• Journal of The Geomorphological Association of Korea
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• v.18 no.1
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• pp.41-56
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• 2011

This study analyzes the change in land-cover based on satellite imagery to draw up land-cover map in the future, and estimates the change in land category using statistical data of the land category. To estimate land category, this study applied the double exponentially smoothing method. The result of the land cover classification according to year using satellite imagery showed that the type with the largest increase in area of land cover change in the cities of Cheonan and Asan was artificial structure, followed by water, grass field and bare land. However forest, paddy, marsh and dry field were reduced. Further, the result of the time-series analysis of the land category was found to be similar to the result of the land cover classification using satellite imagery. Especially, the result of the estimation of the land category change using the double exponentially smoothing method showed that paddy, dry field, forest and marsh are anticipated to consistently decrease in area from 2010 to 2100, whereas artificial structure, water, bare land and grass field are anticipated to consistently increase. Such results can be utilized as basic data to estimate the change in land cover according to climate change in order to prepare climate change response strategies.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.523-538
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• 2011

This study analyzes the changes in the surface area of each forest cover, based on temperature data analysis and satellite imagery as the basic methods for the impact assessment of climate change on regional units. Furthermore, future changes in the forest cover are predicted using the double exponential smoothing method. The results of the study have shown an overall increase in annual mean temperature in the studied region since 1990, and an especially increased rate in winter and autumn compared to other seasons. The multi-temporal analysis of the changes in the forest cover using satellite images showed a large decrease of coniferous forests, and a continual increase in deciduous forests and mixed forests. Such changes are attributed to the increase in annual mean temperature of the studied regions. The analysis of changes in the surface area of each forest cover using the statistical data displayed similar tendencies as that of the forest cover categorizing results from the satellite images. Accordingly, rapid changes in forest cover following the increase of temperature in the studied regions could be expected. The results of the study of the forest cover surface using the double exponential smoothing method predict a continual decrease in coniferous forests until 2050. On the contrary, deciduous forests and mixed forests are predicted to show continually increasing tendencies. Deciduous forests have been predicted to increase the most in the future. With these results, the data on forest cover can be usefully applied as the main index for climate change. Further qualitative results are expected to be deduced from these data in the future, compared to the analyses of the relationship between tree species of forest and climate factors.

• The Korean Journal of Applied Statistics
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• v.28 no.4
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• pp.663-683
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• 2015

The change of the population pyramid due to low fertility and rapid aging threatens the financial sustainability of National Health Insurance. We construct statistical models for prevalence rates and medical expenses using National Health Insurance Service (NHIS) sample cohort data from 2002-2013. We then project yearly expenditures and income of national health insurance until 2060 that considers various assumptions in regards to future population structure and economic conditions. We adopt a VECM-LC model for prevalence rates and the double exponentially smoothing method for the per capita co-payment of healthcare expense (in which the two models are institution-disease-sex-age specific) to project of national health insurance expenditures. We accommodate various assumptions of economic situations provided by the national assembly and government to produce a financial projection for national health insurance. Two assumptions of dependents ratios are used for the projection of national health insurance income to conduct two future population structures by the two assumptions of aging progresses and various assumptions on economic circumstances as in the expenditure projection. The health care deficit is projected to be 20-30 trillion won by 2030 and 40-70 trillion won by 2060 in 2015 constant price.