• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1447-1460
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• 2021

Urbanization increases the amount of impervious surface and artificial heat emission, resulting in urban heat island (UHI) effect. Local climate zones (LCZ) are a classification scheme for urban areas considering urban land cover characteristics and the geometry and structure of buildings, which can be used for analyzing urban heat island effect in detail. This study aimed to examine the UHI effect by urban structure in Suwon and Daegu using the LCZ scheme. First, the LCZ maps were generated using Landsat 8 images and convolutional neural network (CNN) deep learning over the two cities. Then, Surface UHI (SUHI), which indicates the land surface temperature (LST) difference between urban and rural areas, was analyzed by LCZ class. The results showed that the overall accuracies of the CNN models for LCZ classification were relatively high 87.9% and 81.7% for Suwon and Daegu, respectively. In general, Daegu had higher LST for all LCZ classes than Suwon. For both cities, LST tended to increase with increasing building density with relatively low building height. For both cities, the intensity of SUHI was very high in summer regardless of LCZ classes and was also relatively high except for a few classes in spring and fall. In winter the SUHI intensity was low, resulting in negative values for many LCZ classes. This implies that UHI is very strong in summer, and some urban areas often are colder than rural areas in winter. The research findings demonstrated the applicability of the LCZ data for SUHI analysis and can provide a basis for establishing timely strategies to respond urban on-going climate change over urban areas.

• Journal of Mushroom
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• v.19 no.3
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• pp.234-245
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• 2021

To extend the shelf life of king oyster mushrooms for export, we investigated the impacts of mushroom quality grade, fruiting body trimming, and packaging method (tray container sealed packaging vs string-tied OPP bag packaging). Quality is divided into two grades: 1^st grade, which is mushrooms adapted by lowering the cultivation temperature to 9~11℃, and 2^nd grade, mushrooms held at 13~15℃ prior to harvest. Using selected 1^st and 2^nd grade mushrooms, 3 treatments were carried out to assess effects of trimming and packaging method. Test groups included 1) trimming plus string-tied OPP bag packaging (Cut & OPP), 2) no trimming plus string-tied OPP bag packaging (Uncut & OPP), and 3) trimming plus tray container sealing packaging (Cut & Tray). Gas composition inside the packaging, changes in quality factors, and sensory evaluation for fresh quality were performed over 42 days of 0℃ storage. Overall freshness was best maintained in the following order: Cut & Tray > Cut & OPP > Uncut & OPP for both 1^st and 2^nd grade mushrooms. The shelf-life of 1st grade mushrooms was about 30 days for Cut & Tray, 28 days for Cut & OPP, and 21 days for Uncut & OPP. The shelf-life of 2^nd grade mushrooms was about 22 days for Cut & Tray, 17 ays for Cut & OPP, and 14 days for Uncut & OPP. Factors affecting fresh mushroom quality included browning of cap and stalk, and mushroom decay index. Browning of the lower part of the stalk, with related color change as noted in a^* and b^* values were the main factors indicating quality deterioration of king oyster mushrooms.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1029-1042
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• 2021

As part of the next-generation Compact Advanced Satellite 500 (CAS500) project, CAS500-4 is scheduled to be launched in 2025 focusing on the remote sensing of agriculture and forestry. To obtain quantitative information on vegetation from satellite images, it is necessary to acquire surface reflectance through atmospheric correction. Thus, it is essential to develop an atmospheric correction method suitable for CAS500-4. Since the absorption and scattering characteristics in the atmosphere vary depending on the wavelength, it is needed to analyze the sensitivity of atmospheric correction parameters such as aerosol optical depth (AOD) and water vapor (WV) considering the wavelengths of CAS500-4. In addition, as CAS500-4 has only five channels (blue, green, red, red edge, and near-infrared), making it difficult to directly calculate key parameters for atmospheric correction, external parameter data should be used. Therefore, thisstudy performed a sensitivity analysis of the key parameters (AOD, WV, and O₃) using the simulated images based on Sentinel-2 satellite data, which has similar wavelength specifications to CAS500-4, and examined the possibility of using the products of GEO-KOMPSAT-2A (GK2A) as atmospheric parameters. The sensitivity analysisshowed that AOD wasthe most important parameter with greater sensitivity in visible channels than in the near-infrared region. In particular, since AOD change of 20% causes about a 100% error rate in the blue channel surface reflectance in forests, a highly reliable AOD is needed to obtain accurate surface reflectance. The atmospherically corrected surface reflectance based on the GK2A AOD and WV was compared with the Sentinel-2 L2A reflectance data through the separability index of the known land cover pixels. The result showed that two corrected surface reflectance had similar Seperability index (SI) values, the atmospheric corrected surface reflectance based on the GK2A AOD showed higher SI than the Sentinel-2 L2A reflectance data in short-wavelength channels. Thus, it is judged that the parameters provided by GK2A can be fully utilized for atmospheric correction of the CAS500-4. The research findings will provide a basis for atmospheric correction of the CAS500-4 in the future.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1739-1756
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• 2021

Atmospheric nitrogen dioxide (NO₂) is mainly caused by anthropogenic emissions. It contributes to the formation of secondary pollutants and ozone through chemical reactions, and adversely affects human health. Although ground stations to monitor NO₂ concentrations in real time are operated in Korea, they have a limitation that it is difficult to analyze the spatial distribution of NO₂ concentrations, especially over the areas with no stations. Therefore, this study conducted a comparative experiment of spatial interpolation of NO₂ concentrations based on two linear-regression methods(i.e., multi linear regression (MLR), and regression kriging (RK)), and two machine learning approaches (i.e., random forest (RF), and support vector regression (SVR)) for the year of 2020. Four approaches were compared using leave-one-out-cross validation (LOOCV). The daily LOOCV results showed that MLR, RK, and SVR produced the average daily index of agreement (IOA) of 0.57, which was higher than that of RF (0.50). The average daily normalized root mean square error of RK was 0.9483%, which was slightly lower than those of the other models. MLR, RK and SVR showed similar seasonal distribution patterns, and the dynamic range of the resultant NO₂ concentrations from these three models was similar while that from RF was relatively small. The multivariate linear regression approaches are expected to be a promising method for spatial interpolation of ground-level NO₂ concentrations and other parameters in urban areas.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Korean Journal of Ichthyology
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• v.32 no.4
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• pp.210-221
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• 2020

Since the introduction of Israeli carp into Korea for farming in 1973, there are no breeding studies on developing Korea Israeli carp (domestic) so far. This study performed gene-based cross-breeding studies to restore genetic diversity of lowered Israeli carp through continuous inbreeding, and for rapid growth and better scales. This study produced four cross-breeding groups (F1) using Koean Israeli carp and Chinese Songpu mirror carp for the improvement of growth and scale of Israeli carp in Korea. And mating scheme for breeding groups was set in consideration of the morphological analysis and genetic distance of broodstock. In addition, this study used microsatellite markers and genotype data to analyze genetic diversity and parentage analysis. As a result, the average N_A and H_E values of Korean select broodstock are 8.3 and 0.743, and F1 is 13.0 and 0.764. This study shows that the genetic diversity of F1 has been recovered over Korean Israeli carp through breeding between Korean Israeli carp and Chinese Songpu mirror carp. Common Israeli carp in Korea reached 1.7 kg in 17 months, and improved Israeli carp reached to 2.2 kg. The KC (Korea×China, KC) group was 2.52 and broodstock group was 3.15. F1 showed lower scale score (0.63) than broodstock. The improved carp (F1; CK, KC) had 20% better scales than the parent group (F0), which improved 27% in weight and 25% in scales compared to common Israeli carp. The Israeli carp developed by the genetics-based breeding grew quicker and had improved genetic diversity and fewer scales, which will be of great value for Korean Israeli aquaculture industry due to good marketability.

• Journal of Korean Society of Spine Surgery
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• v.25 no.4
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• pp.160-168
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• 2018

Study Design: Retrospective study of prospectively-collected data. Objectives: To determine the factors associated with conversion from conservative to surgical treatment in single-level lumbar spinal stenosis patients. Summary of Literature Review: Various reports have presented clinical outcomes after the surgical and nonsurgical treatment of spinal stenosis. However, few reports have investigated factors predicting conversion to surgery during the course of conservative treatment. Materials and Methods: We analyzed 40 patients who visited our hospital from May 2010 to May 2015 and were traceable for at least 3 years after being advised to undergo surgery following 3 months of conservative treatment. Of these patients, 20 underwent surgery and 20 did not. We then investigated the factors associated with conversion to surgical treatment. Clinical assessments were conducted using a questionnaire, and the overall area of the spinal canal and the muscle area within the spinal canal were measured using magnetic resonance imaging. Results: The average area of the spinal canal was $81.40{\pm}53.61mm^2$ in the surgical group, compared to $127.75{\pm}82.55mm^2$ in the nonsurgical group (p=0.042). The muscle area in the spinal canal was $5.17{\pm}1.30cm^2$ in the surgical group, whereas it was $6.40{\pm}1.56cm^2$ in the nonsurgical group (p=0.010). The patients in the surgical group were more likely to have experienced repetitive strain and to have frequently visited health clubs (p=0.047, p=0.037, respectively). However, regular stretching was more common in the nonsurgical group (p=0.028). Conclusions: The factors associated with conversion to surgical treatment were a narrow spinal canal, a small muscle area within the spinal canal, visiting health clubs, repetitive sprain, and not stretching. A small muscle area within the spinal canal can be considered as a key factor related to surgical conversion.

• Journal of Korean Philosophical Society
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• v.130
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• pp.277-304
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• 2014

Der vorliegende Beitrag zielt darauft ab, zwei Perspektiven $f{\ddot{u}}r$ die Kunst bei Kant und Nietzsche und ihre Schlussfolgerungen zu $er{\ddot{o}}rtern$. Kants Kritik der Urteilskraft hat eine enorme Rolle in der Geschichte der ${\ddot{A}}sthetik$ gespielt. $F{\ddot{u}}r$ Kant sollen ${\ddot{a}}sthetische$ Urteile ebenso wie Erkenntnis- und Moralurteile $allgemeing{\ddot{u}}ltig$ sein, obwohl sie auf einem $pers{\ddot{o}}nlichen$ Geschmack beruhen. Die $Allgemeing{\ddot{u}}ltigkeit$ des $Sch{\ddot{o}}nen$ sei $m{\ddot{o}}glich$, weil sie nicht auf dem Gegenstand, sondern auf dem transzendentalen Subjekt basiere. Die $sch{\ddot{o}}ne$ Kunst als Kunst des Genies soll uns wie die $Natursch{\ddot{o}}nheit$ ohne Interesse wohlgefallen. Nietzsches Stellungnahme zu Kants ${\ddot{A}}sthetik$ ist sehr kritisch. Nietzsches erster Kritikpunkt richtet sich gegen das 'interesselose Wohlgefallen'. Gegen Kant behauptet Nietzsche, dass die $Sch{\ddot{o}}nheit$ sehr wohl mit Interesse verbunden ist. Grund $daf{\ddot{u}}r$ ist, dass das $Sch{\ddot{o}}ne$ wesentlich aus dem Willen zur Macht entspringt. Der zweite Kritikpunk Nietzsches liegt darin, dass in Kants ${\ddot{A}}sthetik$ die Moral im Vordergrund steht. Das $Sch{\ddot{o}}ne$ ist $f{\ddot{u}}r$ Kant durch die Moral gerechtfertigt. Nietzsche dreht diese Stellung der Moral zur Kunst um. Der dritte Kritikpunkt Nietzsches ist, dass Kant statt von der Erfahrung des $K{\ddot{u}}nstlers$ (Schaffenden) aus das ${\ddot{a}}sthetische$ Problem zu betrachten, allein vom Zuschauer (Empfangenden) aus ${\ddot{u}}ber$ die Kunst und das $Sch{\ddot{o}}ne$ nachgedacht habe. $F{\ddot{u}}r$ Nietzsche ist die Kunst $prim{\ddot{a}}r$ vom $K{\ddot{u}}nstler$ aus zu verstehen. Nietzsches Physiologie der Kunst ist mit dem Begriff 'Leib' $verkn{\ddot{u}}pft$, d.h. Nietzsche behauptet, dass physiologische und ${\ddot{a}}sthetische$ Prozesse wesentlich $zusammenh{\ddot{a}}ngen$. Die Schlussfolgerung der Physiologie der Kunst lautet: erstens, jeder Mensch ist $K{\ddot{u}}nstler$, sofern er schaffend ist, und zweitens, die Welt selbst ist nichts als Kunst. Nietzsches Physiologie der Kunst hat einen $gro{\ss}en$ Einfluss auf die $gegenw{\ddot{a}}rtige$ Kunst $ausge{\ddot{u}}bt$ und kein anderer Philosoph hat auf die $gegenw{\ddot{a}}rtige$ Kunst nachaltiger gewirkt.