• Journal of the Korean earth science society
• /
• v.41 no.6
• /
• pp.575-587
• /
• 2020

Meteorological phenomena are observed by the Korea Meteorological Administration in a variety of ways (e.g., surface, upper-air, marine, ocean, and aviation). However, there are limits to the meteorological observation of the planetary boundary layer (PBL) that greatly affects human life. In particular, observations using a sonde or aircraft require significant observational costs in economic terms. Therefore, the goal of this study was to measure and analyze the meteorological factors of the vertical distribution of the see-land breeze among local meteorological phenomena using meteorological drones. To investigate the spatial distribution of the see-land breeze, a same integrated meteorological sensor was mounted on each drone at three different points (seaside, bottom of mountain, and mountainside), including the Boseong tall tower (BTT) at the Boseong Standard Weather Observatory (BSWO) in the Boseong region. Vertical profile observations for air temperature, relative humidity, wind direction, wind speed, and air pressure were conducted up to 400 m every 30 minutes from 1100 LST to 1800 LST on August 4, 2018. The spatial characteristics of meteorological phenomena for temperature, relative humidity, and atmospheric pressure were not shown at the four points. Strong winds (~8 m s-1) were observed from the midpoint (~100 m) at strong solar radiation hour, and in the afternoon the wind direction changed from the upper layer at the inland area to the west wind. It is expected that the analysis results of the lower atmospheric layer observed using the meteorological drone may help to improve the weather forecast more accurately.

• Korean Journal of Remote Sensing
• /
• v.34 no.3
• /
• pp.439-450
• /
• 2018

The lineament is a linear or curved terrain element to discriminate adjacent geological structures in each other. It has been widely used for analysis of geology, mineral exploration, natural disasters, and earthquake, etc. In the past, the lineament has been extracted using cartographic map or field survey. However, it is possible to extract more efficiently the lineament for a very wide area thanks to development of remote sensing technique. Remotely sensed observation by aircraft, satellite, or digital elevation model (DEM) has been used for visual recognition for manual lineament extraction. Automatic approaches using computer science have been proposed to extract lineament more objectively. In this study, we evaluate the characteristics of lineament which is automatically extracted with respect to difference of spatial resolution of DEM. We utilized two types of DEM: one is Shuttle Radar Topography Mission (SRTM) with spatial resolution of about 90 m (3 arc sec), and the other is the latest world DEM of TerraSAR-X add-on for Global DEM with 12 m spatial resolution. In addition, a global DEM was resampled to produce a DEM with a spatial resolution of 30 m (1 arc sec). The shaded relief map was constructed considering various sun elevation and solar azimuth angle. In order to extract lineament automatically, we used the LINE module in PCI Geomatica software. We found that predominant direction of the extracted lineament is about $N15-25^{\circ}E$ (NNE), regardless of spatial resolution of DEM. However, more fine and detailed lineament were extracted using higher spatial resolution of DEM. The result shows that the lineament density is proportional to the spatial resolution of DEM. Thus, the DEM with appropriate spatial resolution should be selected according to the purpose of the study.

• The Korean Journal of Community Living Science
• /
• v.17 no.4
• /
• pp.151-161
• /
• 2006

This study was made to find out how health practice affect on nutrition status of the college freshmen in male and female. 400 freshmen students in 4year colleges were surveyed. Questionnaire and blood analysis were made. The contents of questionnaire contained general characteristics, health practice behavior, and food intake. The physical measurement included height, weight and blood pressure. The questions for health practice were about drinking, smoking, BMI, skipping breakfast and sleeping. Nutrient intake was expressed by DDS(Dietary Diversity Score by 5 food groups) and DVS (Dietary Variety Score) and 24-hrs recall method was used to find out the quantity of daily food intake. EAR% was calculated and NAR and MAR were produced. The results are as follows: 1) BMI was $22.77kg/m^2$ for males and $20.42kg/m^2$ for females. The ratio maintaining normal weight indicated by BMI of 18.5-23 was higher(p<0.001) for female students(63.2%) than males(56.5%). The ratio of overweight with over $23kg/m^2$ of BMI was 28.5% for males and 8.8% for females(p<0.001). 2)The ratio of drinking students was 59.4% for males and 40.6% for female(p<0.001). And the ratio of smoking students was 95.2% for males and 4.8% for females(p<0.001). 3) The ratio of poor health practice group was 35.7% for males and 25.5% for females, and that of excellent one was 25.4% for males and 33.1% for females(p<0.05). 4) In NAR, the lowest ratio was observed for the intake of Ca, Fe, Vitamin C and Vitamin $B_2$. The intake of Fe, Vitamin $B_2$ and phosphorus were different significantly according to sexuality. For Fe, female students showed lower level than male students(p<0.001). For Vitamin $B_2$, and phosphorus female students showed higher level(p<0.001). 5) In MAR, there was no difference according to sexuality in almost all of the ingredients. 6) For energy intake, male and female students showed 59% and 66% of EAR and it was insufficient for them. 7) For protein, more than 100% was obtained. The lowest ratio was observed for the intake of vitamin C 50.8%, Ca 53.6% and Fe 65.1% of EAR were obtained. The lowest intake ratio and for the intake of Fe female students obtained just 37.5% of EAR showing high risk of anemia. The intake of energy(p<0.001), phosphorus(p<0.01), niacin(p<0.05), Fe(p<0.001), and Vitamin $B_2$ (p<0.001) were different significantly according to sexuality. For Fe, female students showed lower level than male students(p<0.001). For energy, phosphorus, niacin, and Vitamin $B_2$ female students showed higher level(p<0.001) than male students. 8) For blood pressure, male students showed normal level of 120.7/79.1 mmHg, however, female students showed 114.5/75.4 mmHg lower than male (p<0.001). 9). In blood, for hemoglobin female students showed significantly lower level than that of male(p<0.001). T-Cholesterol and HDL-Cholesterol female students showed higher level than males (p<0.001), And for triglyceride male students showed higher level than females(p<0.001). Ca and Fe female students showed lower level (p<0.001).