• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.65-69
• /
• 2015

하천에서 유사이동은 하천환경과 하천형상을 결정하는 주요 요소이므로 이를 해석하는 것은 매우 중요하다. 그러나 유사이동은 일반적으로 이상흐름 (two-phase flow)이며 난류를 동반하기에 이를 해석하기에는 쉽지 않다. 이상흐름을 해석하는 방법으로는 유사를 연속상인 유사구름(sediment cloud)으로 표현하여 해석하는 Euler-Euler 모형이 있으며 입자를 직접 추적하여 해석하는 Euler-Lagrange 모형이 있다. 본 연구에서는 유사이동 해석을 위하여 Euler-Lagrange 모형을 사용하였으며 흐름의 진동성분을 고려하기 위하여 EIM (Eddy Interaction Model)을 사용하였다. 유체의 유속은 Dou (1987)가 제시한 경험식을 사용하였고 난류운동에너지와 소산률은 Nezu and Nakagawa (1993)가 제시한 식을 사용하였다. EIM에서 입자에 발생하는 와의 영향시간(eddy interaction time)을 계산하기 위해 Gosman and Ioannides (1983)가 제시한 eddy lifetime과 eddy crossing time을 사용하였다. 유사입자는 입자의 운동량방정식을 풀어 그 거동을 추적하였으며 일정 시간 후 입자의 수를 이용하여 농도를 계산하였다. 유체에 발생하는 유속의 진동성분에 의해 입자가 부상하고 중력에 의해 흐름에 따른 일정한 농도분포 형태를 가지는 것을 확인하였다. 유사의 입자크기와 흐름에 따른 농도분포를 계산하였으며, 이를 측정치와 비교하여 EIM의 적용성을 확인하였다.

• 한국태양에너지학회:학술대회논문집
• /
• 2011.11a
• /
• pp.342-347
• /
• 2011

Solar energy is attenuated by absorbing gases (ozone, aerosol, water vapour and mixed gas) and cloud in the atmosphere. And these are measured with solar instruments (pyranometer, phyheliometer). However, solar energy is insufficient to represent detailed energy distribution, because the distributions of instruments are limited on spatial. If input data of solar radiation model is accurate, the solar energy reaches at the surface can be calculated accurately. Recently a variety of satellite measurements are available to TERA/AQUA (MODIS), AURA (OMI) and geostationary satellites (GMS-5, GOES-9, MTSAT-1R, MTSAT-2 and COMS). Input data of solar radiation model can be used aerosols and surface albedo of MODIS, total ozone amount of OMI and cloud fraction of meteorological geostationary satellite. The solar energy reaches to the surface is calculated hourly by solar radiation model and those are accumulated monthly and annual. And these results are verified the spatial distribution and validated with ground observations.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1181-1189
• /
• 2022

Clouds are composed of tiny water droplets, ice crystals, or mixtures suspended in the atmosphere and cover about two-thirds of the Earth's surface. Cloud detection in satellite images is a very difficult task to separate clouds and non-cloud areas because of similar reflectance characteristics to some other ground objects or the ground surface. In contrast to thick clouds, which have distinct characteristics, thin transparent clouds have weak contrast between clouds and background in satellite images and appear mixed with the ground surface. In order to overcome the limitations of transparent clouds in cloud detection, this study conducted cloud detection focusing on transparent clouds using machine learning techniques (Random Forest [RF], Convolutional Neural Networks [CNN]). As reference data, Cloud Mask and Cirrus Mask were used in MOD35 data provided by MOderate Resolution Imaging Spectroradiometer (MODIS), and the pixel ratio of training data was configured to be about 1:1:1 for clouds, transparent clouds, and clear sky for model training considering transparent cloud pixels. As a result of the qualitative comparison of the study, bothRF and CNN successfully detected various types of clouds, including transparent clouds, and in the case of RF+CNN, which mixed the results of the RF model and the CNN model, the cloud detection was well performed, and was confirmed that the limitations of the model were improved. As a quantitative result of the study, the overall accuracy (OA) value of RF was 92%, CNN showed 94.11%, and RF+CNN showed 94.29% accuracy.

• Journal of the Korea Society for Simulation
• /
• v.32 no.3
• /
• pp.1-8
• /
• 2023

Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

• Journal of The Geomorphological Association of Korea
• /
• v.25 no.1
• /
• pp.67-80
• /
• 2018

This study used aerial and terrestrial images to build a three-dimensional model of cliffs located in Pado beach using SfM (Structure from Motion) techniques. Using both images, the study purposed to reduce the shadow areas that were found when using only aerial images. Accuracy of the two campaigns was assessed by root mean square error, and monitored by M3C2 (Multiscale Model to Model Cloud Comparison) method. The result of the M3C2 in closed areas such as sea cave and notch did not express the landforms partly. However, eroded debris on sea cliffs were detected as eroded area by M3C2, as well as in captured pictures by multi-camera. The result of this study showed the applicability of multi-camera and SfM in monitoring changes of sea cliffs.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.216-216
• /
• 2015

Frequent hydro-meteorological events caused by global climate change and human exacerbate activities, make the water resource problem more complicated. The increasing speed urbanization brings a significant impact on the city flood control and security, water supply safety, water ecological security, water environment safety and the water engineering security in China, and puts forward higher requirements to urban water integrated management, undoubtedly which become the biggest obstacle for water ecological civilization construction, thus urgent requiring an advanced methods to enhance the effectiveness of the water integrated management. The other fields of smart ideas point out a development path for water resource development. The construction demand of smart water resource is expounded in the paper, combining the philosophy of modern Internet of things with the application of cloud computing technology. The concept of smart water resource is analyzed, the connotation characteristics of smart water resource is extracted, and the general model of smart water resource is refined. Then, the frame structure of smart water resource is put forward. The connotation and the overall framework of the smart water resource represent a higher level of water resource informationization development and provide a comprehensive scientific and technological support to transform water resource management from an extensive, passive, static, branch and traditional management to a fine, active, dynamic, collaborative and modern management.

• 한국신재생에너지학회:학술대회논문집
• /
• 2011.11a
• /
• pp.56.1-56.1
• /
• 2011

The solar and meteorological resources map is calculated using by one-layer solar radiation model (GWNU model), satellites data and numerical model output on the Korean peninsula. The Meteorological input data to perform the GWNU model are retrieved aerosol optical thickness from MODIS (TERA/AQUA), total ozone amount from OMI (AURA), cloud fraction from geostationary satellites (MTSAT-1R) and temperature, pressure and total precipitable water from output of RDAPS (Regional Data Assimilation and Prediction System) and KLAPS (Korea Local Analysis and Prediction System) model operated by KMA (Korea Meteorological Administration). The model is carried out every hour using by the meteorological data (total ozone amount, aerosol optical thickness, temperature, pressure and cloud amount) and the basic data (surface albedo and DEM). And the result is analyzed the distribution in time and space and validated with 22 meteorological solar observations. The solar resources map is used to the solar energy-related industries and assessment of the potential resources for solar plant. The National Institute of Meteorological Research in KMA released $4km{\times}4km$ solar map in 2008 and updated solar map with $1km{\times}1km$ resolution and topological effect in 2010. The meteorological resources map homepage (http://www.greenmap.go.kr) is provided the various information and result for the meteorological-solar resources map.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.34-34
• /
• 2023

The Chah-Nimeh reservoirs, which are a sort of natural lakes located in the border of Iran and Afghanistan, are the main drinking and agricultural water resources of Sistan arid region. Considering the occurrence of intense seasonal wind, locally known as levar wind, this study aims to explore the possibility to provide a TSM (Total Suspended Matter) monitoring model of Chah-Nimeh reservoirs using multi-temporal satellite images and in-situ wind speed data. The results show that a strong correlation between TSM concentration and wind speed are present. The developed empirical model indicated high performance in retrieving spatiotemporal distribution of the TSM concentration with R²=0.98 and RMSE=0.92g/m³. Following this observation, we also consider a machine learning-based model to predicts the average TSM using only wind speed. We connect our in-situ wind speed data to the TSM data generated from the inversion of multi-temporal satellite imagery to train a neural network based mode l(Wind2TSM-Net). Examining Wind2TSM-Net model indicates this model can retrieve the TSM accurately utilizing only wind speed (R²=0.88 and RMSE=1.97g/m³). Moreover, this results of this study show tha the TSM concentration can be estimated using only in situ wind speed data independent of the satellite images. Specifically, such model can supply a temporally persistent means of monitoring TSM that is not limited by the temporal resolution of imagery or the cloud cover problem in the optical remote sensing.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.147-147
• /
• 2022

In January 2021 heavy flood affected South Kalimantan with causing many casualties. The heavy rainfall is predicted to be generated due to the ENSO (El Nino-Southern Oscillation). The weak La-Nina mode appeared to generate more convective cloud above the warmed ocean and result in extreme rainfall with high anomaly compared to past historical rainfall event. Subsequently, the antecedent soil moisture distribution showed to have an important role in generating the flood response. Saturated flow and infiltration excess mainly contributed to the runoff generation due to the high moisture capacity. The hydro-meteorological processes in this event were deeply analyzed using the coupled atmospheric model of Weather Research and Forecasting (WRF) and the hydrological model extension (WRF-Hydro). The sensitivity analysis of the flood response to the SST anomaly and the soil moisture capacity also compared. Result showed that although SST and soil moisture are the main contributors, soil moisture have more significant contribution to the runoff generation despite of anomaly rainfall occurred. Model performance was validated using the Global Precipitation Measurement (GPM) and Soil Moisture Operational Products System (SMOPS) and performed reasonably well. The model was able to capture the hydro-meteorological process of atmosphere and hydrological feedbacks in the extreme weather event.

• Journal of Astronomy and Space Sciences
• /
• v.26 no.4
• /
• pp.555-566
• /
• 2009

Precipitable water vapor (PWV) derived from a numerical weather prediction (NWP) model were compared to observations derived from ground-based Global Positioning System (GPS) receivers. The model data compared were from the Weather Research and Forecasting (WRF) model short-range forecasts on nested grids. The numerical experimets were performed by selecting the cloud microphysics schemes and for the comparisons, the Changma period of 2008 was selected. The observational data were derived from GPS measurements at 9-sites in South Korea over a 1-month period, in the middle of June-July 2008. In general, the WRF model demonstrated considerable skill in reproducing the temporal and spatial evolution of the PWV as depicted by the GPS estimations. The correlation between forecasts and GPS estimates of PWV depreciated slowly with increasing forecast times. Comparing simulations with a resolution of 18 km and 6 km showed no obvious PWV dependence on resolution. Besides, GPS and the model PWV data were found to be in quite good agreement with data derived from radiosondes. These results indicated that the GPS-derived PWV data, with high temporal and spatial resolution, are very useful for meteorological applications.