• Journal of Yeungnam Medical Science
• /
• v.36 no.3
• /
• pp.241-248
• /
• 2019

Background: Heatstroke is one of the most serious heat-related illnesses. However, establishing public policies to prevent heatstroke remains a challenge. This study aimed to investigate the most relevant climate elements and their warning criteria to prevent outdoor heatstroke (OHS). Methods: We investigated heatstroke patients from five major hospitals in Daegu metropolitan city, Korea, from June 1 to August 31, 2011 to 2016. We also collected the corresponding regional climate data from Korea Meteorological Administration. We analyzed the relationship between the climate elements and OHS occurrence by logistic regression. Results: Of 70 patients who had heatstroke, 45 (64.3%) experienced it while outdoors. Considering all climate elements, only mean heat index (MHI) was related with OHS occurrence (p=0.019). Therefore, the higher the MHI, the higher the risk for OHS (adjusted odds ratio, 1.824; 95% confidence interval, 1.102-3.017). The most suitable cutoff point for MHI by Youden's index was $30.0^{\circ}C$ (sensitivity, 77.4%; specificity, 73.7%). Conclusion: Among the climate elements, MHI was significantly associated with OHS occurrence. The optimal MHI cutoff point for OHS prevention was $30.0^{\circ}C$.

• Korean Journal of Remote Sensing
• /
• v.28 no.1
• /
• pp.159-169
• /
• 2012

The purpose of this study was to assess the vulnerability of forest ecosystem to climate change in South Korea using socio-environmental indicators and the results of two vegetation models named as Hydrological and Thermal Analogy Group(HyTAG), and MAPSS-Century 1(MC1). The changing frequency and direction of biome types estimated by HyTAG model was used for quantifying sensitivity and adaptive capacity of forest distribution. Similarly, the variation and changing tendency of net primary production and soil carbon storage estimated by MC1 model was used for quantifying sensitivity and adaptive capacity of forest function. As socio-environmental indicators, many statistical data such as financial autonomy rate and the number of forestry officer was prepared. All indicators were standardized, and then calculated using the vulnerability assessment equation. The period of vulnerability assessment was divided into the past(1971-2000) and the future(2021-2050). To understand what policy has a priority to climate change, distribution maps of each indicators was depicted and the vulnerability results were compared among administrative districts. Evident differences could be found in entire study area. These differences were mostly derived from regionalspecific adaptive capacity. The result and methodology of this study would be helpful for the development of decision-making supporting system and policy making in forest management with respect to climate change.

• Journal of Climate Change Research
• /
• v.4 no.1
• /
• pp.1-10
• /
• 2013

This study has purpose to minimize the impact of climate change of Siheung. Vulnerability assessment was carried out for establishing the Siheung Climate Change Master Plan. Climate change vulnerability assessment analyzed using climate exposure, sensitivity and adaptive capacity indicators. A proxy variable is selected from each indicator. Meteorological data uses the RCP scenarios provided by the Meteorological Administration, and this study assumes that the same trend will continues in the future. Siheung are vulnerable to heavy rains in the flooded roads and farmland. Also, it is necessary to be careful heat wave in summer. The size and scale of the damage depends on the city's ability to respond to the impacts of climate change. It is necessary to make a adaptation plan for climate change impact assessment and vulnerability analysis. This study will be used to make Siheung Climate Change Master Plan and to determine the priority of the policy as guideline. It is expected that this study is helpful to pursue climate change vulnerability assessment of other local governments.

• Journal of Environmental Science International
• /
• v.25 no.1
• /
• pp.67-83
• /
• 2016

In order to improve the prediction of the regional air quality modeling in the Seoul metropolitan area, a sensitivity analysis using two PBL and microphysics (MP) options of the WRF model was performed during four seasons. The results from four sets of the simulation experiments (EXPs) showed that meteorological variables (especially wind field) were highly sensitive to the choice of PBL options (YSU or MYJ) and no significant differences were found depending on MP options (WDM6 or Morrison) regardless of specific time periods, i.e. day and night, during four seasons. Consequently, the EXPs being composed of YSU PBL option were identified to produce better results for meteorological elements (especially wind field) regardless of seasons. On the other hand, the accuracy of all simulations for summer and winter was somewhat lower than those for spring and autumn and the effect according to physics options was highly volatile by geographical characteristics of the observation site.

• Journal of Environmental Science International
• /
• v.17 no.10
• /
• pp.1183-1193
• /
• 2008

Today, environmental pollution and destruction due to the industrialization of our modem society have been the global issues. Although now we can lead affluent lives through science technologies and economic development, these environmental problems have resulted in striking the harmonious balance between human beings and nature and threatened human lives with abnormal weather caused by the global warming, destruction of the ozone layer, and El Nino phenomenon, acid rain, decrease in species diversity, movement of hazardous materials, and harmful waste increase. We are aware of the importance of environmental education, but in reality, it seems impossible to implement appropriate environmental education on account of our educational climate which exclusively focuses on the entrance examination. However, environmental education is the most ultimate solution for those problems in that only when students understand our environment fully and grow habits to protect it through environmental education, the present environmental problems can be solved and more serious problems that can be resulted in the future can possibly be prevented. Thus, this study has examined the effect of using image media in the environment subject on students' environmental sensitivity. According to the results, it was shown that it had positive effects on 'sensitivity of environment', 'attitudes towards environment', and 'environmental affinitive behaviors'.

• Korean Journal of Remote Sensing
• /
• v.29 no.6
• /
• pp.589-593
• /
• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.

• Spatial Information Research
• /
• v.19 no.3
• /
• pp.1-9
• /
• 2011

The vulnerability of ocean should be assessed to establish the climate change adaptation policy in field of the ocean, which has big effect on human and natural system. In this study, the criteria for assessing vulnerability of ocean to climate change were employed in terms of sensitivity, adaptative capacity and exposure. And suitable indicators for the criteria were selected and spatial data set for the indicators was prepared. In the ocean sector, the data for indicators were divided into two types, such as the inland and ocean data. The inland data were extrapolated and integrated to the coordinate of ocean data for the vulnerability assessment to climate change. As a result, the spatially diverse distribution of vulnerability on the ocean could be derived from the integration of two types of data. The results showed that southwestern ocean is much more sensitive than west and east ocean. Also southwestern ocean of exposure ratio of change is higher than the other part of ocean. On the other hand the adaptative capacity found that the highest in east ocean. The vulnerability assessment result showed southwestern ocean is more vulnerable than the other part of ocean.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_3
• /
• pp.1951-1963
• /
• 2021

Remote sensing data using earth observation satellites in agricultural environment monitoring has many advantages over other methods in terms of time, space, and efficiency. Since the sensor mounted on the satellite measures the energy that sunlight is reflected back to the ground, noise is generated in the process of being scattered, absorbed, and reflected by the Earth's atmosphere. Therefore, in order to accurately measure the energy reflected on the ground (radiance), atmospheric correction, which must remove noise caused by the effect of the atmosphere, should be preceded. In this study, atmospheric correction sensitivity analysis, inter-satellite cross-analysis, and comparative analysis with ground observation data were performed to evaluate the application of KOMPSAT-3 satellite's atmospheric correction for agricultural application. As a result, in all cases, the surface reflectance after atmospheric correction showed a higher mutual agreement than the TOA reflectance before atmospheric correction, and it is possible to produce the time series vegetation index of the same standard. However, additional research is needed for quantitative analysis of the sensitivity of atmospheric input parameters and the tilt angle.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1231-1244
• /
• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.

• Journal of Korea Water Resources Association
• /
• v.42 no.11
• /
• pp.921-931
• /
• 2009

For the assessment of climate change impacts for the Byeongseong stream, CGCM 3.1 T63 is selected as future climate information. The projections come from CGCM used to simulate the GHG emission scenario known as A2. Air temperature and precipitation information from the GCM simulations are converted to regional scale data using the statistical downscaling method known as MSPG. Downscaled climate data from GCM are then used as the input data for the SWAT model to generate regional runoff and water quality estimates in the Byeongseong stream. As a result of simple sensitivity analysis, the increase of CO2 concentration leads to increase water yield through reduction of evapotranspiration and increase of soil water. Hydrologic responses to climate change are in phase with precipitation change. Climate change is expected to reduce water yields in the period of 2021-2030. In the period of 2051-2060, stream flow is expected to be reduced in spring season and increased in summer season. While soil losses are also in phase with water yields, nutrient discharges (i.e., total nitrogen) are not always in phase with precipitation change. However, it should be noted that there are a lot of uncertainties in such multiple-step analysis used to convert climate information from GCM-based future climate projections into hydrologic information.