• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.199-217
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• 2016

Influences of seasonal warming and cooling rates on the annual temperature patterns were analyzed based on the meteorological data from 13 weather stations in Busan Metropolitan Area(BMA), Korea during 1997~2014. BMA daily temperature time-series was generalized by Fourier analysis, which mathematically summarizes complex, regularly sampled periodic records, such as air temperature, into a limited number of major wave components. Local monthly warming and cooling rates of BMA were strongly governed by the ocean effect within the city. March($1.121^{\circ}C/month$) and November(-$1.564^{\circ}C/month$) were the two months, when the most rapid warming and cooling rates were observed, respectively during the study period. Geographically, spring warming rates of inland increased more rapidly compared to coastal areas due to weaker ocean effect. As a result, the annual maximum temperature was reached earlier in a location, where the annual temperature range was larger, and therefore its July mean temperature and continentality were higher. Interannual analyses based on average temperature data of all weather stations also showed that the annual maximum temperature tended to occur earlier as the city's July mean temperature increased. Percent area of impervious surfaces, an indicator of urbanization, was another contributor to temperature change rates of the city. Annual mean temperature was positively correlated with percent area of impervious surfaces, and the variations of monthly warming and cooling rates also increased with percent area of impervious surfaces.

• 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.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.239-252
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• 2022

Quality control methods for the first G-band vapor radiometer (GVR) mounted on a weather aircraft in Korea were developed using the GVR Precipitable Water Vapor (PWV). The aircraft attitude information (degree of pitch and roll) was applied to quality control to select the shortest vertical path of the GVR beam. In addition, quality control was applied to remove a GVR PWV ≥20 mm. It was found that the difference between the warm load average power and sky load average power converged to near 0 when the GVR PWV increased to 20 mm or higher. This could be due to the high brightness temperature of the substratus and mesoclouds, which was confirmed by the Communication, Ocean and Meteorological Satellite (COMS) data (cloud type, cloud top height, and cloud amount), cloud combination probe (CCP), and precipitation imaging probe (PIP). The GVR PWV before and after the application of quality control on a cloudy day was quantitatively compared with that of a local data assimilation and prediction system (LDAPS). The Root Mean Square Difference (RMSD) decreased from 2.9 to 1.8 mm and the RMSD with Korea Local Analysis and Precipitation System (KLAPS) decreased from 5.4 to 4.3 mm, showing improved accuracy. In addition, the quality control effectiveness of GVR PWV suggested in this study was verified through comparison with the COMS PWV by using the GVR PWV applied with quality control and the dropsonde PWV.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1191-1205
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• 2022

Particulate matter(PM) among air pollutants with complex and widespread causes is classified according to particle size. Among them, PM_2.5 is very small in size and can cause diseases in the human respiratory tract or cardiovascular system if inhaled by humans. In order to prepare for these risks, state-centered management and preventable monitoring and forecasting are important. This study tried to predict PM_2.5 in Seoul, where high concentrations of fine dust occur frequently, using two ensemble models, random forest (RF) and extreme gradient boosting (XGB) using 15 local data assimilation and prediction system (LDAPS) weather-related factors, aerosol optical depth (AOD) and 4 chemical factors as independent variables. Performance evaluation and factor importance evaluation of the two models used for prediction were performed, and seasonal model analysis was also performed. As a result of prediction accuracy, RF showed high prediction accuracy of R² = 0.85 and XGB R² = 0.91, and it was confirmed that XGB was a more suitable model for PM_2.5 prediction than RF. As a result of the seasonal model analysis, it can be said that the prediction performance was good compared to the observed values with high concentrations in spring. In this study, PM_2.5 of Seoul was predicted using various factors, and an ensemble-based PM_2.5 prediction model showing good performance was constructed.

• Journal of Environmental Science International
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• v.26 no.2
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• pp.221-230
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• 2017

To determine the effect of air pollution reduction policies, the long-term trend of air pollutants should be analyzed. Kolmogorov-Zurbenko (KZ) filter is a low-pass filter, produced through repeated iterations of a moving average to separate each variable into its temporal components. The moving average for a KZ(m, p) filter is calculated by a filter with window length m and p iterations. The output of the first pass subsequently becomes the input for the next pass. Adjusting the window length and the number of iterations makes it possible to control the filtering of different scales of motion. To break down the daily mean $PM_{10}$ into individual time components, we assume that the original time series comprises of a long-term trend, seasonal variation, and a short-term component. The short-term component is attributable to weather and short-term fluctuations in precursor emissions, while the seasonal component is a result of changes in the solar angle. The long-term trend results from changes in overall emissions, pollutant transport, climate, policy and/or economics. The long-term trend of the daily mean $PM_{10}$ decreased sharply from $59.6ug/m^3$ in 2002 to $44.6ug/m^3$ in 2015. This suggests that there was a long-term downward trend since 2005. The difference between the unadjusted and meteorologically adjusted long-term $PM_{10}$ is small. Therefore, we can conclude that $PM_{10}$ is unaffected by the meteorological variables (total insolation, daily mean temperature, daily mean relative humidity, daily mean wind speed, and daily mean local atmospheric pressure) in Busan.

• New & Renewable Energy
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• v.9 no.2
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• pp.15-22
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• 2013

The solar energy are an infinite source of energy and a clean energy without secondary pollution. The global solar energy reaching the earth's surface can be calculated easily according to the change of latitude, altitude, and sloped surface depending on the amount of the actual state of the atmosphere and clouds. The high-resolution solar-meteorological resource map with 1km resolution was developed in 2011 based on GWNU (Gangneung-Wonju National University) solar radiation model with complex terrain. The very high resolution solar energy map can be calculated and analyzed in Seoul and Eunpyung with topological effect using by 1km solar-meteorological resources map, respectively. Seoul DEM (Digital Elevation Model) have 10m resolution from NGII (National Geographic Information Institute) and Eunpyeong new town DSM (Digital Surface Model) have 1m spatial resolution from lidar observations. The solar energy have small differences according to the local mountainous terrain and residential area. The maximum bias have up to 20% and 16% in Seoul and Eunpyung new town, respectively. Small differences are that limited area with resolutions. As a result, the solar energy can calculate precisely using solar radiation model with topological effect by digital elevation data and its results can be used as the basis data for the photovoltaic and solar thermal generation.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.23-34
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• 2015

This Study analyzed heavy snow properties according to the area that was based by winter weather properties and the damage data by the heavy snow among each local government of Chungcheongbuk-do. The result of analysis, Jecheon-si and Boeun-gun are represented the highest dangerous regions by potential degree of risk by average amount of snowfall for 35 years. But, the potential degree of risk by maximum amount of snowfall for 35 years is different with it. Cheongju-si and Youngdong-gun, Goesan-gun, Boeun-gun are represented the highest dangerous regions. Examining the frequency of regions with potential danger factors according to the characteristics of heavy snowfall, Boeun-gun and Jecheon-si, Goesan-gun, Youngdong-gun, Cheongju-si is derived the highest dangerous regions in Chungcheongbuk-do.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.159-169
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• 1993

As Global Positioning System is able to provide 24-hour all weather surveying capability and high precision survey in three dimension, expected that the extensive use of GPS to support geophysics, geophysics, millitary and time correction etc. But in order to use the GPS results effectively, we have to solve problems about coordinates transformation relating the WGS84 to Bessel Datums and development of the accurate geoid undulation model. In this paper, we derive polynomial model equations about geoid undulation around local area(longitude $126^{\circ}{\sim}129^{\circ}$, latitude $36^{\circ}{\sim}37^{\circ}$) in Korea by GPS/Leveling method, also study the geoidal height calcaulation methods supplemented by Earth Gravitational Models (OSU981A, OSU86F).

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.87-95
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• 2006

Recently, local heavy rain for a short term is caused by unusual changing in the weather. This phenomenon has, several times, caused an extensive flash flood, casualties, and material damage. This study is aimed at calculating the characteristics of flash floods in streams. For this purpose, the analysis of topographical characteristics of water basin through applying GIS techniques will be conducted. The flash flood prediction model we used is made with GCIUH (geomorphoclimatic instantaneous unit hydrograph). The database is established by the use of GIS and by the extraction of streams and watersheds from DEM. The streams studied are included small, middle and large scale watersheds. For the first, for the establishment or criteria on the flash flood warning, peak discharge and trigger runoff must be decided. This study analyzed the degree or aptitude of topographical factors to the trigger runoff calculated by GCUH model.