• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.953-966
• /
• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_2
• /
• pp.875-883
• /
• 2023

In this letter, we used PlanetScope imagery to conduct experiments on the color characteristics for oil type classification of marine oil spills through Red-Green-Blue (RGB) histogram analysis. The histograms of marine oil spills can be divided into three categories (dark black tones, light silver tones, and light rainbow tones) according to the distribution of pixel values in each band. Thick oil layers with dark black tones can be classified as heavy oil, while thin oil layers with light silver and rainbow tones can be classified as light oil. As more images are analyzed in the future, these oil spill detection and classification methods will become more generalized and reliable.

• Journal of radiological science and technology
• /
• v.32 no.4
• /
• pp.453-460
• /
• 2009

The purpose of this study was to determine the dose distribution and image quality according to slice thickness and BC(beam collimation) in the gantry aperture. CT scans were performed with a 64-slice MDCT(Brilliance 64, Philips, Cleveland, USA) scanner. To determine the dose distribution according to BC, a ionization chamber was placed at isocenter and 5, 10, 15, 20, 25 and 30 cm positions from the isocenter in the 12, 3, 6 and 9 o'clock directions. The dose distribution for phantom scan was also measured using CT head and body dose phantom with five holes at the center of the phantom and the positions of the 12, 3, 6 and 9 o'clock directions. The image noise measurement for different BCs was performed using an AAPM CT phantom. Water-filled block of the phantom was moved by 5 cm or 10 cm to the 12 o'clock direction, and the image noise was measured at the center of the phantom, and the points of 12, 3, 6 and 9 o'clock direction respectively. Some points were placed beyond the scan field of view (SFOV), so that measurement was not possible at that points. The results are as follows: The CTDIw showed a larger decrease as the source goes farther from the iso-center or the BC became wider. The CTDIw depends on the BC width more than the number of the channel of a detector array. The value of CTDIW decreased with increasing BC, but the value decreased 16.6~31.9% in the head phantom scan in air scan and 51.0~64.5% in the body phantom scan. The value of the noise was 3.9~5.9 in the head and 5.3~7.4 in the body except for BC of $2{\times}0.5\;mm$, regardless of the degree of deviation from the iso-center. When a subject was located within the SFOV, the position did not significantly affect image quality even if the subject was out of the center.

• The Korean Journal of Nuclear Medicine
• /
• v.36 no.3
• /
• pp.155-165
• /
• 2002

Purpose: The aim of this study was to identify the brain areas whose regional cerebral blood flow (rCBF) was changed in medial temporal lobe epilepsy (mTLE) using ${H_2}^{15}O-PET$. Materials and Methods: 12 patients with mTLE (6 left, 6 right mTLE) and 6 normal controls were scanned during a fixation baseline period and a sensory-motor condition where subjects pressed a button to an upward arrow. A voxel-based analysis using SPM99 software was peformed to compare the patient groups with the normal controls for the rCBF during fixation baseline period and for relative changes of rCBF during the sensory-motor task relative to fixation. Results: During the fixation baseline, a significant reduction of rCBF was found posterior insula bilaterally and right frontopolar regions in right mTLE patients compared to the normal controls. In left mTLE patients, the reduction was found in left frontopolar and temporal legions. During the sensory-motor task, rCBF increase over the fixation period, was reduced in left frontal and superior temporal legions in the right mTLE patients whereas in various areas of right hemisphere in left mTLE patients, relative to normal controls. However, the increased rCBF was also found in the left inferior parietal and anterior thalamic/fornix regions in both right and left mTLE patients compared to normal controls. Conclusion: Epilepsy induced changes were found not only in relative increase/decrease of rCBF during a simple sensory-motor control condition relative to a fixation rest condition but also in the relative rCBF distribution during the rest period.

• Radiation Oncology Journal
• /
• v.20 no.3
• /
• pp.264-273
• /
• 2002

Purpose : Three-dimensional radiation dosimetry using magnetic resonance imaging of polymer gel was recently introduced. This dosimetry system is based on radiation induced chain polymerization of acrylic monomers in a muscle equivalent gel and provide accurate 3 dimensional dose distribution. We planned this study to evaluate the clinical value of this 3-dimensional dosimetry. Materials and Methods: The polymer gel poured into a cylindrical glass flask and a spherical glass flask. The cylindrical test tubes were for dose response evaluation and the spherical flasks, which is comparable to the human head, were for isodose curves. T2 maps from MR images were calculated using software, IDL. Dose distributions have been displayed for dosimetry. The same spherical flask of gel and the same irradiation technique was used for film and TLD dosimetry and compared with each other. Results : The R2 of the gel respond linearly with radiation doses in the range of 2 to 15 Gy. The repeated dosimetry of spherical gel showed the same isodose curves. These isodose curves were identical to dose distributions from treatment planning system especially high dose range. In addition, the gel dosimetry system showed comparable or superior results with the film and TLD dosimetry. Conclusion : The 3-dimensional dosimetry for conformal radiation therapy using MRI of polymer gal showed stable and accurate results. Although more studies are needed for convenient clinical application, it appears to be a useful tool for conformal radiation therapy.

• Progress in Medical Physics
• /
• v.22 no.1
• /
• pp.42-51
• /
• 2011

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.

• Korean Journal of Remote Sensing
• /
• v.28 no.4
• /
• pp.393-407
• /
• 2012

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of $3{\times}3$, $5{\times}5$, $7{\times}7$, and $9{\times}9$ pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of $7{\times}7$ produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of $9{\times}9$ produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

• Korean Journal of Remote Sensing
• /
• v.33 no.2
• /
• pp.243-248
• /
• 2017

Sea ice which is an important component of the global climate system is being actively detected by satellite because it have been distributed to polar and high-latitude region. and the sea ice detection method using satellite uses reflectance and temperature data. the sea ice detection method of Moderate-Resolution Imaging Spectroradiometer (MODIS), which is a technique utilizing Ice Surface Temperature (IST) have been utilized by many studies. In this study, we propose a simple and effective method of sea ice detection using the dynamic threshold technique with no IST calculation process. In order to specify the dynamic threshold, pixels with freezing point of MODIS IST of 273.0 K or less were extracted. For the extracted pixels, we analyzed the relationship between MODIS IST, MODIS $11{\mu}m$ channel brightness temperature($T_{11{\mu}m}$) and Brightness Temperature Difference ($BTD:T_{11{\mu}m}-T_{12{\mu}m}$). As a result of the analysis, the relationship between the three values showed a linear characteristic and the threshold value was designated by using this. In the case ofsea ice detection, if $T_{11{\mu}m}$ is below the specified threshold value, it is detected as sea ice on clear sky. And in order to estimate the performance of the proposed sea ice detection method, the accuracy was analyzed using MODIS Sea ice extent and then validation accuracy was higher than 99% in Producer Accuracy (PA).

• Economic and Environmental Geology
• /
• v.55 no.5
• /
• pp.551-561
• /
• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1211-1224
• /
• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.