• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.627-636
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• 2021

Although many studies on ship detection using synthetic aperture radar (SAR) satellite images are being conducted around the world, there are still very few employing SAR microsatellites, as most of the microsatellites are optical satellites. Recently, the ICEYE and Capella Space have embarked on the development of microsatellites with SAR sensor, and similar projects are being initiated globally in line with the flow of the new space era [e.g., for the ICEYE: 18 satellites (~2021); Capella Space: 36 satellites (~2023); and the Coast Guard SAR: 32 satellites in the early development stage]. In preparation for these new systems, it is important to review the SAR microsatellite system and the recent advances in this technology. Accordingly, in this paper, the current status and characteristics of optical and SAR microsatellite constellation operation are described, and studies using them are investigated. In addition, based on the status and characteristics of the representative SAR microsatellites, specifically the ICEYE and Capella systems, methods for using SAR microsatellite data for ship detection applications are described. Our results confirm that the SAR microsatellites operate as a constellation and have the advantages of short revisit cycles and quick provision of high-resolution images. With this technology, we expect SAR microsatellites to contribute greatly to the monitoring a wide-area target vessel, in which the spatiotemporal resolution of the imagery is especially important.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.424-433
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• 2021

Recent climate change has caused abnormal weather phenomena all over the world and a lot of damage in many fields of society. Particularly, a lot of recent damages were due to extreme precipitation, such as torrential downpour or drought. The objective of this study was to analyze the temporal and spatial changes in the precipitation pattern in South Korea. To achieve this objective, this study selected some of the precipitation indices suggested in previous studies to compare the temporal characteristics of precipitation induced by climate change. This study selected ten ASOS observatories of the Korea Meteorological Administration to understand the change over time for each location with considering regional distribution. This study also collected daily cumulative precipitation from 1951 to 2020 for each point. Additionally, this study generated high-resolution national daily precipitation distribution maps using an orographic precipitation model from 1981 to 2020 and analyzed them. Temporal analysis showed that although annual cumulative precipitation revealed an increasing trend from the past to the present. The number of precipitation days showed a decreasing trend at most observation points, but the number of torrential downpour days revealed an increasing trend. Spatially, the number of precipitation days and the number of torrential downpour days decreased in many areas over time, and this pattern was prominent in the central region. The precipitation pattern of South Korea can be summarized as the fewer precipitation days and larger daily precipitation over time.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1623-1631
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• 2022

Since oil spills can be a significant threat to the marine ecosystem, it is necessary to obtain information on the current contamination status quickly to minimize the damage. Satellite-based detection of marine oil spills has the advantage of spatiotemporal coverage because it can monitor a wide area compared to aircraft. Due to the recent development of computer vision and deep learning, marine oil spill detection can also be facilitated by deep learning. Unlike the existing studies based on Synthetic Aperture Radar (SAR) images, we conducted a deep learning modeling using PlanetScope optical satellite images. The blind test of the DeepLabV3+ model for oil spill detection showed the performance statistics with an accuracy of 0.885, a precision of 0.888, a recall of 0.886, an F1-score of 0.883, and a Mean Intersection over Union (mIOU) of 0.793.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.

• The Journal of Internal Korean Medicine
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• v.42 no.2
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• pp.75-85
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• 2021

Objectives: This study reported about a patient with a right middle cerebral artery infarction whose gait disturbance was improved by Korean medicine treatment. Methods: The patient was treated with a Korean herbal medicine (Gami-yukmijihwang-tang) along with acupuncture, electroacupuncture, moxibustion, cupping, and physical therapy. The treatment effect was evaluated with the manual muscle test (MMT) and the Korean version of the modified Barthel index (K-MBI). The gait of the patient was evaluated by a 10-m walk test (10MWT), the timed up and go (TUG) test, the functional ambulation profile (FAP) score, and the functional ambulatory category (FAC) score. Spatiotemporal parameters were evaluated using a walkway system (GAITRite®, CIR Systems, Inc., USA). Results: After 83 days of traditional Korean medicine treatment, the K-MBI and FAC scores improved from 50 to 70 and from 1 to 4, respectively. The 10MWT and TUG tests also improved from 24.86 to 16.66 sec and from 22.35 to 17.62 sec, respectively. GAITRite® measurements reflected gait improvements: the FAP score improved from 55 to 86 sec; the step time improved from 0.72 to 0.669 sec; the step length improved from 31.076 cm to 41.284 cm; the gait velocity improved from 42.8 cm/sec to 64.1 cm/sec; the cadence improved from 93.6 steps/min to 90.8 steps/min. No adverse effects resulting from treatment or evaluation occurred during the admission period. Conclusions: This study suggests that traditional Korean medicine treatment may reduce symptoms and improve the quality of life in patients with cerebral infarction.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.453-462
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• 2021

As the frequency of localized heavy rainfall has increased during recent years, the importance of high-resolution radar data has also increased. This study aims to correct the bias of Dual Polarization radar that still has a spatial and temporal bias. In many studies, various statistical techniques have been attempted to correct the bias of radar rainfall. In this study, the bias correction of the S-band Dual Polarization radar used in flood forecasting of ME was implemented by a Convolutional Autoencoder (CAE) algorithm, which is a type of Convolutional Neural Network (CNN). The CAE model was trained based on radar data sets that have a 10-min temporal resolution for the July 2017 flood event in Cheongju. The results showed that the newly developed CAE model provided improved simulation results in time and space by reducing the bias of raw radar rainfall. Therefore, the CAE model, which learns the spatial relationship between each adjacent grid, can be used for real-time updates of grid-based climate data generated by radar and satellites.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1105-1114
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• 2022

A study on a method to overcome the limitations of the topographical and hydrological observation environment for estimating the QPE with high consistency with the ground rainfall by utilizing the spatiotemporal observation advantages of the rainfall radar for use in flood forecasting, and quantitative observations of localized rainfall due to these limiting conditions Uncertainty should be identified in terms of flood analysis. Against this background, in this study, 22 major heavy rain events in 2016 were analyzed for each of Mt. Biseul (BSL), Mt. Sobaek (SBS), Mt. Gari (GRS), Mt. Mohu (MHS), and Mt. Seodae (SDS) to determine the observation distance and altitude. The uncertainty of observation was quantified and an error map was derived. As a result of the analysis, it was found that, on average, the rainfall radar exceeded 10% up to 100 km and 30% over 150 km. Based on the average radar operating altitude angle, it was found that the error for the altitude was approximately 10% or less up to the second altitude angle, 20% at the third or higher altitude angle, and more than 50% at the fourth altitude angle or higher.

• Journal of Space Technology and Applications
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• v.2 no.2
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• pp.104-120
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• 2022

The Small Scale magNetospheric and Ionospheric Plasma Experiment (SNIPE)'s scientific goal is to observe spatial and temporal variations of the micro-scale plasma structures on the topside ionosphere. The four 6U CubeSats (~10 kg) will be launched into a polar orbit at ~500 km. The distances of each satellite will be controlled from 10 km to more than ~1,000 km by the formation flying algorithm. The SNIPE mission is equipped with identical scientific instruments, Solid-State Telescopes(SST), Magnetometers(Mag), and Langmuir Probes(LP). All the payloads have a high temporal resolution (sampling rates of about 10 Hz). Iridium communication modules provide an opportunity to upload emergency commands to change operational modes when geomagnetic storms occur. SNIPE's observations of the dimensions, occurrence rates, amplitudes, and spatiotemporal evolution of polar cap patches, field-aligned currents (FAC), radiation belt microbursts, and equatorial and mid-latitude plasma blobs and bubbles will determine their significance to the solar wind-magnetosphere-ionosphere interaction and quantify their impact on space weather. The formation flying CubeSat constellation, the SNIPE mission, will be launched by Soyuz-2 at Baikonur Cosmodrome in 2023.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.67-74
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• 2022

In recent, the number of real-time traffic information sources and providers has increased as increasing smartphone users and intelligent transportation system facilities installed at roadways including vehicle detection system (VDS), dedicated short-ranged communications (DSRC), and global positioning system (GPS) probe vehicle. The accuracy of such traffic information would vary with these heterogeneous information sources or spatiotemporal traffic conditions. Therefore, the purpose of this study is to propose an empirical strategy of heterogeneous information fusion to improve the accuracy of real-time traffic information. To carry out this purpose, travel speed data collection based on the floating car technique was conducted on 227 freeway links (or 892.2 km long) and 2,074 national highway links (or 937.0 km long). The average travel speed for 5 probe vehicles on a specific time period and a link was used as a ground truth measure to evaluate the accuracy of real-time heterogeneous traffic information for that time period and that link. From the statistical tests, it was found that the proposed fusion strategy improves the accuracy of real-time traffic information.

• Journal of Life Science
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• v.32 no.2
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• pp.148-154
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• 2022

Focal adhesion kinase (FAK) is known to regulate cell adhesion, migration, and mechanotransduction in focal adhesions (FAs). However, studies on how FAK activity is regulated in the plasma membrane microdomains according to the composition of extracellular matrix (ECM) proteins are still lacking. A genetically encoded fluorescence resonance energy transfer (FRET)-based biosensor can provide useful information on the activity of intracellular signals with high spatiotemporal resolution. In this study, we analyzed the FAK activities in lipid raft (detergent-resistant membrane) and non-lipid raft (non-detergent-resistant membrane) microdomains using FRET-based membrane targeting FAK biosensors (FAK-Lyn and FAK-KRas biosensors) under four different ECM protein compositions: glass, type 1 collagen, fibronectin, and laminin. Interestingly, FAK activity in response to laminin in a lipid raft microdomain was lower than that in other ECM conditions. Cells subjected to fibronectin showed higher FAK activity in a lipid raft microdomain than that in a non-lipid raft microdomain. Therefore, this study demonstrates that the FAK activity can be distinctively regulated according to the ECM type and the environment of the plasma membrane microdomains.