• Journal of Korean Society for Atmospheric Environment
• /
• v.24 no.6
• /
• pp.649-661
• /
• 2008

The impact of the detailed surface data on regional meteorological fields in complex coastal area is studied using RAMS. Resolutions of topography and land use data are very important to numerical modeling, because high resolution data can reflect correct terrain height and detail characteristics of the surface. Especially, in complex coastal region such as Gwangyang area, southern area in Korean Peninsula, high resolution topography and land use data are indispensable for accurate modeling results. This study investigated the effect of resolutions of terrain data using SRTM with 3 second resolution topography and KLU with 1 second resolution land use data. Case HR was the experiment using high resolution data, whereas Case LR used low resolution data. In Case HR, computed surface temperature was higher than Case LR along the coastline and wind speed was $1{\sim}2m/s$ weaker than Case LR. Time series of temperature and wind speed indicated great agreement with the observation data. Moreover, Case HR indicated outstanding results on statistical analysis such as regression, root mean square error, index of agreement.

• Atmosphere
• /
• v.23 no.4
• /
• pp.485-500
• /
• 2013

This study conducted WRF-Fire simulations in order to investigate sensitivities of the resolution of fire fuel and terrain data sets, and the surface wind to simulated fire area. The sensitivity simulations were consisted of 8 different WRF-Fire runs, each of which used different combination of data sets of fire fuel and terrain with different resolution. From the results it was turned out that the surface wind was most sensitive. The next was fire fuel and then fire terrain. Unfortunately, every run produced too much fire area. In other words no simulations succeeded in simulating such proper fire area so as for the WRF-Fire to be used realistically. It was verified that the errors of fire area from each runs were contributed by 41%, 53%, and 6% from surface wind, fire fuel, and fire terrain, respectively. Finally this study suggested that the selection of Anderson fuel category in the area of interest seemed to be very critical in the performance of WRF-Fire simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2012.05a
• /
• pp.847-848
• /
• 2012

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.231-236
• /
• 1999

Accurate ocean surface fluxes with high resolution are critical for understanding a mechanism of global climate. However, it is difficult to derive those fluxes by using ocean observation data because the number of ocean observation data is extremely small and the distribution is inhomogeneous. On the other hand. satellite data are characterized by the high density, the high resolution and the homogeneity. Therefore, it can be considered that we obtain accurate ocean surface by using satellite data. Recently we constructed ocean surface data sets mainly using satellite data. The data set is named by Japanese Ocean Flux data sets with Use of Remote sensing Observations (J-OFURO). Here, we introduce J-OFURO. The data set includes shortwave radiation, longwave radiation, latent heat flux, sensible heat flux, and momentum flux etc. Moreover, sea surface dynamic topography data are included in the data set. Radiation data sets covers western Pacific and eastern Indian Ocean because we use a Japanese geostationally satellite (GMS) to estimate radiation fluxes. On the other hand, turbulent heat fluxes are globally estimated. The constructed data sets are used and shows the effectiveness for many scientific studies.

• Journal of Environmental Impact Assessment
• /
• v.20 no.2
• /
• pp.199-205
• /
• 2011

The Saemangeum embankment construction have changed the flowing on the topography of the coastal marine environment. However, the variety of ecological factors are changing from outside of Saemangeum embankment area. The ecosystem of various marine organisms have led to changes by sea surface temperature. The aim of this study is to monitoring of sea surface temperature(SST) changes were measured by using thermal infrared satellite imagery, MODIS and Landsat. The MODIS data have the high temporal resolution and Landsat satellite data with high spatial resolution was used for time series monitoring. The extracted informations from sea surface temperature changes were compared with the dyke to allow them inside and outside of Saemangeum embankment. The spatial extent of the spread of sea water were analyzed by SST using MODIS and Landsat thermal channel data. The difference of sea surface temperature between inland and offshore waters of Saemangeum embankment have changed by seasonal flow and residence time of sea water in dyke.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.3
• /
• pp.217-223
• /
• 2014

With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

• New & Renewable Energy
• /
• v.9 no.2
• /
• pp.15-22
• /
• 2013

The solar energy are an infinite source of energy and a clean energy without secondary pollution. The global solar energy reaching the earth's surface can be calculated easily according to the change of latitude, altitude, and sloped surface depending on the amount of the actual state of the atmosphere and clouds. The high-resolution solar-meteorological resource map with 1km resolution was developed in 2011 based on GWNU (Gangneung-Wonju National University) solar radiation model with complex terrain. The very high resolution solar energy map can be calculated and analyzed in Seoul and Eunpyung with topological effect using by 1km solar-meteorological resources map, respectively. Seoul DEM (Digital Elevation Model) have 10m resolution from NGII (National Geographic Information Institute) and Eunpyeong new town DSM (Digital Surface Model) have 1m spatial resolution from lidar observations. The solar energy have small differences according to the local mountainous terrain and residential area. The maximum bias have up to 20% and 16% in Seoul and Eunpyung new town, respectively. Small differences are that limited area with resolutions. As a result, the solar energy can calculate precisely using solar radiation model with topological effect by digital elevation data and its results can be used as the basis data for the photovoltaic and solar thermal generation.

• The Bulletin of The Korean Astronomical Society
• /
• v.44 no.1
• /
• pp.52.1-52.1
• /
• 2019

The Helioseismic and Magnetic Imager (HMI) is the instrument of Solar Dynamics Observatory (SDO) to study the magnetic field and oscillation at the solar surface. The HMI image is not enough to analyze very small magnetic features on solar surface since it has a spatial resolution of one arcsec. Super resolution is a technique that enhances the resolution of a low resolution image. In this study, we use a method for enhancing the solar image resolution using a Deep-learning model which generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained a model based on a very deep residual channel attention networks (RCAN) with HMI images in 2014 and test it with HMI images in 2015. We find that the model achieves high quality results in view of both visual and measures: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is much better than the conventional bi-cubic interpolation. We will apply this model to full-resolution SDO/HMI and GST magnetograms.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2006.06a
• /
• pp.34-39
• /
• 2006

An automated surface-strain measurement system, named ASIAS, was developed by using the image processing and stereo vision techniques in the previous studies by the corresponding author and his coworkers. This system has been upgraded mainly to improve the accuracy through image enhancement, sub-pixel measurement, surface smoothing, etc., since the first version was released. The present study has still more improved the convenience of users as well as the accuracy of measurement by processing high resolution images 8 mega pixels or more which can be easily obtained from a portable digital steal camera. It is proved that high resolution image processing greatly decreases the measurement error and gives strain data without considerable deterioration of accuracy even when the deformed grids to be measured and the master grids for camera calibration are captured together in the same image, making the whole process of strain measurement much simpler.

• Korean Journal of Remote Sensing
• /
• v.12 no.1
• /
• pp.60-80
• /
• 1996

AVHRR(Advanced Very High Resolution Radiometer) on NOAA satellite provides data in five spectral, one in visible range, one in near infrared and three in thermal range. In this paper, application of NOAA/AVHRR data is studied for environment monitoring such as cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index, forest fire, flood, snow cover and so on. The analyses for cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index and forest fire showed reasonable agreement. But monitoring for flood and snow cover was uneasy due to the limitations such as cloud contamination, low spatial resolution. So this research had only simple purpose to identify well-defined waterbody for dynamic monitoring of flood. Based on development of these basic algorithms, we have a plan to further reseach for environment monitoring using AVHRR data.