• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.508-510
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• 2003

Land cover change has been recognized as one of the most important factors influencing the occurrence of rainfall-triggered landslides. Satellite remote sensing provides detailed information regarding the spatial distribution and extent of land cover/use changes. This study describes the land cover changes in Nagasaki City, Japan and Kangnung City, South Korea. The former has been suffered from rainfall-triggered disasters for long term and latter was damaged by Typhoon Rusa in 2002. The results obtained from both study areas clearly show that land cover changes have occurred in the last decade as a result of both natural forces and human activities.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.179-179
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• 2015

Citarum River is one of the important river in West Java, Indonesia. During the rainy season, flood happens almost every year in Upper Citarum Watershed, hence, it is necessary to establish the countermeasure in order to prevent and mitigate flood damages. Since the lack of hydrological data for the modelling is common problem in this area, it is difficult to prepare the countermeasures. Therefore, we used Rainfall-Runoff-Inundation (RRI) Model developed by Sayama et al. (2010) as the hydrological and inundation modelling for evaluating the inundation case happened in Upper Citarum Watershed, West Java, Indonesia and the satellite based information such as rainfall (GSMaP), landuse and so on instead of the limited hydrological data. In addition, 3 arc-second HydroSHEDS Digital Elevation Model (DEM) is used. To verify the model, the observed data of Nanjung water stage gauging station and the daily observation data are used. Simulated inundation areas are compared with the flood extent figure from Upper Citarum Basin Flood Management Project (UCBFM).

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.445-454
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• 2009

Localized unprecedented torrential rain and heavy rainfall cause repeated damages and make it difficult to detect and predict the landslide caused by heavy rainfall. To analyze the landslide characteristics of Inje area this study used satellite images photographed after the occurrence of landslide caused by the typhoon Ewiniar occurred in July, 2006, and for GIS analysis purpose, interpreted the satellite images (SPOT5) visually to digitize into developing parts, water traveling parts and sediment parts. For analysis of spatial characteristics, landslide areas obtained from visual interpretation of digital map, 3rd & 4th forest vegetation maps and detailed soil map and grids were overlaid and analyzed. As a result, in regard to topographic features, landslide occurred at places, of which average slope is $26.34^{\circ}$, had south, south-east, south-west aspects and average altitude of 627m. From hydrological analysis, it was found out that water traveling area rapidly spread approaching water traveling area and sediment area. From forest type analysis, it was found out that landslide occurrence was high in pine woods, and in terms of girth class attribute, landslide occurred in small-sized woods, in which the crown occupancy of trees that have the diameter at breast height, 6~16cm, was greater than 50%. From the analysis of soil series, landslide areas constitute 37.85% of OdF and 37.35% of SmF, which had sandy loam soil and excellent drainage capacity. Through this study, landslides in Inje area were characterized and SPOT5 images of 2.5m resolution could be used. But there was a difficulty in determining water traveling parts adjacent to urban area.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.37-45
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• 2006

Damage of rivers construction is serious to natural disaster by concentration rainfall in summer. Specially, increase of soil erosion breeds flood calamity of river bed accumulation and pondage decline etc., and erosion increase in upper stream shows in rivers flood of earth and sand, farm land and form of urban district burying. Flood damage investigation through on-the-spot probe until present need effective and scientific modelling techniques because is not efficient. This research wished to examine practical use of monitoring data of high resolution satellite image through satellite image analysis of various space resolution. Research analyzed abstraction possibility of soil disaster information using high resolution satellite image. Also, studied soil disaster damage present condition interpretation practical use possibility through various resolution satellite image analysis, and studied practical use of KOMPSAT image for interpretation of river topography change analysis.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.439-444
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• 2006

Korea Peninsula consists of approximately 70% of mountainous terrain of total area, in addition, annual average rainfall is plentiful, especially during rainy season of summer, and it is often accompanied with typhoon and heavy rain, which results in frequent landslides. Since there are limitations with existing methods to analyze extensive disasters, it is necessary to develop new remote sensing technology using an artificial satellite to study on landslides closely. This paper is written in order to establish the database with map information on various landslides using GIS, furthermore, to analyze precariousness of the areas, which are susceptible to landslide, and risks of potential areas in consideration of heavy rain, based on land-cover classification derived from images from satellite.

• Proceedings of the KSRS Conference
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• v.2
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• pp.563-566
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• 2006

In order for the evaluation and analysis of the spring drought which has been periodically occurring in Korean peninsula since 2000, the use of satellite image data is increasing to investigate temporal and spatial characteristics of the drought areas. The recent spring droughts in south Korea have some characteristics. It last for short period in spring when the activity of vegetation is not lively and it have large areal deviation in the severity of drought. In this study, considering the characteristics of the spring drought in Korean peninsular, the MODIS satellite image data which has superior spatial and radiometric resolutions was used for the analysis of the spring drought. In two basins having different spatial characteristics, the drought events were selected and their severities were analyzed using the MODIS NDVI, LSWI, and daily rainfall data since 2000, and the spatial characteristics of the drought area were analyzed using the DEM, land cover, and digital forest map of the study areas.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.357-360
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• 2005

Soil loss is widely recognized as a threat to farm livelihoods and ecosystem integrity worldwide. Soil loss prediction models can help address long-range land management planning under natural and agricultural conditions. Even though it is hard to find a model that considers all forms of erosion, some models were developed specifically to aid conservation planners in identifying areas where introducing soil conservation measures will have the most impact on reducing soil loss. Revised Universal Soil Loss Equation (RUSLE) computes the average annual erosion expected on hillslopes by multiplying several factors together: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and support practice (P). The value of these factors is determined from field and laboratory experiments. This study calculated soil erosion using GIS-based RUSLE model in Imha basin and examined soil erosion source area using SPOT 5 high-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area applying field survey method in common areas (dry field & orchard area) that are difficult to confirm soil erosion source area using satellite image.

• KCID journal
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• v.21 no.1
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• pp.78-88
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• 2014

This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.