• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.653-662
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• 2011

Land surface temperature (LST) is a one of the key variables of land surface which can be estimated from geostationary meteorological satellite. In this study, we have developed the three sets of LST retrieval algorithm from MTSAT-2 data through the radiative transfer simulations under various atmospheric profiles (TIGR data), satellite zenith angle, spectral emissivity, and surface lapse rate conditions using MODTRAN 4. The three LST algorithms are daytime, nighttime and total LST algorithms. The weighting method based on the solar zenith angle is developed for the consistent retrieval of LST at the early morning and evening time. The spectral emissivity of two thermal infrared channels is estimated by using vegetation coverage method with land cover map and 15-day normalized vegetation index data. In general, the three LST algorithms well estimated the LST without regard to the satellite zenith angle, water vapour amount, and surface lapse rate. However, the daytime LST algorithm shows a large bias especially for the warm LST (> 300 K) at day time conditions. The night LST algorithm shows a relatively large error for the LST (260 ~ 280K) at the night time conditions. The sensitivity analysis showed that the performance of weighting method is clearly improved regardless of the impacting conditions although the improvements of the weighted LST compared to the total LST are quite different according to the atmospheric and surface lapse rate conditions. The validation results of daytime (nighttime) LST with MODIS LST showed that the correlation coefficients, bias and RMSE are about 0.62~0.93 (0.44~0.83), -1.47~1.53 (-1.80~0.17), and 2.25~4.77 (2.15~4.27), respectively. However, the performance of daytime/nighttime LST algorithms is slightly degraded compared to that of the total LST algorithm.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.37-46
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• 2016

This study is to estimate COMS (Communication, Ocean and Meteorological Satellite) daily land surface temperature (LST) of Korea Peninsula from 15 minutes interval COMS LST (COMS LST-15) satellite data. Using daily observed LST data of Automated Agriculture Observing System (AAOS) 11 stations from January 2013 to May 2015, the COMS daily LST was compared and validated. For the representative time for daily mean LST value from COMS LST-15, the time of 23 : 45 and 0:00 showed minimum deviations with AAOS daily LST. The time zone from 23 : 45 to 1:15 and from 7 : 30 to 9 : 45 showed high determination coefficient (R2) of 0.88 and 0.90 respectively. The daily COMS LST by averaging COMS LST-15 of the day showed R2 of 0.83. From the 5 cases of results, the COMS daily LST could be extracted from the average LST by using 15 minutes data from 7 : 30 to 9 : 45.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.507-515
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• 2009

Land surface temperature (LST) is a key environmental variable in a wide range of applications, such as weather, climate, hydrology, and ecology. However, LST is one of the most difficult surface variables to observe regularly due to the strong spatio-temporal variations. So, we have developed the LST retrieval algorithm from COMS (Communication, Ocean and Meteorological Satellite) data through the radiative transfer simulations under various atmospheric profiles (TIGR data), satellite zenith angle (SZA), spectral emissivity, and surface lapse rate conditions using MODTRAN 4. However, the LST retrieval algorithm has a tendency to overestimate and underestimate the LST for surface inversion and superadiabatic conditions, respectively. To minimize the overestimation and underestimation of LST, we also developed day/night LST algorithms separately based on the surface lapse rate (local time) and recalculated the final LST by using the weighted sum of day/night LST. The analysis results showed that the quality of weighted LST of day/night algorithms is greatly improved compared to that of LST estimated by original algorithm regardless of the surface lapse rate, spectral emissivity difference (${\Delta}{\varepsilon}$) SZA, and atmospheric conditions. In general, the improvements are greatest when the surface lapse rate and ${\Delta}{\varepsilon}$ are negatively large (strong inversion conditions and less vegetated surface).

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.23-23
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• 2018

본 연구에서는 다중분위회귀분석모형(Multiple Quantile Regression Model, MQRM)과 MODIS(MODerate resolution Imaging Spectroradiometer) LST (Land Surface Temperature) 자료를 이용하여 전국 공간토양수분을 산정하였다. 공간토양수분을 산정하기 위한 과정은 크게 두가지로 구분된다. 첫 번째로 기존의 MODIS LST 자료를 조건부 합성 보정기법을 적용하여 실측 LST 자료와 비교하여 위성 LST 자료가 갖고 있는 오차를 보정하였다. 그 결과, 조건부 합성 보정기법을 적용하기전 전국 71개 지상관측지점에서 관측한 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.70으로 어는정도 유의성 있는 상관관계를 나타냈으나 조건부 합성 보정기법을 적용한 후 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.92로 상당히 크게 향상됨을 알 수 있었다. 두 번째로 보정된 MODIS LST를 이용하여 다중분위회귀분석 모형을 개발하고 토양수분을 예측하는 단계로 입력자료로 위성영상 자료와 관측자료를 융합하여 사용하였다. 위성영상 자료로는 보정된 MODIS LST와 MODIS NDV를 구축하였고 일단위 강수량 및 일조시간의 기상자료는 기상청으로부터 전국 71개 지점에 대해 구축하여 IDW 공간보간기법을 이용한 공간자료로 구축하였다. 토양수분 결과를 비교하기 위한 관측 토양수분은 자동농업기상관측(Automated Agriculture Observing System, AAOS)지점에서 2013년 1월부터 2015년 12월까지의 실측 일단위 토양수분 자료를 구축하여 사용하였다. 다중분위회귀분석 모형은 LST 인자를 중심으로 각각의 분위(0.05, 0.25, 0.5, 0.75, 0.95)에 해당되는 값의 회귀식을 NDVI, 강수 입력자료를 독립인자로서 조합하여 계절 및 토성에 따른 총 80개의 회귀식을 산정하였다. 관측 토양수분과 모의 토양수분을 비교한 결과 $R^2$가 0.70 (철원), 0.90 (춘천), 0.85 (수원), 0.65 (서산), 0.78 (청주), 0.82 (전주), 0.62 (순천), 0.63 (진주), 0.78 (보성)로 높은 상관성을 보였다. 본 연구에서는 다중분위회귀 모형의 성능을 검증하기 위해 기존의 다중선형회귀모형의 결과와 비교하여 크게 개선됨을 나타냈다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.103-104
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• 2017

본 연구에서는 다중회귀분석모형(MLRM)과 MODIS (MODerate resolution Imaging Spectroradiometer) LST (Land Surface Temperature) 자료를 이용하여 전국 공간토양수분을 산정하였다. 공간토양수분을 산정하기 위한 과정은 크게 두가지로 구분된다. 첫 번째로 기존의 MODIS LST 자료를 조건부 합성 보정기법을 적용하여 실측 LST 자료와 비교하여 위성 LST 자료가 갖고 있는 오차를 보정하였다. 그 결과, 조건부 합성 보정기법을 적용하기전 전국 71개 지상 관측지점에서 관측한 실측 LST와 MODIS LST의 R2는 전체 평균 0.70으로 어는정도 유의성 있는 상관관계를 나타냈으나 조건부 합성 보정기법을 적용한 후 실측 LST와 MODIS LST의 R2는 전체 평균 0.92로 상당히 크게 향상됨을 알 수 있었다. 두 번째로 보정된 MODIS LST를 이용하여 다중회귀분석 모형을 개발하고 토양수분을 예측하는 단계로 입력자료로 위성영상 자료와 관측자료를 융합하여 사용하였다. 위성영상 자료로는 보정된 MODIS LST와 MODIS NDV를 구축하였고 일단위 강수량 및 일조시간의 기상자료는 기상청으로부터 전국 68개 지점에 대해 구축하여 IDW 공간보간기법을 이용한 공간자료로 구축하였다. 토양수분 결과를 비교하기 위한 관측 토양수분은 자동농업기상관측(Automated Agriculture Observing System, AAOS)지점에서 2013년 1월부터 2015년 12월까지의 실측 일단위 토양수분 자료를 구축하여 사용하였다. 다중회귀분석 모형은 각각의 입력자료를 독립인자로서 조합하여 12개의 시나리오를 만들었다. 시공간적 경향을 고려하기 위하여 계절별, 토양 토성(soil texture)를 구분하여 회귀분석을 실시하였다. 관측 토양수분과 모의 토양수분을 비교한 결과 $R^2$가 0.80 (철원), 0.90 (춘천), 0.80 (수원), 0.63 (서산), 0.77 (청주), 0.82 (전주), 0.52 (순천), 0.63 (진주), 0.99 (보성)로 높은 상관성을 보였다. 본 연구에서는 토양수분을 예측하기 위한 인자 중 가장 민간함 LST를 보정하지 않는 토양수분 예측 방법은 상당한 오차를 포함하게 되어 실측 토양수분 결과와 크게 차이가 나타남을 보여주었다.

• Journal of Korean Academy of Nursing
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• v.49 no.3
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• pp.329-339
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• 2019

Purpose: The purpose of this study was to investigate the frequency, patterns, and factors of reversals in decisions about life-sustaining treatment (LST) among older patients with terminal-stage chronic cardiopulmonary disease. Methods: This was a retrospective correlational descriptive study based on medical chart review. De-identified patient electronic medical record data were collected from 124 deceased older patients with terminal-stage cardiopulmonary disease who had made reversals of LST decisions in an academic tertiary hospital in 2015. Data were extracted about the reversed LST decisions, LST treatments applied before death, and patients' demographic and clinical factors. Multivariate logistic regression analysis was used to identify the factors associated with the reversal to higher intensity of LST treatment. Results: The use of inotropic agents was the most frequently reversed LST treatment, followed by cardiopulmonary resuscitation, intubation, ventilator therapy, and hemodialysis. Inconsistency between the last LST decisions and actual treatments occurred most often in hemodialysis. One-third of the reversals in LST decisions were made toward higher intensity of LST treatment. Patients who had lung diseases (vs. heart diseases); were single, divorced, or bereaved (vs. married); and had an acquaintance as a primary decision maker (vs. the patients themselves) were significantly more likely to reverse the LST decisions to higher intensity of LST treatment. Conclusion: This study demonstrated the complex and turmoil situation of the LST decision-making process among older patients with terminal-stage cardiopulmonary disease and suggests the importance of support for patients and families in their LST decision-making process.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.197-214
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• 2019

In this study, the correlation analysis was conducted between observed air temperature (maximum, minimum, and mean air temperature) and the daytime and nighttime data of Terra/Aqua MODIS LST(Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) for 86 weather stations. All the data of the recent 11 years from 2008 to 2018 were prepared with daily base. In particular, the characteristics of the cold and heat waves incidence period in 2018 were analyzed. The correlation analysis was performed using the Pearson correlation coefficient(R) and root mean square error(RMSE). As a result of time series analysis, the trend between observed air temperature and MODIS LST were similar, showing the correlation above 0.9 in maximum temperature, above 0.8 in mean and minimum temperature. Especially, the maximum temperature was found to have the highest accuracy with Terra MODIS LST daytime, and the minimum temperature had the highest correlation with Terra MODIS LST nighttime. During the cold wave period, both Terra and Aqua MODIS LST showed higher correlations with nighttime data than daytime data. For the heat wave period, the Aqua MODIS LST daytime data was good, but the overall R was below 0.5. Additional analysis is necessary for further study considering such as land cover and elevation characteristics.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.87-95
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• 2012

Land surface temperature (LST) is an important factor in human health, thermal environment, heat balance, global change studies, and as control for climate change. The objective of this study was to assess the influence of Urban Heat Island (UHI) Effects on the LST and NDVI in Cheongju, Korea. The aim was to evaluate the effect of urban thermal environment for LST comparison of satellite-derived and in situ measured temperature. In this study, LANDSAT TM and KOMPSAT scene were used. The results indicated that the minimum LST is observed over dense forest as about $21{\sim}25^{\circ}C$ and maximum LST is observed over industrial area of about $28{\sim}32^{\circ}C$. The estimated LST showed that industrial area, bare soils and built-up areas exhibit higher surface temperatures, while forest, water bodies, agricultural croplands, and dense vegetations have lower surface temperatures during the summer daytime. Result corroborates the fact that LST over land use/land cover (LULC) types are greatly influenced by the amount of vegetation and water bodies present. The LST of industrial area and urban center is higher than that of suburban area, so it is clearly proved that there are obvious UHIE in Cheongju.

• Korean Journal of Adult Nursing
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• v.29 no.2
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• pp.131-142
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• 2017

Purpose: The aims of the study were to investigate relationships among intensive care unit (ICU) nurses' attitude, role perception, and nursing stress related to life sustaining treatment (LST), and secondly, to identify factors influencing nursing stress about LST. Methods: Participants were 202 conveniently sampled ICU nurses from general hospitals in Korea with over 300 beds. From December 1, 2015 to January 31, 2016, data were collected using structured questionnaires. The questionnaire was designed to measure nursing stress related to LST. Content validity and reliability was established for the instrument. Results: Relationships were found between attitude and role perception, and between role perception and nursing stress about LST. Participants' role perception, gender, education level, and the experience of dealing with family members of patients receiving LST accounted for 13% of variance in nursing stress about LST. Conclusion: Results confirmed that ICU nurses' role perception affects nursing stress about LST. Accordingly, the nursing education programs related to LST should aim to enhance role perception of nurses, and strategies to reduce the nursing stress about LST of the nurses in ICU need to be further developed.