• Journal of the Korean earth science society
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• v.33 no.7
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• pp.569-582
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• 2012

The heavy rainfalls caused large property damages and human casualties. For example, Changma caused 0.25 billion dollars in damages and 57 deaths and 112 missing by accompanying the torrentially convective heavy rainfall in Seoul, 2011. In addition, TY15 (Bolaven) caused a small damage by bringing a relatively small amount of rainfall and strong wind in Gwanju, 2012. The investigation and analyses of these mesoscale processes of rainfall events for different physical properties using KLAPS for weather environments of the above cases were performed. These typical and ideal meoscale systems by better and more favorable cloud systems were chosen to retrieve rain intensity from Radar and Chullian data. The quantitative rain intensities of Radar and Chullian differ greatly from the ground-based gauge values with underestimating over 50 mm/hr at the peak time of hourly maximum rain intensity about over than 85 mm/hr. However, the Radar rain intensity demonstrated approximately lower than 35 mm/hr, and the Chullian rain intensity less than 60 mm/hr for Changma in Seoul, 2011. For typhoon (TY15, Bolaven) in Gwangju, similarly, the quantitative rain intensities of Radar and Chullian differ from the ground-based gauge values. At the peak time, the hourly maximum rain intensity of ground-based gauge was more than 15 mm/hr. However, the Radar rain intensity showed lower than 5 mm/hr, and the Chullian rain intensity lower than 10 mm/hr. Regarding the above two cases of typhoon and Changma, even though Radar and Chullian rain intensities have been underestimated when compared to the ground-based rain intensity, the distributions of time scale features of both Radar and Chullian rain intensities still delineated a similar tendency of rain intensity distribution of the ground-based gauge data.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.589-597
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• 2023

Floating debris in large quantities from land during heavy rainfall has adverse social, economic, and environmental impacts, but the monitoring system for the concentration area and amount is insufficient. In this study, we proposed an efficient monitoring method for floating debris entering the river during heavy rainfall in Daecheong Lake, the largest water supply source in the central region, and applied remote sensing techniques to estimate the standing-stock of floating debris. To investigate the status of floating debris in the upper of Daecheong Lake, we used a tracking buoy equipped with a low-orbit satellite communication terminal to identify the movement route and behavior characteristics, and used a drone to estimate the potential concentration area and standing-stock of floating debris. The location tracking buoys moved rapidly during the period when the cumulative rainfall for 3 days increased by more than 200 to 300 mm. In the case of Hotan Bridge, which showed the longest distance, it moved about 72.8 km for one day, and the maximum moving speed at this time was 5.71 km/h. As a result of calculating the standing-stock of floating debris using a drone after heavy rainfall, it was found to be 658.8 to 9,165.4 tons, with the largest amount occurring in the Seokhori area. In this study, we were able to identify the main concentrations of floating debris by using location-tracking buoys and drones. It is believed that remote sensing-based monitoring methods, which are more mobile and quicker than traditional monitoring methods, can contribute to reducing the cost of collecting and processing large amounts of floating debris that flows in during heavy rain periods in the future.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.509-520
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• 2012

The objective of this study was to estimate rice yield in Korea using satellite and meteorological data such as sunshine hours or solar radiation, and rainfall. Terra and Aqua MODIS (The MOderate Resolution Imaging Spectroradiometer) products; MOD13 and MYD13 for NDVI and EVI, MOD15 and MYD15 for LAI, respectively from a NASA web site were used. Relations of NDVI, EVI, and LAI obtained in July and August from 2000 to 2011 with rice yield were investigated to find informative days for rice yield estimation. Weather data of rainfall and sunshine hours (climate data 1) or solar radiation (climate data 2) were selected to correlate rice yield. Aqua NDVI at DOY 233 was chosen to represent maximum vegetative growth of rice canopy. Sunshine hours and solar radiation during rice ripening stage were selected to represent climate condition. Multiple regression based on MODIS NDVI and sunshine hours or solar radiation were conducted to estimate rice yields in Korea. The results showed rice yield of $494.6kg\;10a^{-1}$ and $509.7kg\;10a^{-1}$ in 2011, respectively and the difference from statistics were $1.1kg\;10a^{-1}$ and $14.1kg\;10a^{-1}$, respectively. Rice yield distributions from 2002 to 2011 were presented to show spatial variability in the country.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.133-145
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• 2010

This study analyzed the characteristics of sediment produce by landslide triggered by rainfall. One-dimensional unsaturated groundwater model and infinite slope stability analysis were used to estimate the behavior of soil moisture and slope stability according to rainfall, respectively. Slope stability analysis was performed considering on soil depth and characteristics of trees. As the results considering on recovery of the failed slopes, much amount of sediment was produced in 1963, 1970, and 2002. As the results of verification of simulation results using Landsat 5 TM images, we can find differences of landslide location between the results from model and satellite images. These differences can be caused by uncertainties of the rough parameters in the model. However, in the case that Obong-dam basin was divided into two subbasin, Wangsan-chun and Doma-chun basin, the results of each subbasin show errors around 20%. And only 4% of error occurred in the case of comparing landslide area on the entire Obong-dam basin. These errors seem insignificant considering on the errors which can be caused from the analyses in this study such as estimation of sediment produce, soil cover classification, and estimation of landslide area.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.441-441
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• 2015

북한의 수자원 현황을 분석하고 미래를 전망하는 일은 수자원 분야 전문가들의 공통된 관심사 중 하나이다. 그러나 많은 노력에도 불구하고 제한된 자료로 인해 이에 대한 체계적인 성과가 구축되지 못한 것이 사실이다(안재현 등, 2010). 북한 수자원 현황과 관련해서 1994년 한국수자원공사의"북한 수자원 현황 및 개발 동향"에 대한 연구와 1996년 한국과학기술단체총연합회의"남북한 수자원 비교평가 연구"가 수행된 바 있다. 본 연구에서는 2012년 7월 북한의 홍수피해에 대하여 북한지역의 빈약한 강우량 정보를 활용하여 위성으로부터 유도된 강우자료를 보정하여 북한지역의 홍수량을 산정하는데 활용할 수 있는 시계열 자료를 생성하는 것을 목적으로 하였다. 2012년 북한 홍수피해는 조선 중앙통신 보도에 의하면 6월 말부터 7월말까지 169명 사망, 400여명 실중, 144명 상해의 인명피해와 평안남북도, 자강도, 함경남북도 등 4만 3770여 가구가 침수되었으며, 농경지 피해는 6만 5280정보가 유실, 매몰, 침수(평안북도 2만 3400정보, 평안남도 2만 1900정보, 함경남도 5679정보, 함경북도 7220정보)의 피해를 입은 것으로 보도하고 있다(http://www.hani.co.kr/arti/politics/defense/545795.html). 한편, 북한의 기상수문국 통보에 의하면 2012년 장마가 시작된 이후 20일 동인 평균 강우량의 2배 가까운 비가 내렸으며, 특히 7월 19일 오후 9시부터 21일 오후 3시 사이 자강도 동신군에 413mm, 송원군에 383mm, 희천시에 322mm, 평안북도 태천군에 380mm, 향산군에 312mm, 동창군에 304mm의 폭우가 쏟아졌다고 조선중앙통신은 덧붙였다. 본 연구에서는 위성으로부터 유도된 강수자료 중 GSMaP_NRT자료를 활용하여 북한의 기상수문국에서 통보한 같이 기간의 강수량 자료를 분석한 결과 자강도 동신군 지역의 경우 총강우는 208.8mm로 분석되었으며, 평균강우는 9.49mm, 최대강우강도는 17.7mm/hr로 분석되었다. 두 자료의 총강우량에 대한 상대오차는 약 49.5% 정도의 오차가 있는 것으로 분석되었다. 위성강우 보정 방법으로 Immerzeel(2001) 등은 위성으로 관측된 시계열 자료와 지상계측된 시계열 자료를 분석하여 두 자료간의 평균과 표준편차를 이용하여 평균 및 표준편차 계수를 산정하여 위성자료에 대한 보정강우를 생성하는 방법을 제시한 바 있다. 본 연구에서는 위성으로부터 유도된 강우량 자료는 시계열 자료이나 지점계측 강우는 총강우만 존재하여 총강우에 대한 시계열 자료를 위성강수자료를 무차원화하여 지점계측의 위성 보정강우를 생성하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.3-10
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• 2010

The development of various spatial information and GIS has led to the research on interpretation of natural phenomena and correlational studies. This study is aimed to analyze the correlation between RUSLE(Revised Universal Soil Loss Equation) around Nakdong River area during the period of 1955 to 2005 and the amount of area change in the islets at the estuary terrain calculated in the study "Change Detection at the Nakdong Estuary Delta using Satellite Image and GIS". For the calculation of RUSLE, The 'Revised-USLE' model, a modified USLE model commonly used in Korea was used. For the rainfall erosion factor to calculate and compare the area of islets, the actual observation data for one year before the observation of satellite image from all observatories across Korea was used. The correlation coefficient between RUSLE and area change of islets was 0.57 for Jinwoo Islet; 0.7 for Sinja Islet; 0.87 for Doyodeung. This results showed that there was a great influence from Doyodeung where the main water way of Nakdong River runs. This study showed that the study using USLE for various fields and through identifying the characteristics of each factor is useful to understand natural phenomenon in practice.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.497-510
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• 2010

In this study, comparisons of the backscattering coefficients and the coherence values which had been extracted from SAR (Synthetic Aperture Radar) images such as JERS-1, ENVISAT and ALOS satellites with surface roughness, surface geometric and soil moisture content were carried out. As the results of analysis using the backscattering coefficient and coherence values from SAR images, the coherence was shown high in the region containing more of mud fraction due to higher viscosity of fine grain-size. A lot of tidal channels were well developed in the Ganghwa tidal flat, affecting the drainage of seawater and subsequent soil moisture content by exposure time of tidal flat. The backscattering coefficient. consequently, appeared to be lower in sand flat and mix flat with decrease of soil moisture. In contrast, most mud flats were distributed at high elevation so that soil moisture was not much influenced by seawater. The backscattering coefficient in mud flat seemed to have a relationship with the density of tidal channel. In addition, lowering backscattering coefficients in the all Ganghwa tidal flat was observed when surface remnant water increased according to the amount of rainfall. The correlation between backscattering coefficient, coherence and sediment environment factors in the Ganghwa tidal flat was investigated. In the future, more quantitative spatial analysis will be helpful to well understand the sedimentary influence of various sediment environment factors.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.233-243
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• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.1-7
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• 2019

In this study, we estimated the tropospheric delay of GNSS (Global Navigation Satellite System) signals during passing through the atmosphere in relation to weather and seasonal factors. For this purpose, we chose four CORS (Continuously Operating Reference Station) stations from inland (CCHJ and PYCH) and on the coast (GEOM and CHJU). A total of 48 days for each station (one set of data for each week) were downloaded from the NGII (National Geographic Information Institute) and processed it using the scientific GNSS software. The average tropospheric delays in winter are less than 2,400 mm, which is about 200 mm less than those in summer. The estimated tropospheric delay shows a similar pattern from all stations except the absolute bias in magnitude, while a large delay was observed for the station located on the coast. In addition, the delay during the day was relatively stable in winter, and the average tropospheric delay was strongly related to the orthometric height. The inland stations have tropospheric delays by the precipitation rather than humidity due to dry weather and difference in temperature. On the contrary, it was primarily caused by the humidity on the sea. The correlation between temperature and water vapor pressure is 0.9 or larger for all stations, and the tropospheric delay showed a high linear relationship with temperature. It is necessary to analyze the GNSS data with higher temporal resolution (e.g. all RINEX data of the year) to improve the stability and reliability of the correlation results.