• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.293-296
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• 2008

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1279-1290
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• 2017

R's {shiny} package provides an environment for creating web applications with only R scripts. Shiny does not require knowledge of a separate web programming language and its development is very easy and straightforward. In addition, Shiny has a variety of extensibility, and its functions are expanding day by day. Therefore, the presentation of high-quality results is an excellent tool for R-based analysts. In this paper, we present actual cases of large data analysis using Shiny. First, geological anomaly zone is extracted by analyzing topographical data expressed in the form of contour lines by analysis related to spatial data. Next, we will construct a model to predict major diseases by 16 cities and provinces nationwide using weather, environment, and social media information. In this process, we want to show that Shiny is very effective for data visualization and analysis.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.52-52
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• 1995

The temporal and spatial distribution of atmospheric transmissivity and depletion rate of solar radiation are investigated, and are compared to the concentration of several components of air pollution. The length of the data span is 11 years from 1983 to 1993. The data of radiation and sunshine rate recorded at 20 meteorological standard stations were used, and in order to investigate a relationship between the depletion rate of solar radiation and air pollution, the concentration data of air pollution observed in Seoul, Pusan, Taegu, Taejon and Kwangju were compiled from 1991 to 1993. Regression coefficient a and b vary from 0.100 to 0.209, from 0.464 to 0.691, and their means are 0.163 and 0.533, respectively. Climatological atmospheric transmissivity is ranged from 0.68 to 0.83, and its mean is 0.75. Atmospheric transmissivity is relatively low in Pusan, Taejon, Kwangju and Inchon which have large population and are highly industrialized. However, that in Chinju, Mokpo, Cheju and Sosan appears to be large compared to the aforementioned stations. Insolation rate of clear days varies from 0.71 to 0.58, and its mean is 0.63. Insolation rate of Kangnung and Chinju are higher than those of Seoul and Pusan by 5%. From the correlation coefficients between depletion rate of solar radiation and air pollution concentration, the most significant factors related to the depletion rate of solar radiation is appeared to be TSP followed by $SO_2$. Ozone shows a negative correlation, End $NO_2$ does not show a obvious correlation with the depletion rate of solar radiation.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.437-446
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• 1995

The temporal and spatial distribution of atmospheric transmissivity and depletion rate of solar radiation are investigated, and are compared to the concentration of several components of air pollution. The length of the data span is 11 years from 1983 to 1993. The data of radiation and sunshine rate recorded at 20 meteorological standard stations were used, and in order to investigate a relationship between the depletion rate of solar radiation and air pollution, the concentration data of air pollution observed in Seoul, Pusan, Taegu, Taejon and Kwangju were compiled from 1991 to 1993. Regression coefficient a and b vary from 0.100 to 0.209, from 0.464 to 0.691, and their means are 0.163 and 0.533, respectively. Climatological atmospheric transmissivity is ranged from 0.68 to 0.83, and its mean is 0.75. Atmospheric transmissivity is relatively low in Pusan, Taejon, Kwangju and Inchon which have large population and are highly industrialized. However, that in Chinju, Mokpo, Cheju and Sosan appears to be large compared to the aforementioned stations. Insolation rate of clear days varies from 0.71 to 0.58, and its mean is 0.63. Insolation rate of Kangnung and Chinju are higher than those of Seoul and Pusan by 5%. From the correlation coefficients between depletion rate of solar radiation and air pollution concentration, the most significant factors related to the depletion rate of solar radiation is appeared to be TSP followed by $SO_2$. Ozone shows a negative correlation, End $NO_2$ does not show a obvious correlation with the depletion rate of solar radiation.

• Journal of Korean Society of Forest Science
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• v.106 no.2
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• pp.258-266
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• 2017

This study was conducted to develop a carbon storage distribution map of Pinus rigida stands in Muju-gun by using of the National Forest Inventory data and digital forest map. The relationships between the stand variables such as height, age, diameter at breast height (DBH), crown density and aboveground biomass of Pinus rigida were analyzed. The results showed that the crown density had the highest positive correlation with a value of 0.74 followed by the height variable with value of 0.61. The aboveground biomass regression models were developed to estimate biomass and carbon storage map. The results of this study showed that the average carbon storage was 58.2 ton C/ha while the total carbon stock of rigida pine forests in Muju area was estimated to be 430,963 C ton.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5669-5673
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• 2015

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan- Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.712-721
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• 2016

This study analyzes important urban characteristics according to location of large-scaled professional sports facilities based on a binary logistic regression model and t-test. For the empirical analysis, this study uses 24 urban characteristics within social, economic, cultural, traffic, and spatial categories in 228 cities. The results show that economic condition can be the main decision factor for the differential feature of the location as well as social and traffic conditions. Concretely, more the number of young adults and middle-aged people who have considerable purchasing power, and available land are more the beneficial to the presence of the sports facilities. Recently local governments focus on location of the facilities due to their impacts on regional economics as well as residents' quality of life. In this point of vies, this study gives good understanding why it is a great option for location of the facilities.

• Asian Journal of Atmospheric Environment
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• v.8 no.4
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• pp.202-211
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• 2014

In this study, long-term rainfall data with irregular spatial distribution in Seoul, Korea, were separated into individual precipitation events by the inter-event time definition of 6 hours. Precipitation washout of $PM_{10}$ and $NO_2$ concentrations in the air considering various complex factors were analyzed quantitatively. Concentrations of $PM_{10}$ and $NO_2$ in the atmosphere were lower under condition of rainfall compared to that of non-precipitation, and a noticeable difference in average $PM_{10}$ concentrations was observed. The reduction of concentrations of $PM_{10}$ and $NO_2$ by rainfall monitored at road-side air monitoring sites was also lower than that of urban air monitoring sites due to continuous pollutant emissions by transportation sources. Meanwhile, a relatively smaller reduction of average $PM_{10}$ concentration in the atmosphere was observed under conditions of light rainfall below 1 mm, presumably because the impact of pollutant emission was higher than that of precipitation scavenging effect, whereas an obvious reduction of pollutants was shown under conditions of rainfall greater than 1 mm. A log-shaped regression equation was most suitable for the expression of pollutant reduction by precipitation amount. In urban areas, a lower correlation between precipitation and reduction of $NO_2$ concentration was also observed due to the mobile emission effect.

• Journal of Cadastre & Land InformatiX
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• v.44 no.2
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• pp.231-242
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• 2014

On the Pre-Housing-Sale Systems there are many risks that developers might not fulfill the pre-sale obligations. In korea, in order to protect the people who bought houses from these risk, the Housing Sold Guarantee System was introduced and has been operated. Even though this system if there is accident in the pre-sale warranty business, several problems, such as damages caused to the people who bought the houses, occurs. Therefore, research is needed to Housing Sold Guarantee accident factor. But there are few study about it. This study attempted to analyze influencers on the possibility of the accident. We employ 3,026 data which Korea Housing Guarantee Co., Ltd manages and analyze them empirically, using business characteristics, housing market characteristics, and regional characteristics. Especially this study used to the binary logistic regression model. The results of analysis showed that the accident rate of Housing Sold Guarantee had been effected on the business type, house type, project financing guarantee, operator credit rating, housing market, and regional characteristics.