• Atmosphere
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• v.31 no.1
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• pp.113-141
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• 2021

The impacts of ice clouds on the energy budget of the Earth and their representation in climate models have been identified as important and unsolved problems. Ice clouds consist almost exclusively of non-spherical ice crystals with various shapes and sizes. To determine the influences of ice clouds on solar and infrared radiation as required for remote sensing retrievals and numerical models, knowledge of scattering and microphysical properties of ice crystals is required. A conventional method for representing the radiative properties of ice clouds in satellite retrieval algorithms and numerical models is to combine measured microphysical properties of ice crystals from field campaigns and pre-calculated single-scattering libraries of different shapes and sizes of ice crystals, which depend heavily on microphysical and scattering properties of ice crystals. However, large discrepancies between theoretical calculations and observations of the radiative properties of ice clouds have been reported. Electron microscopy images of ice crystals grown in laboratories and captured by balloons show varying degrees of complex morphologies in sub-micron (e.g., surface roughness) and super-micron (e.g., inhomogeneous internal and external structures) scales that may cause these discrepancies. In this study, the current idealized models representing morphologies of ice crystals and the corresponding numerical methods (e.g., geometric optics, discrete dipole approximation, T-matrix, etc.) to calculate the single-scattering properties of ice crystals are reviewed. Current problems and difficulties in the calculations of the single-scattering properties of atmospheric ice crystals are addressed in terms of cloud microphysics. Future directions to develop physically consistent ice-crystal models are also discussed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.82-88
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• 2021

Sun-induced fluorescence (SIF) retrieval using remote sensing technique has been used in an effort to understand the photosynthetic efficiency and stress condition of vegetation. Although optical devices and SIF retrieval methodologies were established in order to retrieve SIF, the SIF measurements are domestically sparse. SIF data of paddy rice w as measured in Naju, South Korea from June 10, 2020 to October 5, 2020. The SIFs based red (O2A) and far-red (O2B) w ere retrieved using a spectral fitting method and an improved Fraunhofer line depth, and photosynthetically active radiation was also produced. In addition, the SIF data was filtered considering solar zenith angle, saturation conditions, the rapid and sudden change of solar irradiance, and sun glint. The provided SIF data can help to understand a SIF product and the filtering method of SIF data can contribute to producing high-quality SIF data.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.553-566
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• 2021

River confluence is often characterized by shear layer and the associated strong mixing. In natural rivers, the main channel and its tributary can be separated by the shear layer using contrasting colors. The shear layer can be easily observed using aerial images from satellite or unmanned aerial vehicles. This study proposes a low-cost identification method extracting geographic features of the shear layer using RGB aerial image. The method consists of three stages. At first, in order to identify the shear layer, it performs image segmentation using a Gaussian mixture model and extracts the water bodies of the main channel and tributary. Next, the self-organizing map simplifies the flow line of the water bodies into the 1-dimensional curve grid. After that, the curvilinear coordinate transformation is performed using the water body pixels and the curve grid. As a result, the shear layer identification method was successfully applied to the confluence between Nakdong River and Nam River to extract geometric shear layer features (confluence angle, upstream- and downstream- channel widths, shear layer length, maximum shear layer thickness).

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.125-131
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• 2022

Recently, the prevalence of remotely managed patient care systems in medical institutions is increasing due to COVID-19. In particular, in the case of fluid monitoring, hospitals are considering introducing it as a system that can reduce patient safety and nurses' work. There are two products under development: a load cell method that measures weight and a method that detects drops of sap by infrared sensing. Although each product has differences in operation principle, sensor type, size, usage, and price, medical institutions are highly interested in the accuracy of the data obtained.In this study, two prototypes with different sensor methods were manufactured and the total amount of infusion per hour was measured to test the accuracy, which is the core of the infusion monitoring device. In addition, when there was an external movement, the change in the measured value of the sap was tested to evaluate the accuracy according to the measurement method. As a result of the experiment, there was a difference of less than 5% in the measurement value error of the two devices, and the load cell method showed a difference in the low-capacity measurement value and the infrared method in the high-capacity measurement value. As a result of this experiment, there was little difference in accuracy according to the sensor method of the infusion monitoring device, and it is considered that there is no problem in accuracy when used in a medical institution.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.194-208
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• 2021

The Hwanggang Dam in North Korea is located upstream of the Imjin River which is a shared river in the border area. It is known to have a reservoir capacity of 350 million cubic meters and releases a discharge primarily for generating hydroelectric power and partly for transferring to the Yesung River basin. Due to the supply of water from the Hwanggang Dam to another basin, the flow of the Imjin River has decreased, which has a negative impact on the water supply, river maintenance flow, water quality, and ecological environment in Korea. However, due to the special national security issue of the South and North Korea border region, the hydrological data is not shared, and the operation method of the Hwanggang Dam is unknown, so there is a risk of damage to the southern part of the downstream area. In this study, the monthly diversion as the long-term runoff concept was derived through the calibrated hydrological model based on optical remotely sensed Images and water balance analysis. As a result of the water balance analysis from January 2019 to September 2021, the average diversion of the Hwanggang Dam was 29.2m³/s, which is equivalent to 922 million tons per year and 45.6% of the annual inflow of 2.02 million tons into the Hwanggang Dam.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.88-99
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• 2022

The river network is one of the essential topographical characteristics in river management. The river network which as previously constructed by the ground surveying method has recently begun to be efficiently constructed using the remote sensing datasets. Since it is difficult to remove these obstacles such as bridges in the urban rivers, it is rare to construct the urban river networks with the various obstacles. In this study, the Sentinel-2 satellite imagery was used to develop the automatic method for detecting the urban river networks without the obstacles and with the preserved boundaries as follows. First, the normalized difference water index image was generated using the multispectral bands of the given Sentinel-2 satellite imagery, and the binary image that could classify the water body and other regions was generated. Next, the morphological operations were employed for detecting the complete river networks with the obstacles removed and the boundaries preserved. As a result of applying the proposed methodology to Han River in Seoul, the complete river networks with the obstacles removed and the boundaries preserved were well constructed.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.64-75
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• 2021

On the moon as well as the earth, one of the easiest ways to understand geological formation history of any region is to observe the stratigraphy if it is available, the order in which the strata build up. By analyzing stratigraphy, it is possible to infer what geological events have occurred in the past. Mare Nubium also has an unique normal fault called Rupes Recta that shows stratigraphy. However, a rover moving with wheels is incompetent to explore the cliff since the Rupes Recta has an inclination of 10° - 30°. Therefore, a quadruped walking robot must be employed for stable expedition. To exploration a fault with a four-legged walking robot, it is necessary to design an expedition route by taking account of whether the stratigraphy is well displayed, whether the slope of the terrain is moderate, and whether there are obstacles and rough texture in the terrain based on the remote sensing data from the previous lunar missions. For the payloads required for fault surface exploration we propose an optical camera to grasp the actual appearance, a spectrometer to analyze the composition, and a drill to obtain samples that are not exposed outward.

• Economic and Environmental Geology
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• v.55 no.2
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• pp.197-207
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• 2022

This study investigated spectroscopic exploration of Myeonsan formation, the titanium(Ti) ore hostrock, in Joseon supergroup based on machine learning technique. The mineral composition, Ti concentration, spectral characteristics of Myeonsan and non-Myeonsan formation of Joseon supergroup were analyzed. The Myeonsan formation contains relatively larger quantity of opaque minerals along with quartz and clay minerals. The PXRF analysis revealed that the Ti concentration of Myeosan formation is at least 10 times larger than the other formations with bi-modal distribution. The bi-modal concentration is caused by high Ti concentrated sandy layer and relatively lower Ti concentrated muddy layer. The spectral characteristics of Myeonsan formation is manifested by Fe oxides at near infrared and clay minerals at shortwave infrared bands. The Ti exploration is expected to be more effective on detection of hostrock rather than Ti ore because ilmenite does not have characteristic spectral features. The random-forest machine learning classification detected the Myeonsan fomation at 85% accuracy with overall accuracy of 97%, where spectral features of iron oxides and clay minerals played an important role. It indicates that spectral analysis can detect the Ti host rock effectively, and can contribute for UAV based remote sensing for Ti exploration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.