• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.556-559
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• 2007

The Urban Environmental Quality (UEQ) indicates a complex and various parameters resulting from both human and natural factors in an urban area. Vegetation, climate, air quality, and the urban infrastructure may interact to produce effects in an urban area. There are relationships among air pollution, vegetation, and degrading environmental the urban heat island (UHI) effect. This study investigates the application of multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air quality and UHI intensity in Seoul from 2000 to 2006 in fine resolution (30m) using the emissivity-fusion method. The Haze Optimized Transform (HOT) correction approach has been adopted for atmospheric correction on all bands except thermal band. The general UHI values (${\Delta}(T_{urban}-T_{rural})$) are 8.45 (2000), 9.14 (2001), 8.61 (2002), and $8.41^{\circ}C$ (2006), respectively. Although the UHI values are similar during these years, the spatial coverage of "hot" surface temperature (>$24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84(2002), and 0.89 (2006), respectively. Air quality is shown to be an important factor in the spatial variation of UEQ. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.26-28
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• 2008

Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.105-113
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• 2016

Fire radiative power(FRP), which means the power radiated from wildfire, is used to estimate fire emissions. Currently, the geostationary satellites of East Asia do not provide official FRP products yet, whereas the American and European geostationary satellites are providing near-real-time FRP products for Europe, Africa and America. This paper describes the first retrieval of Himawari-8 FRP using the mid-infrared radiance method and shows the comparisons with MODIS FRP for Sumatra, Indonesia. Land surface emissivity, an essential parameter for mid-infrared radiance method, was calculated using NDVI(normalized difference vegetation index) and FVC(fraction of vegetation coverage) according to land cover types. Also, the sensor coefficient for Himawari-8(a = 3.11) was derived through optimization experiments. The mean absolute percentage difference was about 20%, which can be interpreted as a favourable performance similar to the validation statistics of the American and European satellites. The retrieval accuracies of Himawari FRP were rarely influenced by land cover types or solar zenith angle, but parts of the pixels showed somewhat low accuracies according to the fire size and viewing zenith angle. This study will contribute to estimation of wildfire emissions and can be a reference for the FRP retrieval of current and forthcoming geostationary satellites in East Asia.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.189-194
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• 2008

Middle-infrared (MIR) spectral region between 3.0 and $5.0\;{\mu}m$ in wavelength is useful for observing high temperature events such as volcanic activities and forest fire. However, atmospheric effects and sun irradiance in day time has not been well studied for this MIR spectral band. The objectives of this basic study is to evaluate atmospheric effects and eventually to estimate surface temperature from a single channel MIR image, although a typical approach utilize split-window method using more than two channels. Several parameters are involved for the correction including various atmospheric data and sun-irradiance at the area of interest. To evaluate the effect of sun irradiance, MODIS MIR images acquired in day and night times were used for comparison. Atmospheric parameters were modeled by MODTRAN, and applied to a radiative transfer model for estimating the sea surface temperature. MODIS Sea Surface Temperature algorithm based upon multi-channel observation was performed in comparison with results from the radiative transfer model from a single channel. Temperature difference of the two methods was $0.89{\pm}0.54^{\circ}C$ and $1.25{\pm}0.41^{\circ}C$ from the day-time and night-time images, respectively. It is also shown that the emissivity effect has by more largely influenced on the estimated temperature than atmospheric effects. Although the test results encourage using a single channel MR observation, it must be noted that the results were obtained from water body not from land surface. Because emissivity greatly varies on land, it is very difficult to retrieval land surface temperature from a single channel MIR data.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.339-351
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• 2011

This study investigates the potentials of satellite, ground measurement data, and geo-spatial information within an urban area for the mapping of the Urban Environmental Quality (UEQ) parameters. The UEQ indicates a complex and various parameters resulting from both human and natural factors, which are greenness, climate, air pollution, the urban infrastructure, and etc. Multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air pollution by the Haze Optimized Transform (HOT) technique, Urban Heat Island (UHO using the emissivity-fusion method in Seoul from 2000 to 2006 in fine resolution (30m) were analyzed for the estimation of UEQ index. Although the UHI values are similar ($8.4^{\circ}C{\sim}9.1^{\circ}C$) during these years, the spatial coverage of "hot" surface temperature (> $24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84 (2002), and 0.89 (2006), respectively. It was found that the proposed method was successfully analyzed spatial structure of the UEQ and the scenarios of the best and worst areas within the city were also identified. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.435-452
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• 2016

Land Surface Temperature (LST) has been operationally retrieved from the Communication, Ocean, and Meteorological Satellite (COMS) data by the spilt-window method (CSW_v2.0) developed by Cho et al. (2015). Although the CSW_v2.0 retrieved the LST with a reasonable quality compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data, it showed a relatively poor performance for the strong inversion and lapse rate conditions. To solve this problem, the LST retrieval algorithm (CSW_v2.0) was updated using the simulation results of radiative transfer model (MODTRAN 4.0) by considering the diurnal variations of air temperature. In general, the upgraded version, CSW_v3.0 showed a similar correlation coefficient between the prescribed LSTs and retrieved LSTs (0.99), the relatively smaller bias (from -0.03 K to-0.012 K) and the Root Mean Square Error (RMSE) (from 1.39 K to 1.138 K). Particularly, CSW_v3.0 improved the systematic problems of CSW_v2.0 that were encountered when temperature differences between LST and air temperature are very large and/or small (inversion layers and superadiabatic lapse rates), and when the brightness temperature differences and surface emissivity differences were large. The bias and RMSE of CSW_v2.0 were reduced by 10-30% in CSW_v3.0. The indirect validation results using the MODIS LST data showed that CSW_3.0 improved the retrieval accuracy of LST in terms of bias (from -0.629 K to -0.049 K) and RMSE (from 2.537 K to 2.502 K) compared to the CSW_v2.0.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.219-219
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• 2011

순 장파복사량은 지표면으로 입사되는 하강 장파복사량(Downward Longwave Radiation, $R_{ld}$)과 지표면에서 반사되는 상승 장파복사량(Upward Longwave Radiation, $R_{lu}$)의 차이로 정의되는데 이는 에너지 수지 및 농업기상 연구의 중요한 주제 중 하나로서 다루어져 온 순복사량의 중요한 요소이다. 일반적으로 $R_{lu}$의 경우 지표면 온도와 방사율(emissivity)를 이용하여 산출되므로 정확히 추정이 가능하나, $R_{ld}$의 경우 대기 최상층에서 관측되는 방사량과 지표면 근처의 방사량을 함께 고려해야 하므로 실측이 어렵다. $R_{ld}$는 야간 복사계(pyrgeometer)를 이용하여 직접적으로 측정할 수 있지만 관측기기 자체가 구비되어있는 관측소가 적어 매우 드물게 이용된다. 또한 단파 복사 에너지 측정 기기에 비해 비용이 많이들고 종종 관측값이 큰 오차를 가지고 있기 때문에 실무에 적용하기 힘든 단점이 있다. 따라서 기상 관측소에서 얻어지는 증기압과 온도 관측치를 물리식, 경험식 등에 적용하여 산정하게 된다. 현재는 $R_{ld}$의 추정은 관측된 방사량간의 관계를 나타내는 경험식을 기반으로 지표면 근처의 대기 온도와 습도를 이용하여 산출하는 방법이 널리 사용되고 있다. 본 연구에서는 증발산 산정 알고리즘 개발의 시발점으로써 $R_{ld}$를 먼저 구하고 $R_{lu}$를 구하였다. 신뢰성 높은 방법을 이용하여 $R_{ld}$를 구하게 되면 정확도 높은 $R_N$을 구하는 데 기여할 수 있으며, 궁극적으로 보다 정확한 증발산을 산정할 수 있게 된다. $R_{ld}$는 일반적으로 clear sky 조건 하에서의 복사 에너지 플럭스($R_{ldc}$)를 구한 후 구름의 양에 따라 보정한다. 하강 장파복사량의 경우 널리 사용되는 공식 중 하나인 Brutsaert의 공식을 사용하였다. 광릉, 해남에 위치한 플럭스 타워지점에서 실측된 기온과 실제 수증기압을 입력인자로 사용하여 지점별 $R_{ldc}$를 먼저 구하고 Moderate Resolution Imaging Spectroradiometer(MODIS) 영상자료를 이용하여 검증한 뒤 최종적으로 남한지역을 대상으로 순 장파복사량 지도를 작성하였다. 이를 위해 MODIS 07 대기 프로파일 산출물(Atmospheric Profile Product)중 기온 및 이슬점온도를 추출하여 산정식의 입력자료로서 사용하였다. 상승 장파복사량의 경우 MODIS 11 지표면 온도 산출물(Land Surface Temperature product)를 이용하여 산정하였다. 이는 남한 지역의 증발산량 추정 및 에너지 수지 연구를 위한 중요한 기본 자료로서 유용하게 사용될 수 있으리라 사료된다.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1423-1444
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• 2022

In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.721-732
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• 2016

The accuracy and error characteristics of microwave Sea Surface Temperature (SST) measurements in the Northwest Pacific were analyzed by utilizing 162,264 collocated matchup data between GCOM-W1/AMSR2 data and oceanic in-situ temperature measurements from July 2012 to August 2016. The AMSR2 SST measurements had a Root-Mean-Square (RMS) error of about $0.63^{\circ}C$ and a bias error of about $0.05^{\circ}C$. The SST differences between AMSR2 and in-situ measurements were caused by various factors, such as wind speed, SST, distance from the coast, and the thermal front. The AMSR2 SST data showed an error due to the diurnal effect, which was much higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. In addition, the RMS error tended to be large in the winter because the emissivity of the sea surface was increased by high wind speeds and it could induce positive deviation in the SST retrieval. Low sensitivity at colder temperature and land contamination also affected an increase in the error of AMSR2 SST. An analysis of the effect of the thermal front on satellite SST error indicated that SST error increased as the magnitude of the spatial gradient of the SST increased and the distance from the front decreased. The purpose of this study was to provide a basis for further research applying microwave SST in the Northwest Pacific. In addition, the results suggested that analyzing the errors related to the environmental factors in the study area must precede any further analysis in order to obtain more accurate satellite SST measurements.