Understanding the trade-off effect in ecosystem services and measuring the interrelationships between services are crucial for managing limited environmental resources. Accordingly, in this study, we identified the dominant trends and increases and decreases in ecosystem services derived from changes in land cover over about 30 years and tracked changes in the relationships between ecosystem services that occurred over time. Through it, we determined the relationship between land cover changes and ecosystem service changes, as well as the distinct characteristics of service changes in different areas. The research primarily utilized the InVEST model, an ecosystem service assessment model. After standardizing the evaluation results between 0 and 1, it went through principal component analysis, a dimensionality reduction technique, to observe the time-series changes and understand the relationships between the services. According to the research results, the area of urbanized regions dramatically increased between 1989 and 2019, while forests showed a significant increase between 2009 and 2019. Between 1989 and 2019, the national ecosystem service supply witnessed a 13.9% decrease in water supply, a 10.5% decrease in nitrogen retention, a 2.6% increase in phosphorus retention, a 0.9% decrease in carbon storage, a 1.2% increase in air purification, and a 3.4% decrease in habitat quality. Over the past 30 years, South Korea experienced an increase in urbanized areas, a decrease in agricultural land, and an increase in forests, resulting in a trade-off effect between phosphorus retention and habitat quality. This study concluded that South Korea's environment management policies contribute to improving ecosystem quality, which has declined due to urbanization, and maximizing ecosystem services. These findings can help policymakers establish and implement forestry policies focusing on sustainable environmental conservation and ecosystem service provision.
Waterbody change detection using satellite images has recently been carried out in various regions in South Korea, utilizing multiple types of sensors. This study utilizes optical satellite images from Landsat and Sentinel-2 based on Google Earth Engine (GEE) to analyze long-term surface water area changes in four monitored small and medium-sized water supply dams and agricultural reservoirs in South Korea. The analysis covers 19 years for the water supply dams and 27 years for the agricultural reservoirs. By employing image analysis methods such as normalized difference water index, Canny Edge Detection, and Otsu'sthresholding for waterbody detection, the study reliably extracted water surface areas, allowing for clear annual changes in waterbodies to be observed. When comparing the time series data of surface water areas derived from satellite images to actual measured water levels, a high correlation coefficient above 0.8 was found for the water supply dams. However, the agricultural reservoirs showed a lower correlation, between 0.5 and 0.7, attributed to the characteristics of agricultural reservoir management and the inadequacy of comparative data rather than the satellite image analysis itself. The analysis also revealed several inconsistencies in the results for smaller reservoirs, indicating the need for further studies on these reservoirs. The changes in surface water area, calculated using GEE, provide valuable spatial information on waterbody changes across the entire watershed, which cannot be identified solely by measuring water levels. This highlights the usefulness of efficiently processing extensive long-term satellite imagery data. Based on these findings, it is expected that future research could apply this method to a larger number of dam reservoirs with varying sizes,shapes, and monitoring statuses, potentially yielding additional insights into different reservoir groups.
Because of a significant improvement in the economic situation and development of scientific techniques in Korea during the last 30 years, the life expectancy of the Korean people has lengthened considerably and as a result, the number of the elderly has markedly increased. Such an increase of the number of aged population brought about many social, economic, and medical problems which were never seriously considered before. This study was conducted to assess the trend of medical care utilization and medical expenditure of the elderly. The data of each patient in the study were taken from computer database maintained for administrative purpose by the Korea Medical Insurance Corporation. The study population was 132,670 who were 60 years old or more and registered in Korean Medical Insurance Corporation from 1989 to 1993. The study subjects were predominantly female(56.3%) and 10,000-20,000 Won premium group(50.6%). The following are summaries of findings : The total increase of the number of inpatient cases was 40.5% from 1989 through 1993. The average annual increase was 3.7% in inpatient medical expenditures per case, 4.4% in inpatient medical expenditures per day and 0.08% in length of stay per case from 1989 through 1993. Cataract was the most prevalent disease of 10 leading frequent diseases in all ages from 1989 through 1993. The case mix in 1993 compared to 1989 revealed that cataract and ischemic cerebral disease were increased whereas essential hypertension and pulmonary tuberculosis were decreased . The average annual increase of medical expenditures was 3.8% in general hospitals, 6.3% in hospitals and 2.4% in clinics. From 1989 through 1993, medical expenditures used by high-cost patients accounted for about 14% to 20% of all expenditures for inpatient care, while they represented less than 2.5% of the elderly population. Time series analysis revealed that total medical expenditures and doctor's fee for inpatient will be progressively increased whereas drug expenditures for inpatient will be decreased. And there will be no change in length of stay. Based on the above results, the factors increasing medical cost and utilization should be identified and the method of cost containment for the elderly health care should be developed systematically.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
/
v.10
no.1
/
pp.100-112
/
2005
Soil temperature was measured from the surface to 40 cm depth at three stations with different heights in tidal flat of Gomso Bay, west coast of Korea, for one month in every season 2004 to examine the thermal structure and the variation. Mean temperature in surface layer was higher in summer and lower in winter than in lower layer, reflecting the seasonal variation of vertically propagating structure of temperature by heating and cooling from the tidal flat surface. Standard deviation of temperature decreased from the surface to lower layer. Periodic variations of solar radiation energy and tide mainly caused short term variation of soil temperature, which was also intermittently influenced by precipitation and wind. Time series analysis showed the power spectral energy peaks at the periods of 24, 12 and 8 hours, and the strongest peak appeared at 24 hour period. These peaks can be interpreted as temperature waves forced by variations of solar radiation, diurnal tide and interaction of both variations, respectively. EOF analysis showed that the first and the second modes resolved 96% of variation of vertical temperature structure. The first mode was interpreted as the heating antl cooling from tidal flat surface and the second mode as the effect of phase lag produced by temperature wave propagation in the soil. The phase of heat transfer by 24 hour period wave, analyzed by cross spectrum, showed that mean phase difference of the temperature wave increased almost linearly with the soil depth. The time lags by the phase difference from surface to 10, 20 and 40cm were 3.2,6.5 and 9.8 hours, respectively. Vertical thermal diffusivity of temperature wave of 24 hour period was estimated using one dimensional thermal diffusion model. Average diffusivity over the soil depths and seasons resulted in $0.70{\times}10^{-6}m^2/s$ at the middle station and $0.57{\times}10^{-6}m^2/s$ at the lowest station. The depth-averaged diffusivity was large in spring and small in summer and the seasonal mean diffusivity vertically increased from 2 cm to 10 cm and decreased from 10 cm to 40 cm. Thermal propagation speeds were estimated by $8.75{\times}10^{-4}cm/s,\;3.8{\times}10{-4}cm/s,\;and\;1.7{\times}10^{-4}cm/s$ from 2 cm to 10 cm, 20 cm and 40 cm, respectively, indicating the speed reduction with depth increasing from the surface.
To investigate the relationships between ocean environmental characteristics, the time-series data of temperature and salinity observed at a station near at Hanlim set net in 1995 and 1996 are analyzed, and the results are as follow ; 1. In hanlim set net, the diurnal range of temperature and salinity variation in summer is very large and the amplitude of short-period fluctuation of temperature and salinity is very large. That is, not only the water of the middle and bottom layers (low temperature and high salinity) but also the coalstal water (high temperature and low salinity) appears alternatively depending on the current direction 2. from the result of mooring for 22 days in Hanlim set net, the mean speed and direction of tidal current in neap tide were 9.1 cm/sec and south westward in ebb time, and 11.6 cm/sec and north or northeastward in flood time, respectively. The highest speed of the current was 15cm/sec in ebb time, and 22.6 cm/sec in flood time. The mean speed and direction of tidal current in spring tide were 10.4 cm/sec, and southwestward in ebb time, and 12.3 cm/sec, and north or northestward in flood time, respectively. The highest speed of the current was 19.4 cm/sec in ebb time, and 20 cm/sec in flood time respectively. The mean speed of the current in flood time was larger than that in ebb time. The velocity vector along the major axis of semidiurnal tide ($M_2$) component was 1.5 times larger than that of diurnal tide ($K_1$), The major directions of two compornants were northwestward and east-southeastward and residiual current were 3.25 cm/sec and northwestward-directed. Result of TGPS Buoy tracer for 3 days between Biyang-Do and Chgui-Do showed that the mean speed was 1.6 knot in ebb time and 1.3 knot in flood time. Direction of tidal was southwestward in ebb time and northeastward in flood time respectively. The maximum current speed was 4.8 knot in ebb time and 3.7 knot in flood time respectively. The mean speed and direction of tidal in of offshore were 1.7 knot and northwestward in flood time. The residual current appeared 0.3 knot northeastward.
The Early Proterozoic reworked rock association occurs within the Preacmbrian high grade metamorphic rocks in the area of Daqingshan, Inner Molgolia. In this association, the various large scale ductile deformation belts, form a nappe structure where the foliation steeply dips to north and the lineation ($340^{circ}-30^{\circ}$) plunges at $45^{\circ}55^{\circ}$. This result indicates the subduction/extension with northern part thrusting over the southern part at high angle. The southern subducted microlithon has the characteristics of prograde metamorphism. The northern thrusted microlithon shows the evidence of retrograde metamorphism with decreasing pressure and increasing temperature. The main rock types of Early Proterozoic Moyites are biotite adamellite and syenogranites occurring in the form of small batholiths or stocks and alkali-feldspar granites in veins. The biotite adamellites are progressively contacted with the Archean and Early Proterozoic rocks and contain a great deal of enclaves of metamorphosed rocks, suggesting an anatexis origin. The geochemical characteristics of moyites show the typical features of anatexis granite. At middle to late Early Proterozoic time, the continent-continent collision formed the large scale thrusting and imbrication of Archean basement rocks. According to the mineral assemblage and thermobarometer of Paria et al. (1988) give the following P-T condition : up-faulted block; $700-710^{\circ}C$, 0.72-0.78 Gpa (early stage) and $600^{\circ}C$, 0.44 Gpa (late stage), footwall block; $620^{\circ}C$, 0.8 Gpa (early stage), $620-840^{\circ}C$, 0.64-0.45 Gpa (peak) and $620-630^{\circ}C$, 0.35Gpa (late stage). These results suggest a clockwise P-T-t path (jin et al., 1991, 1994). According to the depth-temperature model in the comperature subduction zone and the experimental data of Wyllie et al. (1983), we propose a tectonic-magmatic-thermal model to account for metamorphism-anatexis of moyite occurring in subduction-shear zone.
Journal of Korean Society of Coastal and Ocean Engineers
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v.31
no.5
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pp.265-277
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2019
Using the measured data of waves and shore-line, we reviewed the grand circulation process and seasonal variation of beach cusp at the Mang-Bang beach from the perspective of trapped mode Edge waves known as the driving mechanism of beach cusp. In order to track the temporal and spatial variation trends of beach cusp, we quantify the beach cusp in terms of its wave length and amplitude detected by threshold crossing method. In doing so, we also utilize the spectral analysis method and its associated spectral mean sand wave number. From repeated period of convergence and ensuing splitting of sand waves detected from the yearly time series of spectral mean sand wave number of beach cusp, it is shown that the grand circulation process of beach cusp at Mang-Bang beach are occurring twice from 2017. 4. 26 to 2018. 4. 20. For the case of beach area, it increased by $14,142m^2$ during this period, and the shore-line advanced by 18 m at the northen and southern parts of the Mang-Bang beach whereas the shore-line advanced by 2.4 m at the central parts of Mang-Bang beach. It is also worthy of note that the beach area rapidly increased by $30,345m^2$ from 2017.11.26. to 2017.12.22. which can be attributed to the nature of coming waves. During this period, mild swells of long period were prevailing, and their angle of attack were next to zero. These characteristics of waves imply that the main transport mode of sediment would be the cross-shore. Considering the facts that self-healing capacity of natural beaches is realized via the cross-shore sediment once temporarily eroded. it can be easily deduced that the sediment carried by the boundary layer streaming toward the shore under mild swells which normally incident toward the Mang-Bang beach makes the beach area rapidly increase from 2017.11.26. to 2017.12.22.
Journal of the Korean Association of Geographic Information Studies
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v.13
no.4
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pp.111-124
/
2010
To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.
Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.
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