• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.109-120
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• 2015

Spatial heterogeneous characteristics of solar radiation energy from Climate Change gives rise to energy imbalance in the general ecological system including water resources. This study is to estimate the $CO_2$ flux of South Korea using Terra MODIS image and to assess the reliability of MODIS data from the ground measured $CO_2$ flux by eddy covariance flux tower data at 3 locations (two at mixed forest area and one at rice paddy area). The MODIS Gross Primary Productivity (GPP) product (MOD17A2), 8-day composite at 1-km spatial resolution was adopted for the spatial $CO_2$ flux generation. The MOD17A2 data by noise like cloud and snow in a day were tried to fill by Inverse Distance Weighted (IDW) method from valid pixels and the damping effect of MOD17A2 data were corrected by Quality Control (QC) flag. The MODIS $CO_2$ flux was estimated as the sum of GPP and Re (ecosystem respiration) by Lloyd and Taylor method (1994). The determination coefficient ($R^2$) between MODIS $CO_2$ and flux tower $CO_2$ for 3 years (2011~2013) showed 0.55 and 0.60 in 2 mixed forests and 0.56 in rice paddy respectively. The $CO_2$ flux generally fluctuated showing minus values during summer rainy season (from July to August) and maintaining plus values for other periods. The MODIS $CO_2$ flux can be a useful information for extensive area, for example, as a reliable indicator on ecological circulation system.

• Atmosphere
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• v.24 no.1
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• pp.101-110
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• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.125-143
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• 2017

This study is conducted to estimate potential evapotranspiration of 10 weather observing systems in Andong Dam watershed with FAO56 Penman-Monteith (FAO56 PM) methodology using the meteorological data from 2013 to 2014. Also, assuming that there is no solar radiation data, humidity data or wind speed data, the potential evapotranspiration was estimated by FAO56 PM and the results were evaluated to discuss whether the methodology is applicable when meteorological dataset is not available. Then, the potential evapotranspiration was estimated with Hargreaves method and compared with the potential evapotranspiration estimated by FAO56 PM only with the temperature dataset. As to compare the potential evapotranspiration estimated from the complete meteorological dataset and that estimated from limited dataset, statistical analysis was performed using the Root Mean Square Error (RMSE), the Mean Bias Error (MBE), the Mean Absolute Error (MAE) and the coefficient of determination ($R^2$). Also the Inverse Distance Weighted (IDW) method was performed to conduct spatial analysis. From the result, even when the meteorological data is limited, FAO56 PM showed relatively high accuracy in calculating potential evapotranspiration by estimating the meteorological data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.343-350
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• 2022

High-resolution data are needed to understand water body mixing patterns at river junctions. In particular, in river analysis, hydrological and water quality characteristics are used as basic data for aquatic ecological health, so observation through continuous monitoring is necessary. In addition, since measurement is carried out through a one-dimensional and fixed measurement method in existing monitoring systems, a hydrological and water quality characteristics investigation of an entire river, except for in the immediate vicinity of the measurement point, is not undertaken. In order to obtain high-resolution measurement data, a measurer has to consider multiple factors, and the area or time that can be measured is limited. Although the resolution might be lowered, an appropriate interpolation method must be selected in order to acquire a wide range of data. Therefore, in this study, a high-elevation measurement method at a river junction was introduced, and the interpolation method according to the measurement results was compared. The overall hydraulic and water quality information of the river was indicated through the visualization of the prediction and interpolation method in the low-resolution measurement result. By comparing each interpolation method, Inverse Distance Weighting, Natural Neighbor, and Kriging techniques were applied in river mapping to improve the precision of river mapping through visualized data and quantitative evaluation. It is thought that this study will offer a new method for measuring rivers through spatial interpolation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.359-365
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• 2011

This study aims at filtering ALS points into ground and non-ground effectively through labeling and window based algorithm by utilizing 2D adjacency based on scan line. Firstly, points adjacency is constructed through minimal search based on scan line. Connected component labeling algorithm is applied to classify raw ALS points into ground and non-ground by utilizing the adjacency structure. Then, some small objects are removed by morphology filtering, and isolated ground points are restored by IDW estimation. The experimental results shows that the method provides good filtering performance( about 97% accuracy) for diverse sites, and the overall processing takes less time than converting raw data into TIN or raster grid.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.294-305
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• 2012

The objective of this study is to estimate the chemical compositions and to identify qualitative sources of fall-out particles in study area. Also, this study used a spatial analysis to estimate spatial distributions and average deposition flux. In this study, the chemical compositions of fall-out particle samples collected at Muncheon lake from May 2010 to January 2011 were analyzed by ICP and IC. The monthly trend of deposition fluxes for fall-out particles showed highest in June ($107.61kg/km^2/day$) and lowest in October ($22.22kg/km^2/day$). The average fluxes of Fe, Si, Al, Zn and Ba are 0.44, 0.24, 0.20, 0.17, $0.09kg/km^2/day$, respectively. Also, the average fluxes of $NO_3^-$, $SO_4^{2-}$, $NH_4^+$, $Ca^{2+}$, and $Na^+$ are 6.48, 5.01, 4.96, 1.75, $1.37kg/km^2/day$, respectively. A Factor analysis identified four sources such as 1) nonferrous metal, motor vehicle, and agriculture, 2) soil, 3) field burning, incineration, and 4) road dust and oil burning. The IDW (inverse distance weighting) spatial analysis method was used to estimate spatial distribution and average deposition flux for fall-out particles. A total average deposition fluxes estimated in Muncheon lake were 936.15 kg/month. The spatial distribution trend of deposition flux showed higher at site 1 and 2 than at site 3, 4 because local road is adjacent to the site 1 and 2.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.5
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• pp.545-557
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• 2011

The objective of this study was to estimate the trends of each pollutant using the air pollution monitoring networks data from January 2005 to December 2008 in Daegu area. Also, the spatial characteristics of each pollutant were determined using the Pearson correlation coefficients and COD (coefficients of divergence). In this study, the trends of hourly, monthly, seasonal, and total average concentrations of each pollutant for the 10 sites were analyzed. The Ihyeon site showed highest concentration for the $SO_2$, $NO_2$, and PM10}. In the case of $O_3$, the Jisan site showed highest concentration among the other sites. Also, industrial area presented highest concentration for the $SO_2$, CO, and PM10. On the other hand, $NO_2$ showed highest in commercial area. The IDW (inverse distance weighting) method was used to estimate characteristics of spatial distribution. The results provide identify spatial distribution for each pollutant. Also, the Pearson correlation coefficients and COD values provide spatial variability among the monitoring sites. The COD of each pollutant showed very low values for all of the sites pairs. On the other hand, the Pearson correlation coefficients showed high values for all of the sites pairs. Finally, analysis of spatial variability can be used to characterize the spatial uniformity and similarity of concentrations from each pollutant.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.223-232
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• 2018

As the Seoul metropolitan city has the largest numbers of population and vehicles, the citizens can be exposed to hazardous air pollutants(HAPs) mainly from the vehicular exhaust and human activities. In this study, we proposed a systematic method for the selection of priority monitoring areas for HAPs using Geographic Information System (GIS). First, emission parameters(emission data, vehicle registration, monitoring data, and so on) and population parameters (population and population density) were plotted using the inverse distance weighted (IDW) interpolation. Then, the interpolation data for individual parameters, which were normalized between 1 and 5 points, were compiled for 270 grids with a resolution of $2km{\times}2km$. The total score of each grid was calculated using weights(1~5) for the individual parameters. The final ranking of each grid was assigned by four scenarios with varying fractions of the emission and population parameters from 50 : 50 to 80 : 20. Consequently, nine grids were suggested as priority monitoring areas, and all of them are located in the southwestern part of Seoul.

• Geomechanics and Engineering
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• v.7 no.6
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• pp.589-612
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• 2014

This study includes determination of liquefaction potential in Erzincan city center. Erzincan Province is situated within first-degree earthquake zone on earthquake map of Turkey. In this context, the earthquake scenarios were produced using the empirical expressions. Liquefaction potential for different earthquake magnitudes (6.0, 6.5, 7.0) were determined. Liquefaction potential was investigated using Standard Penetration Test (SPT). Liquefaction potential analyses are determined in two steps: geotechnical investigations and calculations. In the first steps, boreholes were drilled to obtain disturbed and undisturbed soil samples and SPT values were obtained. Laboratory tests were made to identify geotechnical properties of soil samples. In the second step, liquefaction potential analyses were examined using two methods, namely Seed and Idriss (1971), Iwasaki et al. (1981). The liquefaction potential broadly classified into three categories, namely non-liquefiable, marginally liquefiable and liquefiable regions. Additionally, the liquefaction potential index classified into four categories, namely non-liquefiable, low, high and very high liquefiable regions. In order to liquefaction analysis complete within a short time, MATLAB program were prepared. Following the analyses, liquefaction potential index is investigated by Iwasaki et al. (1982) methods. At the final stage of this study, liquefaction potential maps and liquefaction potential index maps of the all study area by using IDW (inverse distance weighted) interpolation method in Geostatistical Analyst Module of ArcGIS 10.0 Software were prepared for different earthquake magnitudes and different depths. The results of soil liquefaction potential were evaluated in ArcGIS to map the distributions of drillings with liquefaction potential. The maps showed that there is a spatial variability in the results obtained which made it difficult to clearly separate between regional areas of high or low potential to liquefy. However, this study indicates that the presence of ground water and sandy-silty soils increases the liquefaction potential with the seismic features of the region.

• Parasites, Hosts and Diseases
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• v.54 no.4
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• pp.439-446
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• 2016

Toxoplasmosis is a protozoan disease that is caused by Toxoplasma gondii in livestock and humans. Due to its medical and veterinary importance, it is essential to study the seroprevalence of T. gondii infection among humans and animals in various parts of the world. The major objective of this study was to determine the seroprevalence and spatial distribution of toxoplasmosis in small ruminants (sheep and goats) of north-eastern region, Pakistan. A total of 1,000 animals comprising of sheep (n=470) and goats (n=530) were examined for T. gondii infection by using ELISA. An epidemiological data was collected in the form of questionnaire. A surface has been generated by using method of interpolation in Arc GIS with the help of IDW (inverse distance weight). The results showed higher seroprevalence of T. gondii in goats (42.8%) as compared to sheep (26.2%). The seroprevalence was higher in females as compared to males in all examined ruminants. Similarly, there is a wide variation in the seroprevalence of T. gondii in different breeds of sheep and goats showing higher seroprevalence in Teddy (52.8%) and Damani breed (34.5%) of goat and sheep's, respectively. The geographical and spatial distribution of T. gondii shows that it is widely distributed in different parts of the north-eastern region of Pakistan. Our results suggest widespread environmental contamination with T. gondii oocysts and that small ruminants could be a potentially important source of T. gondii infection if their infected meat is consumed undercooked.