• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.153-164
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• 2005

The paper presents time and cost effective remote sensing technology to estimate recharge potential of fresh water shallow aquifers for their sustainable management in arid ecosystem. Precipitation measurement of Raudatain Basin in Kuwait from TRMM data has been made and integrated with geological, geomorphological and hyrological data, to estimate the recharge potential of the basin. The total potential recharge to the area is estimated as 333.964 MCM annually. The initial losses are estimated at $60\%$ of the net precipitation .The net available quantity for recharge is 133.58 MCM. For sustainable management of the ground water resources, recharge wells have been proposed in the higher order streams to augment the Raudatain aquifer in Kuwait. If the available quantity of precipitation can be successfully utilized, it will reduce considerable pressure on desalination, which is leading to increased salinity off the coast in Arabian Gulf.

• 한국농공학회논문집
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• 제62권6호
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• 한국농공학회논문집
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• 제59권3호
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.358-360
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• 2002

In order to find horizontal and vertical precipitation structure in Korean peninsula, we use ground-based radar, and Automatic Weather Station (AWS) data. Radar data was selected for rain events in the Pusan and Jindo in Korea, during the spring and summer season of 2002. AWS point gauge measurements are analyzed as part of spatial structure of precipitation. TRMM/PR and ground-based radar is used vertical correlation. The results showed, as expected that the correlation decreased rapidly with distance.

• 대한원격탐사학회지
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• 제33권1호
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.188-188
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• 2017

Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

• 한국지구과학회지
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• 제24권1호
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• pp.22-29
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• 2003

Temporal and spatial variability of precipitation (P), evaporation (E), and moisture balance (P-E; precipitation minus evaporation) has been investigated over the tropical ocean during the period from January 1998 to July 2001. Our data were analyzed by the EOF method using the satellite P and E observations made by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and the Special Sensor Microwave/Imager (SSM/I). This analysis has been performed for two three-year periods as follow; The first period which includes the El Ni${\tilde{n}}$o in early 1998 ranges from January 1998 to December 2000, and the second period which includes the La Ni${\tilde{n}}$o events in the early 1999 and 2000 (without El Ni${\tilde{n}}$o) ranges from August 1998 to July 2001. The areas of maxima and high variability in the precipitation and in the P-E were displaced from the tropical western Pacific and the ITCZ during the La Ni${\tilde{n}}$o to the tropical middle Pacific during the El Ni${\tilde{n}}$o, consistent with those in previous P studies. Their variations near the Korean Peninsula seem to exhibit a weakly positive correlation with that in the tropical Pacific during the El Ni${\tilde{n}}$o. The evaporation, out of phase with the precipitation, was reduced in the tropical western Pacific due to humid condition in boreal summer, but intensified in the Kuroshio and Gulf currents due to windy condition in winter. The P-E variability was determined mainly by the precipitation of which the variability was more localized but higher by 2-3 times than that of evaporation. Except for the ITCZ (0-10$^{\circ}$N), evaporation was found to dominate precipitation by ${\sim}$2 mm/day over the tropical Pacific. Annual and seasonal variations of P, E, and P-E were discussed.

• 대한원격탐사학회지
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• 제30권4호
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• pp.525-536
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• 2014

본 연구에서는 주요 수문 변수인 유출량, 저수위, 유량 등의 관측 자료가 부재한 미계측 유역에 대한 수문학적 가뭄 평가 및 감시를 위해 원격 탐사 자료를 활용하는 방법론을 최근 심각한 가뭄 피해를 입은 지역인 남한강상류 유역에 적용하였다. 수문 변수의 관측 자료가 부재한 지역에 대해서는 원격 탐사를 이용하여 수문 변수보다 추정이 용이한 강수량, 증발산량 등 기상 변수의 추정을 통해 물 수지에 기초하여 가뭄상태에 대한 정보를 얻을 수 있다. 본 연구에서는 2002-2013년의 기간에 대하여 원격 탐사 자료를 이용하여 대기의 온도를 추정하고, 이로부터 증발산량을 도출하여 강수량과 증발산량 차의 백분위가 유량 백분위와 가지는 상관성을 분석하였다. Aqua위성에 탑재된 MODIS 센서의 $1{\times}1km$ 공간 해상도의 지표면 온도와 $5{\times}5km$ 공간해상도의 대기 연직 온도 자료를 이용하여 월별 최고 및 최저 대기 온도를 추정하였으며, Hargreaves 방법을 이용하여 증발산량을 추정하였다. 미국몬태나주립대학교에서 Penman-Monteith 방법을 이용하여 추정한 기존 자료(MOD16)의 잠재 증발산량과 비교한 결과 상대적으로 결정계수는 더 작았으나 상당히 작은 오차를 보였다. 남한강상류 유역에 대하여 TRMM 위성으로부터 도출한 강수량과 함께 1, 3, 6, 12개월 시간 척도의 P-PET(강수량 증발산량) 백분위를 구해 유량 백분위와의 상관관계를 분석하였다. 남한강상류 유역은 여름철(r = 0.89, tau = 0.71)과 가뭄 평가에 중요한 가을철(r = 0.63, tau = 0.47)에 1개월 P-PET 백분위가 유량 백분위와 95% 신뢰도로 통계적으로 유의한 높은 상관관계를 나타냈다. 이 유역은 강수의 영향이 특히 크게 나타나는 지역으로 일반적으로 건조한 지역과는 달리 증발산량이 유량과 양의 상관관계를 보였다. 연구 결과로부터 원격 탐사 자료가 미계측 유역에서 수문학적 가뭄 평가 및 감시에 유용하게 활용될 수 있음을 보였으며 특히 공간적으로 분포된 높은 해상도의 추정 자료는 지역별로 차별화된 가뭄 대책 수립에 기여할 수 있을 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.19-28
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• 2005

Passive microwave remote sensing technique have shown great potential for mon monitoring regional/global surface soil moisture. Given a single measurement at dual polarization/single frequency/single view angle, a strategic approach to artificially generating multiple microwave brightness temperatures is presented. And then the statistically generated microwave brightness temperature data are applied to the inverse algorithm, which mainly relies on a physically based microwave emission model and an advanced single-criterion multi-parameter optimization technique, to simultaneously retrieve soil moisture and vegetation characteristics. . The procedure is tested with dual polarized Tropical Rainfall Measurement Mission Microwave Imager (TRMM/TMI) over two different cover sites in Oklahoma and Beltsville field experimental data. The retrieval results are analyzed and show excellent performance.

• 한국지리정보학회지
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• 제20권1호
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• pp.85-97
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• 2017

최근 전 세계적으로 지구온난화, 기후변화 등으로 태풍, 지진해일, 폭염 및 폭설 등과 같은 수재해의 피해가 대규모로 확대되었다. 특히 태풍으로 인한 경제적 손실은 1960년대 이후 경제개발 및 도시화로 인한 인구과밀지역에서 크게 나타나고 있다. 본 연구에서는 2016년 한반도를 강타한 태풍 차바를 비롯하여 태풍 루사('02), 태풍 매미('03) 및 태풍 볼라벤('12)에 대하여 한반도 내습 전 후 촬영된 위성 현황에 대하여 조사 및 분석을 실시한 결과, 기존 위성을 활용함에 있어 한계를 느끼게 되었다. 국내 위성은 주로 기상, 해양, 지형 및 통신 등의 목적으로 개발 운영됨으로 물 관리 및 수재해 대응에 필요한 시 공간적 데이터 관측 정보가 많이 부족하였다. 때문에 국외 위성으로 범위를 넓혀 조사를 실시하였으며, 이에 GMS, TRMM, COMS 및 GPM 등의 위성 자료를 수집하였다. 향후 한반도에 빠르고 정확한 수재해 정보를 얻기 위하여 시 공간적 데이터 분석단위를 만족시키는 수자원 위성의 개발 및 적용이 필요하다.