• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.235-243
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• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.171-187
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• 2022

Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• Korean Journal of Environment and Ecology
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• v.37 no.3
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• pp.209-220
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• 2023

Over the past few centuries, widespread changes to natural ecosystems caused by human activities have severely threatened biodiversity worldwide. Understanding changes in ecosystems is essential to identifying and managing threats to biodiversity. In line with this need, the IUCN Council formed the IUCN Global Ecosystem Typology (GET) in 2019, taking into account the functions and types of ecosystems. The IUCN provides maps of 10 ecosystem groups and 108 ecological functional groups (EFGs) on a global scale. According to the type classification of IUCN GET ecosystems, Korea's ecosystem is classified into 8 types of Realm (level 1), 18 types of Biome (level 2), and 41 types of Group (level 3). GETs provided by IUCN have low resolution and often do not match the actual land status because it was produced globally. This study aimed to increase the accuracy of Korean IUCN GET type classification by using land cover maps and producing maps that reflected the actual situation. To this end, we ① reviewed the Korean GET data system provided by IUCN GET and ② compared and analyzed it with the current situation in Korea. We evaluated the limitations and usability of the GET through the process and then ③ classified Korea's new Get type reflecting the current situation in Korea by using the national data as much as possible. This study classified Korean GETs into 25 types by using land cover maps and existing national data (Territorial realm: 9, Freshwater: 9, Marine-territorial: 5, Terrestrial-freshwater: 1, and Marine-freshwater-territorial: 1). Compared to the existing map, "F3.2 Constructed lacustrine wetlands", "F3.3 Rice paddies", "F3.4 Freshwater aquafarms", and "T7.3 Plantations" showed the largest area reduction in the modified Korean GET. The area of "T2.2 Temperate Forests" showed the largest area increase, and the "MFT1.3 Coastal saltmarshes and reedbeds" and "F2.2 Small permanent freshwater lakes" types also showed an increase in GET area after modification. Through this process, the existing map, in which the sum of all EFGs in the existing GET accounted for 8.33 times the national area, was modified so that the total sum becomes 1.22 times the national area using the land cover map. This study confirmed that the existing EFG, which had small differences by type and low accuracy, was improved and corrected. This study is significant in that it produced a GET map of Korea that met the GET standard using data reflecting the field conditions. 

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• (The) Research of the performance art and culture
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• no.39
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• pp.509-547
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• 2019

The cocoon breeding related national ritual ceremony exercised from the beginning time of Joseon is the 'clothing culture' that has taken its role in the ritual ceremony where it demonstrates the resolution of a state that placed importance in 'things to wear'. During the reign of King Seongjong, it enhanced the level of importance by adding the 'procedure to pick up the mulberry leaved by the queen personally'. During the reign of King Youngjo, the implication of the ritual ceremony was even more expanded that there was an new emergence of new type of national ceremony for the Joseon Era with its first ritual ceremony for woman to personally administer the memorial ceremony to the 'woman divinity' in addition to the 'Jakheonrye' procedure to personally present by the queen for the cocoon breeding. This is intended to meet the status of chingyeonguirye (farming-friendly ceremony) with King Youngjo to personally cultivate the dry field after administering Seonnongje (good harvest paying ceremony) that it is conspicuously demonstrating the importance of farming and cocoon breeding activities. As a result, the Chinjam (a type of ceremony that queen personally breeds cocoon for fabrics) related ceremonial rite that was rearranged during the reign of King Youngjo was settled into 11 ceremonial rites with the expansion of its contents. It ranges from the procedure to leave the palace for carrying out the ritual ceremony to the procedure for the crown princess and Hyebin-gung to accompany the queen, ritual for the queen to devote the Jakheonrye to exercise Chinjam, the ritual for the king to announce his royal message, johyeonui (morning assembly) exercised after completing Chinjam, it is the ritual for the queen to receive the box that contained the cocoon. This type of ritual ceremony is a significant expansion when compared with the exercise carried out earlier and it is part of characteristics displayed for ritual overhaul trend in the reign of King Youngjo. In the main procedures of these ceremonial rites, the music is accompanied and the music includes folk music, inspiration and so forth. The Chinjam related ritual ceremony in the reign of King Youngjo was established in the direction to establish it as the ritual ceremony for a woman who had the divine role of the seonjamje ritual to administer the ritual in a way of having the justification and reality to be consistent.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.497-508
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• 2023

Agricultural reservoirs are crucial structures for water resources monitoring especially in Korea where the resources are seasonally unevenly distributed. Optical and Synthetic Aperture Radar (SAR) satellites, being utilized as tools for monitoring the reservoirs, have unique limitations in that optical sensors are sensitive to weather conditions and SAR sensors are sensitive to noises and multiple scattering over dense vegetations. In this study, we tried to improve water body detection accuracy through optical-SAR data fusion, and quantitatively analyze the complementary effects. We first detected water bodies at Edong, Cheontae reservoir using the Compact Advanced Satellite 500(CAS500), Kompsat-3/3A, and Sentinel-2 derived Normalized Difference Water Index (NDWI), and SAR backscattering coefficient from Sentinel-1 by K-means clustering technique. After that, the improvements in accuracies were analyzed by applying K-means clustering to the 2-D grid space consists of NDWI and SAR. Kompsat-3/3A was found to have the best accuracy (0.98 at both reservoirs), followed by Sentinel-2(0.83 at Edong, 0.97 at Cheontae), Sentinel-1(both 0.93), and CAS500(0.69, 0.78). By applying K-means clustering to the 2-D space at Cheontae reservoir, accuracy of CAS500 was improved around 22%(resulting accuracy: 0.95) with improve in precision (85%) and degradation in recall (14%). Precision of Kompsat-3A (Sentinel-2) was improved 3%(5%), and recall was degraded 4%(7%). More precise water resources monitoring is expected to be possible with developments of high-resolution SAR satellites including CAS500-5, developments of image fusion and water body detection techniques.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.661-674
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• 2023

From the seafloor of Taean, Chungcheongnamdo Province, a ship of the Joseon Dynasty was discovered for the first time in the history of underwater excavations in Korea in 2014 and was named Mado Shipwreck No. 4. A total of 27 unused whetstones loaded as tribute were discovered on the hull of Mado No. 4, which revealed that Mado Shipwreck No. 4 was a Grain transport ship that sank while carrying tribute from Naju to Hanyang between 1417 and 1425 (King Taejong to King Sejong). All of the 27 whetstones are in the shape of narrow and long sticks. The average values of length, width, thickness, and weight are 161.5 mm, 36.1 mm, 22.7 mm, and 253.2 g, respectively. The result of X-ray diffraction analysis shows that the constituent minerals are quartz, alkali feldspar, and plagioclase, which is similar to that of the high-resolution digital stereomicroscope analysis. The average porosity of Mado-2672 and 2673 is 2.69% and 1.78%, respectively, and the average surface hardness is 807.2HLD and 834.5HLD, respectively. It is interpreted that if the porosity increases beyond a certain level, it affects the decrease in surface hardness. All of these are made of feldspathic sandstones with an average SiO₂ content of 74.51% and were confirmed to be suitable as grindstones. They are all medium whetstones when classified based on the SiO₂ content. These whetstones are small in size and weight and are convenient to carry, so they are presumed to be a type of non-stationary whetstone, and are estimated to have been mainly used in the fields such as weapon polishing and craft production during the Joseon Dynasty.