• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1165-1178
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• 2018

Collapse of an Antarctic ice shelf and its flow velocity changes has the potential to reduce the restraining stress to the seaward flow of the Antarctic Ice Sheet, which can cause sea level rising. In this study, variations in ice velocity from 2000 to 2017 for the Nansen Ice Shelf in East Antarctica that experienced a large-scale collapse in April 2016 were analyzed using Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) images. To extract ice velocity, image matching based on orientation correlation was applied to the image pairs of blue, green, red, near-infrared, panchromatic, and the first principal component image of the Landsat multispectral data, from which the results were combined. The Landsat multispectral image matching produced reliable ice velocities for at least 14% wider area on the Nansen Ice Shelf than for the case of using single band (i.e., panchromatic) image matching. The ice velocities derived from the Landsat multispectral image matching have the error of $2.1m\;a^{-1}$ compared to the in situ Global Positioning System (GPS) observation data. The region adjacent to the Drygalski Ice Tongue showed the fastest increase in ice velocity between 2000 and 2017. The ice velocity along the central flow line of the Nansen Ice Shelf was stable before 2010 (${\sim}228m\;a^{-1}$). In 2011-2012, when a rift began to develop near the ice front, the ice flow was accelerated (${\sim}255m\;a^{-1}$) but the velocity was only about 11% faster than 2010. Since 2014, the massive rift had been fully developed, and the ice velocity of the upper region of the rift slightly decreased (${\sim}225m\;a^{-1}$) and stabilized. This means that the development of the rift and the resulting collapse of the ice front had little effect on the ice velocity of the Nansen Ice Shelf.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1479-1488
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• 2018

On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Korean Journal of Heritage: History & Science
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• v.54 no.2
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• pp.22-37
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• 2021

The wind chime is a longstanding Jangeomgu (majestic article) found in Korea, China, and Japan. However, basic research on wind chimes is currently inadequate as it is difficult to estimate the time of production, and there are few relics. Therefore, this research morphologically classifies the eight bronze wind chimes decorating the baldachin of the Stone Standing Maitreya Bodhisattva of Gwanchoksa Temple, Nonsan. Based on this, the manufacturing techniques and production period are scientifically demonstrated. The synthesis of the research results reveals that the structure and characteristics of the wind chimes of the Stone Standing Maitreya Bodhisattva of Gwanchoksa Temple, Nonsan differ depending on their location on the baldachin. The four large-sized wind chimes on the lower-baldachin were manufactured by casting a Cu-Sn-Pb alloy, and they are estimated to have been made during the early period of Goryeo. The two medium-sized wind chimes of the upper-baldachin's northern direction were manufactured through forging a Cu-Sn or Cu-Sn-Pb alloy, and they appear to have a similar structure to the cylindrical wind chimes appearing during the latter period of Goryeo and the Joseon period. The two small-sized wind chimes of the upper-baldachin's southern direction were manufactured by casting a Cu-Sn-Pb alloy containing Zn, and based on the chemical composition of the alloy and the shape of the clapper, they are estimated to have been manufactured during the latter period of Joseon. Through the observation of microstructures and a chemical composition analysis, it is demonstrated that two wind chimes of the lowerbaldachin were manufactured by casting and slow cooling the alloy with an alloy ratio of Cu:Sn:Pb≒80:15:5. In addition, it is estimated that the wind chimes of the upper-baldachin's northeast direction were manufactured by forging an alloy of Cu-Sn with a similar alloy ratio to that of forged high tin bronze. The results of a comparative analysis of prior research on domestic wind chimes confirm that two wind chimes of the lower-baldachin have a similar composition ratio to the wind chime excavated from Wolnamsaji in Gangjin, containing an amount of tin that corresponds with ancient records. Having a similar alloy ratio to forged high tin bronze, the wind chimes of the upper-baldachin's northeast direction are the only instances among all of the wind chimes that have been examined to date that were manufactured using this forging method. The purpose of this research is to collect baseline data to verify and classify the manufacturing period of wind chimes according to their morphological characteristics based on scientific evidence. It is hoped that this data can be utilized for the restoration and conservation processes of the wind chimes of the Stone Standing Maitreya Bodhisattva of Gwanchoksa Temple, Nonsan.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.189-198
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• 2022

In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO₂) column density in the SO₂ retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO₂ retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO₂ slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO₂ column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO₂ column density retrieved by applying each offset correction factor to the GEMS operational SO₂ retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO₂ column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO₂ standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO₂ column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO₂ retrieval was relatively stable compared to the SO₂ retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO₂ retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.853-865
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• 2022

In this study, from August to October 2019, we conducted a survey of the spatial distribution and dominant species of macrobenthos on the rocky intertidal zones of 38 specified islands distributed along the southern coast of Korea. On the basis of observation made using 50 × 50 cm quadrats, we identified a total of 80 species, among which, Mollusca were the most abundant fauna, with 54 species that accounted for 67.4% of the total, followed by Crustacea with 15 species (18.7%). The recorded numbers of Cnidaria, Porifera, and Echinodermata species ranged from 1 to 6. In terms of the regional patterns of species richness, specified islands in Yeosu were found to be the most species rich, supporting 61 species, whereas islands in Hadong, Namhae, and Chujado were found to have a similar level of species richness, ranging from 42 to 46 species. Islands in Boseong and Goheung were home to the fewest species, with only 29 species being recorded. At the sampling station scale, we noted a considerable difference in faunal richness, ranging from 6 (St. 6) to 33 (St. 20) species. Among the recorded species, Echinolittorina radiata was identified as the dominant species on 15 specified islands, with the next most abundant species being Tetraclita japonica, considered an indicator species of climate change, which was recorded on 11 islands. In terms of frequency, E. radiata, found on 36 islands, was identified as the most frequently occurring species, followed by Reishia clavigera (30 islands), Mytilisepta virgata (29), Nerita japonica (28), Ligia. exotica (27), and Littorina brevicula (26). Of the 80 species identified, 9, 4, and 2 species of Mollusca, Crustacea, and Cnidaria, respectively, are classified as Marine fauna of accepted foreign export, whereas 50 are Red List species, 44 are species of Least Concern, 3 are Data Deficient species, and 1 species was not evaluated. However, during the survey, we found no Near Threatened or Not Applicable species. On the basis of the findings of this survey, it would appear that the abundance and richness of macrobenthic fauna inhabiting the rocky intertidal zones of specified islands along the southern coast of Korea differ according to different habitat conditions, particularly with respect to the duration of exposure and the extent and properties of the substrata. The findings of this study will provide baseline data for future monitoring and management of specified islands in Korea.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.4
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• pp.409-421
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• 2022

Achieving a highly resolved spatial distribution of Mn-bearing minerals and elements in the natural ferromanganese nodules can provide detailed knowledge of the temporal variations of geochemical conditions affecting the formation processes of nodules. While a recent study utilizing Raman spectroscopy has reported the changes in the manganate mineral phases with growth for spherical nodules from the Arctic Sea, the distributions of minerals and elements in the nodules from the shallow Arctic Sea with non-spherical forms have not yet fully elucidated. Here, we reported the micro-laser Raman spectra with varying data acquisition points along three different profiles from the center to the outermost rim of the non-spherical ferromanganese nodules collected from the East Siberian Sea (~73 m). The elemental distributions in the nodule (such as Mn, Fe, etc.) were also investigated by energy dispersive X-ray spectroscopy (EDS) analysis to observe the internal structure and mineralogical details. Based on the microscopic observation, the internal structures of a non-spherical nodule can be divided into three different regions, which are sediment-rich core, iron-rich substrate, and Mn-Fe layers. The Raman results show that the Mn-bearing mineral phases vary with the data acquisition points in the Mn-Fe layer, suggesting the changes in the geochemical conditions during nodule formation. In addition, we also observe that the mineral composition and structural characteristics depend on the profile direction from the core to the rim. Particularly, the Raman spectra obtained along one profile show the lack of Fe-(oxy)hydroxides and the noticeably high crystallinity of Mn-bearing minerals such as birnessite and todorokite. On the other hand, the spectra obtained along the other two profiles present the presence of significant amount of amorphous or poorly-ordered Fe-bearing minerals and the low crystallinity of Mn-bearing minerals. These results suggest that the diagenetic conditions varied with the different growth directions. We also observed the presence of halite in several layers in the nodule, which can be evidence of the alteration of seawater after nodule formation. The current results can provide the opportunity to obtain detailed knowledge of the formation process and geochemical environments recorded in the natural non-spherical ferromanganese nodule.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.297-305
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• 2023

The recycled irrigation is a type of irrigation that uses downstream water to fulfill irrigation demand in the upstream agricultural areas; the used irrigation water returns back to the downstream. The recycled irrigation is advantageous for securing irrigation water for plant growth, but the returned water typically contains high levels of nutrients due to excess nutrients inputs during the agricultural activities, potentially deteriorating stream water quality. Therefore, quantitative assessment on the effect of the recycled irrigation on the stream water quality is required to establish strategies for effective irrigation water supply and water quality management. For this purpose, a watershed model is generally used; however no functions to simulate the effects of the recycled irrigation are provided in the existing watershed models. In this study, we used multi-reservoir model coupled with the Hydrological Simulation Program-Fortran (HSPF) to estimate the effect of the recycled irrigation on the stream water quality. The study area was the Gwangok stream watershed, a subwatershed of Gyeseong stream watershed in Changnyeong county, Gyeongsangnam-do. The HSPF model was built, calibrated, and used to produce time series data of flow and water quality, which were used as hypothetical observation data to calibrate the multi-reservoir model. The calibrated multi-reservoir model was used for simulating the recycled irrigation. In the multi-reservoir model, the Gwangok watershed consisted of two subsystems, irrigation and the Gwangok stream, and the reactions (plant uptake, adsorption, desorption, and decay) within each subsystem, and fluxes of water and materials between the subsystems, were modeled. Using the developed model, three scenarios with different combinations of the operating conditions of the recycled irrigation were evaluated for their effects on the stream water quality.

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