• Journal of Environmental Impact Assessment
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• v.27 no.3
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• pp.291-306
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• 2018

This study was designed to predict potential habitat of Japanese evergreen oak (Quercus acuta Thunb.) in Korean Peninsula considering its dispersal ability under climate change. We used a species distribution model (SDM) based on the current species distribution and climatic variables. To reduce the uncertainty of the SDM, we applied nine single-model algorithms and the pre-evaluation weighted ensemble method. Two representative concentration pathways (RCP 4.5 and 8.5) were used to simulate the distribution of Japanese evergreen oak in 2050 and 2070. The final future potential habitat was determined by considering whether it will be dispersed from the current habitat. The dispersal ability was determined using the Migclim by applying three coefficient values (${\theta}=-0.005$, ${\theta}=-0.001$ and ${\theta}=-0.0005$) to the dispersal-limited function and unlimited case. All the projections revealed potential habitat of Japanese evergreen oak will be increased in Korean Peninsula except the RCP 4.5 in 2050. However, the future potential habitat of Japanese evergreen oak was found to be limited considering the dispersal ability of this species. Therefore, estimation of dispersal ability is required to understand the effect of climate change and habitat distribution of the species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.170-176
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• 2004

This study was carried out to establish a spatial decision support system for evaluating climatic aspects of a given geographic location in complex terrains with respect to the quality apple production. Monthly climate data from S6 synoptic stations across South Korea were collected for 1971-2000. A digital elevation model (DEM) with a 10-m cell spacing was used to spatially interpolate daily maximum and minimum temperatures based on relevant topoclimatological models applied to Jangsoo county in Korea. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Freezing risk in January was estimated under the recurrence intervals of 30 years. Frost risk at bud-burst and blossom was also estimated. Fruit quality was evaluated for soluble solids, anthocyanin content, Hunter L and A values, and LID ratio, which were expressed as empirical functions of temperature based on long-term field observations. AU themes were prepared as ArcGlS Grids with a 10-m cell spacing. Analysis showed that 11 percent of the whole land area of Jangsoo county might be suitable for quality 'Fuji' apple production. A computer program (MAPLE) was written to help utilize the results in decision-making for site-selection of new orchards in this region.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.1-16
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• 2019

Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.184-192
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• 2021

Domestic agriculture is facing real problems, such as a decrease in the population in rural areas, a shortage of labor due to an aging population, and increased risks due to the deepening of climate change. Smart farming technology is being developed to solve these problems. In the development of smart agricultural technology, irrigation control plays an important role in creating an optimal growth environment and is an important issue in terms of environmental protection. This paper is about the study of collecting and analyzing the rhizosphere environmental data of domestic paprika farms for the purpose of improving the quality of crops, reducing production costs, and increasing production. Irrigation control modeling presented in this paper Control modeling is to graphically present changes in a medium weight, feed, and drainage due to regional climatic features. To derive the graph, the parameters were determined through data collection and analysis, and the suggested irrigation control modeling method was applied to the collected rhizosphere environmental data to control irrigation in 6 regions (Gangwon-do, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, and Gyeongnam). The parameters were obtained and graphs were derived from them. After that, a study was conducted to analyze the derived parameters to verify the validity of the irrigation control modeling method and to correlate them with climatic features (average temperature and precipitation).

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.1-16
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• 2007

The use of information on natural resources is indispensable to most agricultural activities to avoid disasters, to improve input efficiency, and to increase lam income. Most information is prepared and managed at a spatial scale called the "Hydrologic Unit" (HU), which means watershed or small river basin, because virtually every environmental problem can be handled best within a single HU. South Korea consists of 840 such watersheds and, while other watershed-specific information is routinely managed by government organizations, there are none responsible for agricultural weather and climate. A joint research team of Kyung Hee University and the Agriculture, forestry and Fisheries Information Service has begun a 4-year project funded by the Ministry of Agriculture and forestry to establish a watershed-specific agricultural weather information service based on "high definition" digital climate maps (HD-DCMs) utilizing the state of the art geospatial climatological technology. For example, a daily minimum temperature model simulating the thermodynamic nature of cold air with the aid of raster GIS and microwave temperature profiling will quantify effects of cold air drainage on local temperature. By using these techniques and 30-year (1971-2000) synoptic observations, gridded climate data including temperature, solar irradiance, and precipitation will be prepared for each watershed at a 30m spacing. Together with the climatological normals, there will be 3-hourly near-real time meterological mapping using the Korea Meteorological Administration's digital forecasting products which are prepared at a 5 km by 5 km resolution. Resulting HD-DCM database and operational technology will be transferred to local governments, and they will be responsible for routine operations and applications in their region. This paper describes the project in detail and demonstrates some of the interim results.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.558-559
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• 2023

지구온난화와 기후변화로 인해 전세계적으로 기업, 정부는 ESG(Environmental, Social and Corporate Governance)에 관심을 가지고 있다. 이에 따라 폐기물 분류 및 재활용에도 관심을 가지고 있지만 국내 외 폐기물 분류는 정확하게 이루어 지지 않고 있다. 이에 본 논문에서는 객체 인식의 대표 모델인 YOLOv5 를 이용해 폐기물 중 대표인 페트병 탐지 시스템을 제안한다. 제안하는 시스템은 페트병 사이 다른 폐기물을 감지해 내고 페트병 중 유색과 투명 페트병을 분류를 한다. 향후, 제안하는 시스템의 성능 평가가 필요하고 다른 폐기물로 확장이 필요하다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.69-70
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• 2023

2023년에도 2월에는 튀르키예와 시리아에서 대규모 지진이 발생하고, 칠레에서는 대규모 산불이 발생하였으며, 8월에는 하와이에서 산불로 많은 인명피해가 있었으며, 9월에는 모로코에서 지진이 발생하였다. 또한, 국내에서는 역대 세 번째로 많은 봄철 산불과 6-7월에는 충북 청주의 궁평 지하차도를 포함한 전국적인 집중호우 등 국내외에서 이전에 경험하지 못한 수준의 극한 재난 사건들이 발생하였으며, 미래에는 이러한 사건들이 더욱 빈번하게 발생할 것으로 예측된다. 이상기후에 대비함과 동시에 재난 발생시 피해를 최소화하기 위한 다양한 방안에 대한 고려가 필요한 시점이다. 본 논문은 극한 재난이 발생하였을 때 발령하는 시스템부터 재난정보를 수신하는 국민에 이르기까지 전반적인 재난정보 전달 관점에서 고려하여 국민의 요구사항을 반영하여 재난정보를 효과·효율적으로 전달하는 방식에 대해 제안한다. 제안하는 방안을 통해 신속·정확·효율적인 재난정보 전달이 이루어져 재난으로부터 인명 및 재산상의 피해를 감소시킬 수 있을 것으로 기대된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.179-180
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• 2021

본 논문에서 자동제어를 이용하여 양어업에 쓰이는 큰 수조를 관리하고, 수온과 탁도를 측장하고 관리자에게 수조 안에서의 환경 및 정보를 제공할 수 있는 스마트 수조에 대해서 기술한다. 기존의 양어업의 경우, 작업 연령의 고령화, 노동 인구 감소 등 심각한 문제가 발생되고 있어 양어업의 노동의 질이 현저히 감소 되고 있다. 본 프로젝트에서는 작업자의 부재 상황에서도 블루투스 무선통신을 활용하여 실시간으로 수조 환경에 대한 정보를 수신받을 수 있고, 수조를 자동화함으로써 급격한 기후변화로 인한 어류 및 어패류의 집단폐사에 대한 대비도 가능하다. 이를 구성하기 위해서 아두이노 메가 2560 메인으로 선택하여 많은 핀들을 연결 하였고, 블루투스 모듈을 통해서 실시간으로 정보를 수신받고, 간단한 조작이 가능하여 노동인구에 대한 문제를 해결할 수 있을 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.271-276
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• 2009

An local area weather condition monitoring system to minimize many disasters from the sudden change of weather condition in local and mountain area is proposed. Firstly, the comparison of present state of the related monitoring systems and the possibility of realization with some merits are investigated. Moreover, this paper present direction of local area weather condition monitoring system based on integration of wireless sensor network and CDMA network following some case study. Through the efficient integration of both networks, the measured weather condition data from sensors can be transmitted to the server or mobile to monitor with high reliability. The proposed monitoring system will guide new type of project in wireless sensor network and support alarm service of the sudden change of weather condition to mobile user from central official regulations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.4
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• pp.121-131
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• 2008

This study was conducted to delineate temporal and spatial patterns of potential risk of cold injury by combining the short-term cold hardiness of Campbell Early grapevine and the IPCC projected climate winter season minimum temperature at a landscape scale. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HD-DTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations using a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and elevation). The same procedure was applied to the official temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 and A1B scenarios) for 2071-2100. The dormancy depth model was run with the gridded datasets to estimate the geographical pattern of any changes in the short-term cold hardiness of Campbell Early across South Korea for the current and future normal years (1971-2000 and 2071-2100). We combined this result with the projected mean annual minimum temperature for each period to obtain the potential risk of cold injury. Results showed that both the land areas with the normal cold-hardiness (-150 and below for dormancy depth) and those with the sub-threshold temperature for freezing damage ($-15^{\circ}C$ and below) will decrease in 2071-2100, reducing the freezing risk. Although more land area will encounter less risk in the future, the land area with higher risk (>70%) will expand from 14% at the current normal year to 23 (A1B) ${\sim}5%$ (A2) in the future. Our method can be applied to other deciduous fruit trees for delineating geographical shift of cold-hardiness zone under the projected climate change in the future, thereby providing valuable information for adaptation strategy in fruit industry.