• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.225-236
• /
• 2022

Urbanization due to population growth and regional development can cause various environmental problems, such as the urban heat island phenomenon. A planned city is considered an appropriate study site to analyze changes in urban climate caused by rapid urbanization in a short-term period. In this study, changes in land cover and surface heat island phenomenon were analyzed according to the development plan in Sejong City from 2013 to 2020 using Landsat-8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) satellite imagery. The surface temperature was calculated in consideration of the thermal infrared band value provided by the satellite image and the emissivity, and based on this the surface heat island effect intensity and Urban Thermal Field Variance Index (UTFVI) change analysis were performed. The level-2 land cover map provided by the Ministry of Environment was used to confirm the change in land cover as the development progressed and the difference in the surface heat island intensity by each land cover. As a result of the analysis, it was confirmed that the urbanized area increased by 15% and the vegetation decreased by more than 28%. Expansion and intensification of the heat island phenomenon due to urban development were observed, and it was confirmed that the ecological level of the area where the heat island phenomenon occurred was very low. Therefore, It can suggest the need for a policy to improve the residential environment according to the quantitative change of the thermal environment due to rapid urbanization.

• Microbiology and Biotechnology Letters
• /
• v.50 no.2
• /
• pp.165-192
• /
• 2022

The microbial metagenome characteristics of bioaerosols and particulate matter (PM) in the outdoor atmospheric environment and the effects of climate and environmental factors on the metagenome were analyzed. The concentrations of bacteria and fungi in bioaerosols and PM were determined by sampling different regions with different environmental properties. A variety of culture-independent methods were used to analyze the microbial metagenome in aerosols and PM samples. In addition, the effects of meteorological and environmental factors on the diversity and metagenomes of bacteria and fungi were investigated. The survival, growth, and dispersal of the microorganisms in the atmosphere were markedly affected by local weather conditions and the air pollutant concentration. The concentration of airborne microorganisms increased as the temperature increased, but their concentration decreased in summer, due to the effects of high temperatures and strong ultraviolet rays. Humidity and microbial concentration were positively correlated, but when the humidity was too high, the dispersion of airborne microorganisms was inhibited. These comprehensive data on the microbial metagenome in bioaerosols and PM may be used to understand the roles and functions of microorganisms in the atmosphere, and to develop strategies and abatement techniques to address the environmental and public health problems caused by these microorganisms.

• Journal of the Korean earth science society
• /
• v.44 no.2
• /
• pp.135-147
• /
• 2023

Satellite-observed significant wave heights (SWHs), which are widely used to understand the response of the ocean to climate change, require long-term and continuous validation. This study examines the accuracy and error characteristics of SWH observed by nine satellite altimeters in the North Pacific and North Atlantic Ocean for 25 years (1992-2016). A total of 137,929 matchups were generated to compare altimeter-observed SWH and in-situ measurements. The altimeter SWH showed a bias of 0.03 m and a root mean square error (RMSE) of 0.27 m, indicating relatively high accuracy in the North Pacific and North Atlantic Ocean. However, the spatial distribution of altimeter SWH errors showed notable differences. To better understand the error characteristics of altimeter-observed SWH, errors were analyzed with respect to in-situ SWH, time, latitude, and distance from the coast. Overestimation of SWH was observed in most satellite altimeters when in-situ SWH was low, while underestimation was observed when in-situ SWH was high. The errors of altimeter-observed SWH varied seasonally, with an increase during winter and a decrease during summer, and the variability of errors increased at higher latitudes. The RMSEs showed high accuracy of less than 0.3 m in the open ocean more than 100 km from the coast, while errors significantly increased to more than 0.5 m in coastal regions less than 15 km. These findings underscore the need for caution when analyzing the spatio-temporal variability of SWH in the global and regional oceans using satellite altimeter data.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.4
• /
• pp.433-447
• /
• 2023

There is a growing demand for the stability of existing dams due to abnormal climate and the aging of dams. Emergency Action Plans (EAPs) for reservoir or dam failure only consider a single rainfall event. Therefore, this study simulates dam failure caused by continuous rainfall events, and proposes the establishment of EAP by selecting the optimal shelters. We define a mega rainfall event scenario caused by continuous rainfall events with 500-year frequency in the Chungju Dam watershed and estimate the mega flood. The mega flood event scenario is divided into two cases: scenario A represents the flooding case caused by discharge release from a dam, while scenario B is the case of a dam break. As a result of flood inundation analysis, the flooded damage area by the scenario A is 50.06 km² and the area by the scenario B is 6.1 times of scenario A (307.45 km²). We select optimal shelters for each administrative region in the city of Chungju, which has the highest inundation rate in the urban area. Seven shelter evaluation indicators from domestic and foreign shelter selection criteria are chosen, and Analytical Hierarchy Process (AHP) method is used to evaluate the alternatives. As a result of the optimal shelter selection, the six shelters are selected and five are schools. This study considers continuous rainfall events for inundation analysis and selection of optimal shelters. Also, the results of this study could be used as a reference for establishment of the EAP.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.5B
• /
• pp.487-495
• /
• 2010

Soil moisture is a crucial factor in hydrological system which influences runoff, energy balance, evaporation, and atmosphere. United States National Aeronautic and Space Administration (NASA) and Department of Agriculture (USDA) have established Soil Moisture Experiment (SMEX) since 2002 for the global observations. SMEX provides useful data for the hydrological science including soil moisture and hydrometeorological variables. The purpose of this study is to investigate the relationship between remotely sensed soil moisture data from aircraft and satellite and ground based experiment. C-band of Polarimetric Scanning Radiometer (PSR) that observed the brightness temperature provides soil moisture data using a retrieval algorithm. It was compared with the In-situ data for 2-30 cm depth at four sites. The most significant depth is 2-10 cm from the correlation analysis. Most of the sites, two data are similar to the mean of data at 10 cm and the median at 7 cm and 10 cm at the 10% significant level using the Rank Sum test and t-test. In general, soil moisture data using the C-band of the PSR was established to fit the Normal, Log-normal and Gumbel distribution. Soil moisture data using the aircraft and satellites will be used in hydrological science as fundamental data. Especially, the C-band of PSR will be used to prove soil moisture at 7-10 cm depths.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.55-63
• /
• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• The Korean Journal of Applied Statistics
• /
• v.36 no.1
• /
• pp.49-62
• /
• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Korean Journal of Soil Science and Fertilizer
• /
• v.44 no.5
• /
• pp.887-894
• /
• 2011

To evaluate the effects of abiotic factors of paddy fields on greenhouse gases (GHGs) emissions from rice paddy fields, $CH_4$ emission amounts were investigated from rice paddy fields by different soil organic matter contents, paddy types, and agricultural climatic zone in Yeongnam area during 3 years. $CH_4$ emission amounts according to soil organic matter contents in paddy field were conducted at having different contents of 5 soil organic matters fields (23.6, 28.7, 31.0, 34.5, and $38.0g\;kg^{-1}$), The highest $CH_4$ emission amount was recorded in the highest soil organic matters plot of $38.0g\;kg^{-1}$. High correlation coefficient (r=$0.963^{**}$) was obtained between $CH_4$ emissions from paddy fields and their soil organic matter contents. According to paddy field types, $CH_4$ emission amounts were investigated at 4 different paddy fields as wet paddy, sandy paddy, immature paddy, and mature paddy. The highest $CH_4$ emissions was recorded in wet paddy (100%) and followed as immature paddy 64.0%, mature paddy 46.8%, and sandy paddy 23.8%, respectively. For the effects of temperature on $CH_4$ emissions from paddy fields, 4 agricultural climatic zones were investigated, which were Yeongnam inland zone (YIZ), eastern coast of central zone (ECZ), plain area of Yeongnam inland mountainous zone (PMZ), and mountainous area of Yeongnam inland mountainous zone (MMZ). The order of $CH_4$ emission amounts from paddy fields by agricultural climatic zone were YIZ (100%) > ECZ (94.6%) > PMZ (91.6%) > MMZ (78.9%). The regression equation between $CH_4$ emission amounts from paddy fields and average air temperature of Jul. to Sep. of agricultural climatic zone was y = 389.7x-4,287 (x means average temperature of Jul. to Sep. of agricultural climatic zone, $R^2=0.906^*$)

• Atmosphere
• /
• v.24 no.3
• /
• pp.303-315
• /
• 2014

Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.

• Journal of the Korea Organic Resources Recycling Association
• /
• v.29 no.1
• /
• pp.19-27
• /
• 2021

Hydroponic farming is a method to grow a plant without soil. Plants can be grown on water or hydroponic growing media, and they are fed with mineral nutrient solutions, which are fertilizers dissolved into water. Hydroponic farming has the advantage of increasing plant productivity over conventional greenhouse farming. Previous studies of hydroponic nutrient wastewater from acyclic hydroponic farms pointed out that hydroponic nutrient wastewater contained residual nutrients, and they were drained to a nearby river bank which causes several environmental issues. Also, previous studies suggest that excessive use of the nutrient solution and disposal of used hydroponic growing media and crop wastes in hydroponic farms are major problems to hydroponic farming. This study was conducted to determine the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment by analyzing water quality and soil analysis of the above three factors. Three soil cultivation farms and several hydroponic farms in the Gangwon C region were selected for this study. Samples of water and soils were collected from both inside and outside of each farm. Also, a sample of soil and leachate from crop waste piles stacked near the farm was collected for analysis. Hydroponic nutrient wastewater from acyclic hydroponic farm contained an average of 402 mg/L of total nitrogen (TN) concentration, and 77.4 mg/L of total phosphate (TP) concentration. The result of TP in hydroponic nutrient wastewater exceeds the living environmental standard of the river in enforcement decree of the framework act on environmental policy by 993.7 times. Also, it exceeds the standard of industrial wastewater discharge standards under the water environment conservation act by 6~19 times in TN, and 2~27 times in TP. Leachate from crop waste piles contained 11,828 times higher COD and 395~2662 times higher TP than the standard set by the living environmental standard of the river in enforcement decree of the framework act on environmental policy and exceeds 778 times higher TN and 5 times higher TP than the standard of industrial wastewater discharge standards under the water environment conservation act. For more precise studies of the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment, additional information regarding a number of hydroponic farms, arable area(ha), hydroponic farming area, seasonal, weather, climate factor around the river, and the property of the area and farm is needed. Analysis of these factors and additional water and soil samples are needed for future studies.