• Spatial Information Research
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• v.4 no.1
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• pp.21-42
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• 1996

The Anyang-cheon is one of the Han River tributaries in Seoul Metropolitan area. It is 35.1km long, has a basin area of 287km2 and touches seven cities of Kyounggi Province and part of Seoul. The purpose of this study were 1) to reconstruct the ancient stream network and to investigate the change of landuse in Anyang-cheon watershed between 1957 and 1991,2) to measure the change of the hydrologic ¬acteristics with urbanization, 3) to suggest the institutional solutions to reduce natural hazard as the area has urbanizedThe main results are as follows: 1.Anyang-cheon river basin has experienced the rapid urbanization and industrialization since 1957. Anyang-cheon stream network was oversimplified in the watershed. The total stream length decreased atributaries in the upper part of river basin have eliminated or buried undergrolmd in pipes. 2.Urbanization impacted to all of the area of Anyang-cht'On watershed. Urbanization in Anyang-cheon watershed corresponds to the large portion of flat area, especially flood - prone zone of river side, and the small portion of Greenbelt to constrain urban expantion in cities. 3.The urbanization of Anyang-cheon watershed produces fundamental changes in watershed hydrology. As infiltration is reduced by the creation of extensive pavement, concrete surface, and sewer pipe, runoff moves more quickly from upland to stream. As a result, runoff from the watershed is flashier, increasing flood hazardAs urban area continue to grow we will need to better utilize stream by protecting and enhancing stream systems.otecting and enhancing stream systems.tems.

• Journal of the Korean association of regional geographers
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• v.23 no.1
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• pp.151-167
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• 2017

The main objective of this study was to investigate the climatic impact of $PM_{10}$ concentration on the temperature change pattern in Busan Metropolitan City(BMC), Korea during 2001~2015. Mean $PM_{10}$ concentration of BMC has gradually declined over the past 15 years. While the highest $PM_{10}$ concentration was observed in spring followed by winter, summer, and fall on average, the seasonal variations of $PM_{10}$ concentration differed from place to place within the city. Frequency analysis showed that the most frequently observed $PM_{10}$ concentration ranged from $20{\mu}g/m^3$ to $60{\mu}g/m^3$, which accounted for 64.6% of all daily observations. Overall, the west-high and east-low pattern of $PM_{10}$ concentration was relatively strong during the winter when the effect of yellow-dust events on the air quality was weak. Comparative analyses between $PM_{10}$ concentration and monthly temperature slope derived from generalized temperature curves indicated that the decreasing trend of $PM_{10}$ concentration was associated with increases of annual temperature range, and $PM_{10}$ concentration had a negative relationship with the temperature slope of warming months. Overall, $PM_{10}$ concentration had a weak correlation with the annual mean temperature, but it had a significant, positive correlation with the winter season, which had a dominant influence on the annual mean temperature. In terms of energy budget, it has been known that the change in $PM_{10}$ concentration contributes to the warming or cooling effect by affecting the radiative forcing due to the reflection and absorption of radiant energy. The correlation between $PM_{10}$ concentration and temperature changes in the study area was not seasonally and spatially consistent, and its significance was statistically limited partly due to the number of observations and the lack of potential socioeconomic factors relevant to urban air quality.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.437-448
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• 2016

Some previous researches suggested a transit trip destination inference method by constructing trip chains with incomplete(missing destination) smart card dataset obtained on the entry fare control systems. To explore the feasibility of the transit trip destination inference method, the transit trip chains are constructed from the pre-paid smart card tagging data collected in Busan on October 2014 weekdays by tracing the card IDs, tagging times(boarding, alighting, transfer), and the trip linking distances between two consecutive transit trips in a daily sequences. Assuming that most trips in the transit trip chains are linked successively, the individual transit trip destination zones are inferred as the consecutive linking trip's origin zones. Applying the model to the complete trips with observed OD reveals that about 82% of the inferred trip destinations are the same as those of the observed trip destinations and the inference error defined as the difference in distance between the inferred and observed alighting stops is minimized when the trip linking distance is less than or equal to 0.5km. When applying the model to the incomplete trips with missing destinations, the overall destination missing rate decreases from 71.40% to 21.74% and approximately 77% of the destination missing trips are the single transit trips for which the destinations can not be inferable. In addition, the model remarkably reduces the destination missing rate of the multiple incomplete transit trips from 69.56% to 6.27%. Spearman's rank correlation and Chi-squared goodness-of-fit tests showed that the ranks for transit trips of each zone are not significantly affected by the inferred trips, but the transit trip distributions only using small complete trips are significantly different from those using complete and inferred trips. Therefore, it is concluded that the model should be applicable to derive a realistic transit trip patterns in cities with the incomplete smart card data.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.60-74
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• 2017

To facilitate prevention of highly pathogenic avian influenza (HPAI), a GIS is widely used for monitoring, investigating epidemics, managing HPAI-infected farms, and eradicating the disease. After the outbreak of foot-and-mouth disease in 2010 and 2011, the government of the Republic of Korea (ROK) established the GIS-based Korean Animal Health Integrated System (KAHIS) to avert livestock epidemics, including HPAI. However, the KAHIS is not sufficient for controlling HPAI outbreaks due to lack of responsibility in fieldwork, such as sterilization of HPAI-infected poultry farms and regions, control of infected animal movement, and implementation of an eradication strategy. An outbreak prediction model to support efficient HPAI control in the ROK is proposed here, constructed via analysis of HPAI outbreak patterns in the ROK. The results show that 82% of HPAI outbreaks occurred in Jeolla and Chungcheong Provinces. The density of poultry farms in these regions were $2.2{\pm}1.1/km^2$ and $4.2{\pm}5.6/km^2$, respectively. In addition, reared animal numbers ranged between 6,537 and 24,250 individuals in poultry farms located in HPAI outbreak regions. Following identification of poultry farms in HPAI outbreak regions, an HPAI outbreak prediction model was designed using factors such as the habitat range for migratory birds(HMB), freshwater system characteristics, and local road networks. Using these factors, poultry farms which reared 6,500-25,000 individuals were filtered and compared with number of farms actually affected by HPAI outbreaks in the ROK. The HPAI prediction model shows that 90.0% of the number of poultry farms and 54.8% of the locations of poultry farms overlapped between an actual HPAI outbreak poultry farms reported in 2014 and poultry farms estimated by HPAI outbreak prediction model in the present study. These results clearly show that the HPAI outbreak prediction model is applicable for estimating HPAI outbreak regions in ROK.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.31-39
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• 2009

This study has found that there is a reverse phase with interdecadal variation in temporal variations of tropical cyclone (TC) genesis frequency (TCGF) between Northwest sector and Southeast sector, based on climatological mean tropical cyclone genesis location over the western North Pacific. The TCGF in the Northwest sector has been increased since the mid 1980s (1986-2005), while TCGF in the Southeast sector was higher until the early 1970s (1951-1970). The analysis of a difference between 1986-2005 and 1951-1970 showed results as follows: i) Through the analysis of vertical wind shear (VWS) and sea surface temperature (SST), less VWS and higher SST in the former (latter) period was located in the Northwest (Southeast) sector. ii) In the analysis of TC passage frequency (TCPF), TCs occurred in the Northwest sector frequently passed from east sea of the Philippines, through East China Sea, to Korea and Japan in the latter period, while TCs in the former period frequently has a lot of influences on South China Sea (SCS). In the case of TCs occurred in the Southeast sector, TCs in the west (east), based on $150^{\circ}E$ had a high passage frequency in the latter (former) period. In particular, TCs during the latter period frequently moved toward from the east sea of the Philippines to SCS and southern China. iii) This difference of TCPF between the two periods was characterized by 500 hPa anomalous pressure pattern. Particularly, anomalous cyclonic circulation strengthened over the East Asian continent caused anomalous southerlies along the East Asian coast line from the east sea of the Philippines to be predominate. These anomalous winds served as steering flows that TC can easily move toward same regions.

• Journal of the Korean Geographical Society
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• v.41 no.5 s.116
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• pp.527-544
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• 2006

This study provides a definition of heat waves, which indicate the conditions of strong sultriness in summer, appropriate to Korea and intends to clarify long term(1973-2006) averaged spatial and temporal patterns of annual frequency of heat waves with respect to their intensity. Based on examination of the Korean mortality rate changes due to increase of apparent temperature under hot and humid summer conditions, three consecutive days with at least $32.5^{\circ}C,\;35.5^{\circ}C,\;38.5^{\circ}C,\;and\;41.5^{\circ}C$ of daily maximum Heat Index are defined as the Hot Spell(HS), the Heat Wave(HW), the Strong Heat Wave(SHW), and the Extreme Heat Wave(EHW), respectively. The annual frequency of all categories of heat waves is relatively low in high-elevated regions or on islands adjacent to seas. In contrast, the maximum annual frequency of heat waves during the study period as well as annual average frequency are highest in interior, low-elevated regions along major rivers in South Korea, particularly during the Changma Break period(between late July and mid-August). There is no obvious increasing or decreasing trend in the annual total frequency of all categories of heat waves for the study period However, the maximum annual frequencies of HS days at each weather station were recorded mainly in the 1970s, while most of maximum frequency records of both the HW and the SHW at individual weather stations were observed in the 1990s. It is also revealed that when heat waves occur in South Korea high humidity as well as high temperature contributes to increasing the heat wave intensity by $4.3-9.5^{\circ}C$. These results provide a useful basis to help develop a heat wave warning system appropriate to Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

• Journal of the Korean Society of Food Culture
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• v.20 no.5
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• pp.608-614
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• 2005

The object of this research is to analyze and classify the dining-out behavior and preference on Korean food by age groups and to make counter proposals for better marketing and planning strategies. Major dining out motives were lack of time, the easiness of preparation, and schedule. For lunch, the schedule was the major dining-out motive. For dinner, the respondents in their 30s and below answered social gathering was their major dining-out motive (40.7% and 31.3% respectively). On the other hand, for the respondents in their 40s and 50s, the family gathering was the major dining motive (50.4% and 55.3% respectively) (${\chi}^{2}=68.081,\;p<0.001$). For dining out frequency, 1-2 dining out per a week had the highest percentage, among which the respondents in their 30s was 42.9% (the highest) and the respondents in their 50s was 18% (the lowest). For the dining-out cost, the respondents in their 30s and below spent more on dinner rather than breakfast or lunch. For the menu preference of Korean foods, Doenjangjigae had the highest percentage. In case of Kimchi, the respondents in their 40s showed higher preference than the respondents in their 30s. Interestingly, the preference for Kimchi was higher in the respondents younger than 30 rather than in the respondents in their 30s. and the respondents older than 40 (p<0.05). Preference for Jangachi was considerably low in the respondents younger than 40, which implies that younger people don't incline to traditional Korean Mitbanchan. The dining-out motive was different in each age group. Now, the dining out motive is not restricted to home meal replacement. Social gatherings are increasing and the consumers of dining-out industry are being diversified. These suggest the increased need for classifying and analyzing the consumers by age groups to get more information on consumer behavior and tastes.