춘 장소에 풍력 단지를 조성하기 위해서는 고해상도의 기상자원지도를 이용해서 파악하는 것이 필요하므로 해상도를 1km으로 설정하여 수행되었다. 본 연구의 결과로 지상 80 m에서의 1km 해상도를 갖는 풍력-기상자원지도를 작성하였다. 개발된 풍력-기상자원지도의 검증을 위해서 우리나라에서 확보가 가능한 북한 27개 지점의 지상 10 m 바람자료들을 활용하였다. 풍속에 대한 검증은 Bias와 RMSE을 이용하였으며, 풍향의 검증은 MAE을 활용하였다. 연 평균의 북한의 풍력-기상자원지도를 보면, 북한의 산맥을 중심으로 다른 지역보다 높은 풍속 분포를 보이고 있으며, 황해도를 포함한 북한의 서해안지역에서 비교적 높은 풍속의 분포를 나타내고 있다. 계절별로 살펴보면 봄철과 겨울철에 여름과 가을철보다 높은 풍력자원이 나타나며, 여름철이 가장 낮은 풍력자원을 갖는 것으로 분석되었다.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.6
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• pp.545-554
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• 1998

The diurnal variation of O3 concentration shows two peaks, the first peak at noontime and the secondary peak at night. In order to show why the secondary peak, high nocturnal O3 concentration, occurs without sunlight which is a essential factor of a photochemical response, the O3 concentration, several weather elements and synoptic weather map were used for June∼September at 1995, 1996. The mean concentration of high nocturnal O3 concentration days is higher by 5.4 ppb than that of low nocturnal O3 concentration days. The nocturnal O3 concentration is higher than that of diurnal O3 concentration during high nocturnal O3 concentration days, at July, 1995 and June, 1996. The high nocturnal O3 concentration is related to low air pressure, high cloud cover and high wind speed. The correlation coefficient, r. between nocturnal O3 concentration and wind speed, pressure and cloud cover is 0.387, -0.218, and 0.194, respeftiviely. It is interesting that the O3 concentration increases at Pusan when the typhoon passes by. The same result showed at Taegu when the typhoon FAYE passed by. According to the analysis of nocturnal O3 concentration for June∼September at 1995 and 1996, it seems that the high nocturnal O3 concentration relates to the trough and cyclones passing by Pusan.