• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.502-514
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• 2023

This study was conducted to understand the long-term changes in soil physiochemical properties and seedling growth in Larix kaempferi (larch) stands planted in clear-cut larch and Pinus rigida (pine) forest soils over an 11-year period after reforestation. Two-year-old bare-root larch seedlings were planted in 2009-2010 at a density of 3,000 seedlings ha^-1 in clear-cut areas that harvested larch (Chuncheon and Gimcheon) and pine (Wonju and Gapyeong) stands. We analyzed the physiochemical properties of the mineral soils sampled at 0-20 cm soil depths in the planting year, and the 3^rd, 7^thand 11^th years after planting, and we measured seedling height and root collar diameter in those years. We found significant differences in soil silt and clay content, total carbon and nitrogen concentration, available phosphorus, and cation exchangeable capacity between the two stands; however, seedling growth did not differ. The mineral soil was more fertile in Gimcheon than in the other plantations, while early seedling growth was greatest in Gapyeong. The seedling height and diameter at 11 years after planting were largest in Wonju (1,028 tree ha^-1) and Chuncheon (1,359 tree ha^-1) due to decreases in stand density after tending the young trees. The soil properties in all plantations were similar 11 years after larch planting. In particular, the high sand content and high available phosphorus levels (caused by soil disturbance during clear-cutting and planting) showed marked decreases, potentially due to soil organic matter input and nutrient uptake, respectively. Thus, early reforestation after clear-cutting could limit nutrient leaching and contribute to soil stabilization. These results provide useful information for nutrient management of larch plantations.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.3
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• pp.134-144
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• 2009

Paleoproductivity changes in the central part of the Bering Sea since the last glacial period were reconstructed by analyzing opal and total organic carbon (TOC) content and their mass accumulation rate (MAR) in sediment core PC23A. Ages of the sediment were determined by both AMS $^{14}C$ dates using planktonic foraminifera and Last Appearance Datum of radiolaria (L. nipponica sakaii). The core-bottom age was calculated to reach back to 61,000 yr BP. and some of core-top was missing. Opal and TOC contents during the last glacial period varied in a range of 1-10% and 0.2-1.0%, and their average values are 5% and 0.7%, respectively. In contrast, during the last deglaciation, opal and TOC contents varied from 5 to 22% and from 0.8 to 1.2%, respectively, with increasing average values of 8% and 1.0%. Opal and TOC MAR were low ($1gcm^{-2}kyr^{-1}$, $0.2gcm^{-2}kyr^{-1}$) during the last glacial period, but they increased (>5 and >$1gcm^{-2}kyr^{-1}$) during the last deglaciation. High diatom productivity during the last deglaciation was most likely attributed to the elevated nutrient supply to the sea surface resulting from increased melt water input from the nearby land and enhanced Alaskan Stream injection from the south under the restricted sea-ice and warm condition during the rising sea level. On the contrary, low productivity during the last glacial period was mainly due to decreased Alaskan Stream injection during the low sea-level condition as well as to extensive development of sea ice under low-temperature seawater and cold environment.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of the East Asian Society of Dietary Life
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• v.19 no.6
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• pp.856-868
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• 2009

This study was conducted to investigate causes for health problems among college women by analyzing factors related to their dietary habits, physical development, health habits, and blood parameters. The subjects were ages 20 to 24 years, lived in the Seoul area and were randomly selected during March, 2008 to August, 2009. The average height and weight of the overall subjects were $162.02{\pm}4.89\;cm$ and $53.96{\pm}7.00\;kg$, respectively. According to a 3-point assessment scale for the subjects' dietary habits, the average point value was 21.2. The percentage of subjects that ate breakfast daily was only 30.5%, and they omitted regular meals at least once a week. Approximately 83.5% of the subjects reported eating out often or frequently, and preferred Korean foods when they ate out. The subjects had interim meals (snacks) one or two times daily, and 40.4% of them preferred unbalanced meals. As their interim meals, among the 'good' group, ate breaded potatoes (39.3%), carbonated beverages, and ice cream (36.8%), whereas the 'poor' group, drank milk and ate dairy products (38.0%) as well as fast food and fried food (22.8%). Intakes of energy, fat, vitamins $B_2$ and $B_6$, niacin, folic acid, calcium, iron, zinc, and phosphorus were higher in the 'poor' group. The average hemoglobin level ($13.77{\pm}1.00\;g/dL$) among the subjects was within normal range; while 2.7% of subjects had hemoglobin levels under 11.1 g/dL (standard value) and were examined as anemic. The degree of interest in health was 24.5% higher among the subjects who had poor dietary habits. In contrast, among those who had good dietary habits, 49.6% reported they had no interest in regular exercise. The subjects reported that regular meals, nutrient intake, sufficient rest, and sleep as necessary to maintain health. The average amount of sleep obtained by the subjects was 6~8 hours. Among the 'poor' group, 36.2% reported that they exercised regularly, whereas 18.5% of the subjects in the 'good' group reported regular exercise (p<0.05). In conclusion, it appears necessary to provide nutrition education through teaching and to promote nutrition and health to college women so they can control their individual health status and create practicable dietary plans.

• Journal of the East Asian Society of Dietary Life
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• v.10 no.2
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• pp.116-128
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• 2000

The purpose of this study is to analyze the nutrient intakes and growth development of rural middle school students provided with and without the national school lunch program(NSLP). The subjects consisted of 340 rural middle school students provided with(n=177) and without(n=163) NSLP. Anthropometric measurements were taken for body weight, height, triceps skinfold thickness and percentage of body fat, and nutrient intakes were assessed by food record method. The results of this study were summarized as follows: There was no significant difference in the height, body weight girls provided with (155.8cm 47.2kg) and without (156.0cm, 49.7kg) NSLP. Total energy intakes of boys were 2123kca1 in with NSLP and 1857kca1 in without NSLP. Total energy intakes of girls were 1913kca1 in with NSLP and 1814kca1 in without NSLP. Total daily energy was provided in the ratio of 19.1%, 39.8%, 32.4% and 8.7% by breakfast, lunch, dinner and snacks in the with NSLP and 17.5%, 32.0%, 34.8% and 15.7% in without NSLP, respectively. Phosphorus, vitamin A, vitamin E, ascorbic acid, thiamin, riboflavin, niacin intakes were above the RDA in with NSLP. In without NSLP, phosphorus, vitamin E, thiamin intakes were above the RDA. however, calcium. iron, vitamin A, vitamin B$_{6}$ were less than the RDA. The study showed that total daily energy and nutrient intakes were significantly higher in students provided with than without school-lunch. Thus, the school-lunch program is recommended and necessary to improve the nutritional status of middle school students.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.11
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• pp.1649-1657
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• 2016

The purpose of this study was to investigate the body mass index (BMI), dietary intake attitudes, and nutrient intake status according to sugar-containing food intake frequency of 409 college students in Gyeonggi-do. Subjects were categorized into three groups according to sugar-containing food intake frequency: rare intake group (n=113), average intake group (n=195), and frequent intake group (n=101). The average height and weight (P<0.001) of each group were $163.8{\pm}0.11cm$ and $52.9{\pm}8.6kg$, $164.4{\pm}0.1cm$ and $56.2{\pm}6.4kg$, and $167.9{\pm}0.1cm$ and $68.0{\pm}15.7kg$, respectively. The average BMIs of the groups were $19.6{\pm}2.3$, $20.7{\pm}0.8$, and $24.0{\pm}2.7$, respectively (P<0.001). Dietary intake attitude scores of the groups were $30.73{\pm}5.68$, $30.11{\pm}5.51$, and $28.00{\pm}5.31$, respectively (P<0.001). As a result of nutrient intake status, daily averages of energy and carbohydrate intake of the frequent intake group were significantly higher than those of the rare intake group (P<0.05). On the other hand, vitamin A, vitamin $B_1$, and vitamin C intakes of the rare intake group were significantly higher than those of the frequent intake group (P<0.05). Using multiple regression analysis, we found that BMI was the most significant variable affecting sugar-containing food intake. Therefore, nutrition education is necessary to improve nutrient intake while considering sugar intake for maintenance of healthy weight.

• Journal of agricultural medicine and community health
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• v.49 no.3
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• pp.257-270
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• 2024

Objective: This study aimed to empirically evaluate the effectiveness of chronic disease management services utilizing ICT for patients with chronic illnesses. Methods: From May to December, 2023, 452 people who were diagnosed with hypertension and diabetes at 9 participating public health centers were provided with customized health care services for 24 weeks, and 15 performance indicators were analyzed to evaluate their effectiveness. Results: Health behavior indicators and health risk factors decreased before and after participation in the project, blood pressure control rate, hypertension and diabetes management rate, medication compliance, weight, BMI, BP, WC, FBG, and HDL-cholesterol improved(p<0.001). Service factors that influence the improvement of health behaviors included the number of activity monitor transmissions(p=0.049), confirmed concentrated consultations on physical activity(p=0.003) and nutrition(p=0.005), and the adherence to medication missions for hypertension(p=0.020). As for service factors influencing chronic disease management, the improvement in blood pressure regulation rate was due to the number of times the blood pressure monitor was linked(p=0.004), and the number of confirmed intensive consultations on physical activity(p=0.026), and nutrition(p=0.049); the improvement in hypertension control rate was due to the number of times the activity monitor and blood pressure monitor were linked(p<0.001), and the number of hypertension medication missions carried out (p=0.004); and the improvement in diabetes control rate was due to the number of times the blood pressure monitor(p=0.022) and blood sugar system were linked(p=0.017). Conclusion: Although this study has limitations as a comparative study before and after the service, it has proved that chronic disease management using ICT has a positive effect on improvement of health behavior indicator, reduction of health risk factors, hypertension, diabetes management index, weight, BMI, TG, BP, FBG improvement.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.8
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• pp.995-1009
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• 2007

The purpose of this study was to investigate the dietary habits, behaviors, and food consumption frequency according to gender and obesity level among middle school students in the Jeonju area. Subjects for the questionnaire were 450 middle school students (male 255, female 195) and were classified as either obese students (n=150 or non-obese students (n=299) by the obesity assessment method. The results were analyzed with SAS program (Version 9.1), and were as follows. 1. Dietary behaviors were significantly different in the rate of 'Skipping breakfast (p<0.05)', 'Duration of meal time (min) (p<0.05)' and 'Unbalanced diet (p<0.01)' between males and females. Dietary habits and behaviors also differed significantly for the rate of ‘Taste preferences (p<0.05)’, and 'Unbalanced diet (p<0.01)' between obese students and non-obese students. 2. Food consumption frequency per week was as follows. First, males were significantly higher than females in 'Instant noodle (p<0.05)', 'Milk (p<0.01)', and 'Soda pop (p<0.01)'; on the other hand females were significantly higher than males in 'Chocolate, Candy (p<0.01)'. Second, non-obese students were significantly higher than obese students in 'Instant noodle (p<0.05)', 'Hamburger, Pizza (p<0.05)', and 'Chocolate, Candy (p<001)'. Especially, non-obese male students were higher in 'Instant noodle (p<0.05)' and 'Hamburger, Pizza (p<0.05)'; non-obese female students were higher in 'Chocolate, Candy (p<0.01)'. In conclusion, an action program is needed to encourage healthful dietary behaviors, increased physical activity, and forming good lifelong habits.