• The Journal of Engineering Geology
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• v.24 no.4
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• pp.501-510
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• 2014

Volcanic eruptions alone may lead to serious natural disasters, but the associated release of water from a caldera lake may be equally damaging. There is both historical and geological evidence of the past eruptions of Mt. Baekdusan, and the volcano, which has not erupted for over 100 years, has recently shown signs of reawakening. Action is required if we are to limit the social, political, cultural, and economic damage of any future eruption. This study aims to identify the area that would be inundated following a volcanic flood from the Cheon-Ji caldera lake that lies within Mt. Baekdusan. A scenario-based numerical analysis was performed to generate a flood hydrograph, and the parameters required were selected following a consideration of historical records from other volcanoes. The amount of water at the outer rim as a function of time was used as an upper boundary condition for the downstream routing process for a period of 10 days. Data from the USGS were used to generate a DEM with a resolution of 100 m, and remotely sensed satellite data from the moderate-resolution imaging spectroradiometer (MODIS) were used to show land cover and use. The simulation was generated using the software FLO-2D and was superposed on the remotely sensed map. The results show that the inundation area would cover about 80% of the urban area near Erdaobaihezhen assuming a 10 m/hr collapse rate, and 98% of the area would be flooded assuming a 100 m/hr collapse rate.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1129-1140
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• 2013

Precipitation is one of the important factors in the hydrological cycle. It needs to understand accurate of spatial precipitation field because it has large spatio-temporal variability. Precipitation data obtained through the Tropical Rainfall Monitoring Mission (TRMM) 3B43 product is inaccurate because it has 25 km space scale. Downscaling of TRMM 3B43 product can increase the accuracy of spatial precipitation field from 25 km to 1 km scale. The relationship between precipitation and the normalized difference vegetation index(NDVI) (1 km space scale) which is obtained from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor loaded in Terra satellite is variable at different scales. Therefore regression equations were established and these equations apply to downscaling. Two renormalization strategies, Geographical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA) are implemented for correcting the differences between remote sensing-derived and rain gauge data. As for considering the GDA method results, biases, the root mean-squared error (RMSE), MAE and Index of agreement (IOA) is equal to 4.26 mm, 172.16 mm, 141.95 mm, 0.64 in 2009 and 17.21 mm, 253.43 mm, 310.56 mm, 0.62 in 2011. In this study, we can see the 1km spatial precipitation field map over Korea. It will be possible to get more accurate spatial analysis of the precipitation field through using the additional rain gauges or radar data.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.301-311
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• 2017

Aerosol optical properties as well as vertical location of layer can alter the radiative balance of the Earth by reflecting and absorbing solar radiation. In this study, radiative transfer model (RTM) and satellite-based analysis have been used to quantify the top-of-atmosphere (TOA) radiative effect of aerosol layers in the cloudy atmosphere of the northeast Asia. RTM simulation results show that the atmospheric warming effect of aerosols increases with their height in the presence of underlying cloud layer. This relationship is higher for stronger absorbing aerosols and higher surface albedo condition. Over study region ($20-50^{\circ}N$, $110-140^{\circ}E$) and aerosol event cases, it is possible to qualitatively identify absorbing aerosol effects in the presence of clouds by combining the UV Absorbing Aerosol Index (AAI) derived from Total Ozone Mapping Spectrometer (TOMS), cloud parameters derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS), with TOA Upward Shortwave Flux (USF) from the Clouds and the Earth's Radiant Energy System (CERES). As the regional-mean radiative effect of aerosols, 6 - 26 % lower the USF between aerosols and cloud cover is taken into account. These results demonstrate the importance of estimation for the accurate quantification of aerosol's direct and indirect effect.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.105-123
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• 2018

Currently, satellite images act as essential and important data in water resources, environment, and ecology as well as information of geographic information system. In this paper, we will investigate basic characteristics of satellite images, especially application examples in water resources. In recent years, researches on spatial and temporal characteristics of large-scale regions utilizing the advantages of satellite imagery have been actively conducted for fundamental hydrological components such as evapotranspiration, soil moisture and natural disasters such as drought, flood, and heavy snow. Furthermore, it is possible to analyze temporal and spatial characteristics such as vegetation characteristics, plant production, net primary production, turbidity of water bodies, chlorophyll concentration, and water quality by using various image information utilizing various sensor information of satellites. Korea is planning to launch a satellite for water resources and environment in the near future, so various researches are expected to be activated on this field.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

• Journal of the Korean earth science society
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• v.32 no.4
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• pp.388-401
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• 2011

Asian dust was observed a total of 66 times in the springtime during the period from 2002 to 2010, with 26 cases in March, 23 cases in April and 17 cases in May. This study investigates a Asian dust episode that occurred during the period from 22 to 25 May 2010, based on synoptic weather patterns, wind vector at 850 hPa, relative humidity at 1000 hPa, Jet streams and wind vector at 300 hPa, PM10 concentration in Korea and satellite imagery. In this case, Asian dust originated on 22 May along the rear of a developing low pressure system in Mongolia. The Asian dust was then transported southeastward and bypassed the Korea peninsula from 23 to 24 May, before reaching Japan on 25 May. Jet streams on 24 May bypassed the Korean peninsula and induced the development of a surface low pressure centered over the peninsula. The resulting air flow was critical to the trajectory of the Asian dust, which likewise bypassed the Korean peninsula. 72-hour backward trajectory data reveal that the Shandong Peninsula and the East China Sea were the points of origin for the air flows that swept through the Japanese sites where Asian dust was observable to the naked eay. The Asian dust pathway is ascertained by horizontal distribution of the Asian dust of RGB imagery from MODIS satellites which captured the Asian dust moving over the Shandong Peninsula, the East China Sea, and northwest of the Kyushu region in Japan. Since the synoptic pattern and the transport way of the Asian dust case are far from typical ones, which Asian dust forecasting technique has long been based on, this study can be good example of exceptional Asian dust pattern and it will be used for more accurate Asian dust forecasting.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.627-646
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• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Atmosphere
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• v.25 no.1
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• pp.117-127
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• 2015

The presences of clouds significantly influence the accuracy of ozone retrievals from satellite measurements. This study focuses on the influence of clouds on Ozone Monitoring instrument (OMI) ozone profile retrieval based on an optimal estimation. There are two operational OMI cloud products; OMCLDO2, based on absorption in $O_2-O_2$ at 477 nm, and OMCLDRR, based on filling in Fraunhofer lines by rotational Raman scattering (RRS) at 350 nm. Firstly, we characterize differences between $O_2-O_2$ and RRS effective cloud pressures using MODIS cloud optical thickness (COT), and then compare ozone profile retrievals with different cloud input data. $O_2-O_2$ cloud pressures are significantly smaller than RRS by ~200 hPa in thin clouds, which corresponds to either low COT or cloud fraction (CF). On the other hand, the effect of Optical centroid pressure (OCP) on ozone retrievals becomes significant at high CF. Tropospheric ozone retrievals could differ by up to ${\pm}10$ DU with the different cloud inputs. The layer column ozone below 300 hPa shows the cloud-induced ozone retrieval error of more than 20%. Finally, OMI total ozone is validated with respect to Brewer ground-based total ozone. A better agreement is observed when $O_2-O_2$ cloud data are used in OMI ozone profile retrieval algorithm. This is distinctly observed at low OCP and high CF.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.105-114
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• 2013

Desertification of the East Asia area induced by human's indiscriminate activities and natural causes has gradually expanded and demanded scientific research for monitoring and predicting land cover condition. Therefore, this research classified land types which were compared to MODIS land cover and analyzed the extent of barren zone effecting Korea through yellow dust using S10-DAY MVC NDVI from SPOT between 1999 and 2011. This study used unsupervised classification after processing NDVI Correction and Water Mask for eliminating noise values included in the data for enhancement of classification accuracy. The results of analysis are that there are active variations near the borders of desert, especially the Mongolian steppe and the Gobi Desert in central Asia. In addition, the extent of entire desert has been decreased in the middle of the last decade, although desertification is in going on in East Asia.