• Atmosphere
• /
• v.25 no.2
• /
• pp.309-322
• /
• 2015

The objective of this study is to evaluate the impact of the high resolution topographies and landuses data on simulated meteorological variables (wind speed at 10 m, temperature at 2 m and relative humidity at 2 m) in WRF. We compare the results with WRF simulation using each resolution of the topographies and landuses, and with 37 AWS observation data on the Seoul metropolitan regions. According to results of using high-resolution topography, WRF model gives better topographical expression over domain. And we can separate more detail (Low intensity residential, high intensity residential, industrial or commercial) using high resolution landuses data. The result shows that simulated temperature and wind speed are generally higher than AWS observation data. However, simulation trend with temperature, wind speed, and relative humidity are similar to observation data. The reason for that is that the high precipitation event occurred in CASE 1 and 2. Temperature have correlation of 0.43~0.47 and standard deviation of $2.12{\sim}2.28^{\circ}C$ in CASE 1, while correlation of more than 0.8 and standard deviation of $3.05{\sim}3.18m\;s^{-1}$ in CASE 2. In case of wind speed, correlation have lower than 0.5 and Standard Deviation of $1.88{\sim}2.34m\;s^{-1}$ in CASE 1 and 2. In statistical analysis shows that using highest resolution (U01) results are more close to the AWS observation data. It can be concluded that the topographies and landuses are important factor that affect model simulation. However, the tendency to always use high resolution topographies and landuses data appears to be unjustified, and optimal solution depends on the combination of scale effect and mechanisms of dynamic models.

• Bulletin of the Korean Chemical Society
• /
• v.32 no.7
• /
• pp.2345-2350
• /
• 2011

Variable temperature high-resolution $^{19}F$ magic angle spinning (MAS) solid-state NMR spectroscopy was used to characterize fluorocarbon (FKM) rubbers. The high-resolution spectra of copolymers made from two monomers, vinylidene fluoride and hexafluoropropene, and terpolymers composed of vinylidene fluoride, hexafluoropropene, and tetrafluoroethylene, were obtained using MAS speeds of up to 18 kHz combined with high temperatures of up to 200 $^{\circ}C$ at a magnetic field strength of 9.4 Tesla. From these high resolution solid-state NMR spectra, we were able to assign the spectral peaks and differentiate the copolymer FKM from the terpolymer FKM. We also determined quantitatively the monomer compositions of each FKM rubber.

• Applied Microscopy
• /
• v.46 no.1
• /
• pp.1-5
• /
• 2016

Recent cryo-electron microscopy (EM) studies reported the structure of various types of proteins at high resolution which is sufficient to visualize the intermolecular interaction at near atomic level. There are two main factors that cause the advances in cryo-EM; the development of image processing techniques, such as single particle analysis, and the improved electron detection devices. Although the atomic structures of small and asymmetric proteins are not yet to be determined by cryo-EM, this striking improvement implies the bright prospect of the application in biomedical studies. This study reviews the recently published studies reported high resolution structures using improved imaging analysis techniques and electron detectors. Furthermore, we will discuss about the future aspects of cryo-EM application.

• Atmosphere
• /
• v.25 no.2
• /
• pp.283-294
• /
• 2015

For urban flash flood simulation, we need the higher resolution radar rainfall than radar rainfall of KMA, which has 10 min time and 1km spatial resolution, because the area of subbasins is almost below $1km^2$. Moreover, we have to secure the high quantitative accuracy for considering the urban hydrological model that is sensitive to rainfall input. In this study, we developed the quantitative precipitation estimation (QPE), which has 250 m spatial resolution and high accuracy using KMA AWS and SK Planet stations with Mt. Gwangdeok radar data in Seoul area. As the results, the rainfall field using KMA AWS (QPE1) is showed high smoothing effect and the rainfall field using Mt. Gwangdeok radar is lower estimated than other rainfall fields. The rainfall field using KMA AWS and SK Planet (QPE2) and conditional merged rainfall field (QPE4) has high quantitative accuracy. In addition, they have small smoothed area and well displayed the spatial variation of rainfall distribution. In particular, the quantitative accuracy of QPE4 is slightly less than QPE2, but it has been simulated well the non-homogeneity of the spatial distribution of rainfall.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.8-12
• /
• 1999

Since the advent of high resolution satellite image, possibilities of applying various human interpretation mechanism to these images have increased. Also many studies about these possibilities in many fields such as computer vision, pattern recognition, artificial intellegence and remote sensing have been done. In this field of these studies, texture is defined as a kind of quantity related to spatial distribution of brightness and tone and also plays an important role for interpretation of images. Especially, methods of obtaining texture by statistical model have been studied intensively. Among these methods, texture measurement method based on cooccurrence matrix is highly estimated because it is easy to calculate texture features compared with other methods. In addition, these results in high classification accuracy when this is applied to satellite images and aerial photos. But in the existing studies using cooccurrence matrix, features have been chosen arbitrarily without considering feature variation. And not enough studies have been implemented for appropriate resolution selection in which cooccurrence matrix can extract texture. Therefore, this study reviews the concept of cooccurrence matrix as a texture measurement method, evaluates usefulness of several features obtained from cooccurrence matrix, and proposes appropriate resolution by investigating variance trend of several features.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2004.03a
• /
• pp.571-577
• /
• 2004

The operational availability of multispactal high-resolution satellite imagery, opens up new possibilities for updating forest stand map. Compared with information acquired by traditional methods (Panchromatic Aerial Photo), these data offer a number of advantages, In this study used 1m resolution and 4 band multispectral, which are capability to update forest map of kind of tree. Therefore, high-resolution satellite imagery is good method for updating forest map in the future.

• Korean Journal of Remote Sensing
• /
• v.39 no.4
• /
• pp.395-407
• /
• 2023

Super-resolution (SR) has great significance in image processing because it enables downstream vision tasks with high spatial resolution. Recently, SR studies have adopted deep learning networks and achieved remarkable SR performance compared to conventional example-based methods. Deep-learning-based SR models generally require low-resolution (LR) images and the corresponding high-resolution (HR) images as training dataset. Due to the difficulties in obtaining real-world LR-HR datasets, most SR models have used only HR images and generated LR images with predefined degradation such as bicubic downsampling. However, SR models trained on simple image degradation do not reflect the properties of the images and often result in deteriorated SR qualities when applied to real-world images. In this study, we propose an image degradation model for HR satellite images based on the modulation transfer function (MTF) of an imaging sensor. Because the proposed method determines the image degradation based on the sensor properties, it is more suitable for training SR models on remote sensing images. Experimental results on HR satellite image datasets demonstrated the effectiveness of applying MTF-based filters to construct a more realistic LR-HR training dataset.

• ETRI Journal
• /
• v.37 no.2
• /
• pp.251-261
• /
• 2015

We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-of-the-art approaches, with comparable performance accuracy.

• Journal of Korean Society for Geospatial Information Science
• /
• v.22 no.1
• /
• pp.23-29
• /
• 2014

The emergence of high resolution satellite images and the evolution of spatial resolution facilitate various studies using high resolution satellite images. Above all, target detection algorithms are effective for monitoring of traffic flow and military surveillance and reconnaissance because vehicles, airplanes, and ships on broad area could be detected easily using high resolution satellite images. Recently, many satellites are launched from global countries and the diversity of satellite images are also increased. On the contrary, studies on comparison about the spatial resolution or target detection, especially, are insufficient in domestic and foreign countries. Therefore, in this study, effects of spatial resolution on target detection are analyzed using the PSO target detection algorithm. The resampling techniques such as nearest neighbor, bilinear, and cubic convolution are adopted to resize the original image into 0.5m, 1m, 2m, 4m spatial resolutions. Then, accuracy of target detection is assessed according to not only spatial resolution but also resampling method. As a result of the study, the resolution of 0.5m and nearest neighbor among the resampling methods have the best accuracy. Additionally, it is necessary to satisfy the criteria of 2m and 4m resolution for the detection of airplane and ship, respectively. The detection of airplane need more high spatial resolution than ship because of their complexity of shape. This research suggests the appropriate spatial resolution for the plane and ship target detection and contributes to the criteria of satellite sensor design.

• Atmosphere
• /
• v.27 no.3
• /
• pp.331-344
• /
• 2017

Solar energy is calculated using high-resolution digital elevation model (DEM). In focus on Seoul metropolitan area, correction coefficients of direct and diffuse solar energy with the topographic effect are calculated from DEM with 1720, 900, 450, 90 and 30 spatial resolutions ($m{\times}m$), respectively. The solar energy on the real surface with high-resolution is corrected using by the correction coefficients with topographic effect from the solar energy on horizontal surface with lower resolution. Consequently, the solar energy on the real surface is more detailed distribution than those of horizontal surface. In particular, the topographic effect in the winter is larger than summer because of larger solar zenith angle in winter. In Seoul metropolitan area, the monthly mean topographic effects are more than 200% in winter and within 40% in summer. And annual topographic effects are negative role with more than -60% and positive role with below 40%, respectively. As a result, topographic effect on real surface is not a negligible factor when calculating and analyzing solar energy using regional and global models.