• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1421-1434
• /
• 2020

The frequency and intensity of heatwaves have been increasing due to climate change. Since urban areas are more severely damaged by heatwaves as they act in combination with the urban heat island phenomenon, every possible preparation for such heat threats is required. Many overseas local governments build heat maps using a variety of spatial information to prepare for and counteract heatwaves, and prepare heatwave measures suitable for each region with different spatial characteristics within a relevant city. Building a heat map is a first and important step to prepare for heatwaves. The cases of heat map construction and thermal environment analysis involve various area distributions from urban units with a large area to local units with a small area. The method of constructing a heat map varies from a method utilizing remote sensing to a method using simulation, but there is no standard for using differentiated spatial information according to spatial scale, so each researcher constructs a heat map and analyzes the thermal environment based on different methods. For the above reason, spatial information standards required for building a heat map according to the analysis scale should be established. To this end, this study examined spatial information, analysis methodology, and final findings related to Korean and oversea analysis studies of heatwaves and urban thermal environments to suggest ways to improve the utilization efficiency of spatial information used to build urban heat maps. As a result of the analysis, it was found that spatial, temporal, and spectral resolutions, as basic resolutions, are necessary to construct a heat map using remote sensing in the use of spatial information. In the use of simulations, it was found that the type of weather data and spatial resolution, which are input condition information for simulation implementation, differ according to the size of analysis target areas. Therefore, when constructing a heat map using remote sensing, spatial, spectral, and temporal resolution should be considered; and in the case of using simulations, the spatial resolution, which is an input condition for simulation implementation, and the conditions of weather information to be inputted, should be considered in advance. As a result of understanding the types of monitoring elements for heatwave analysis, 19 types of elements were identified such as land cover, urban spatial characteristics, buildings, topography, vegetation, and shadows, and it was found that there are differences in the types of the elements by spatial scale. This study is expected to help give direction to relevant studies in terms of the use of spatial information suitable for the size of target areas, and setting monitoring elements, when analyzing heatwaves.

• Journal of Radiation Protection and Research
• /
• v.25 no.4
• /
• pp.207-216
• /
• 2000

Continuous measurements of radon progeny concentrations in the open atmosphere and measurements of meteorological parameters were performed in Tajeon, using a continuous gross alpha/beta aerosol monitor and a weather measuring equipment between July 1999 and July 2000. These data were analyzed for half-hourly, daily, and seasonal variations. The distribution of daily averaged equilibrium equivalent radon concentration$(EEC_{Rn})$ had an arithmetic mean value of $11.3{\pm}5.86Bqm^{-3}$ with the coefficient of variation of about 50% and the geometric mean was $10.3Bqm^{-3}$. The $EEC_{Rn}$ varies between 0.83 and $43.3Bqm^{-3}$, depending on time of day and weather conditions. Half-hourly averaged data indicated a diurnal pattern with the outdoor $EEC_{Rn}$ reaching a maximum at sunrise and a minimum at sunset. The pattern of the seasonal variation of the $EEC_{Rn}$ in Taejon had a tendency of minimum concentration occurring in the summer(July) and maximum concentration occurring in the late autumn(November). But the seasonal variation of the $EEC_{Rn}$ is expect to vary greatly from place to place. The outdoor $EEC_{Rn}$ was highly dependent on the local climate features. Particularly the $EEC_{Rn}$an rapidly drops less than $5Bqm^{-3}$ in case of blowing heavily higher than wind speed of $6msec^{-1}$, reversely the days with more than $30Bqm^{-3}$ were at a calm weather condition with the wind speed of lower than $1msec^{-1}$.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.2
• /
• pp.59-66
• /
• 2013

Among many factors, especially meteorological conditions can impact agricultural productivities. This study was conducted to analyze the relationships between crop yield and meteorological factors. We collected meteorological data (i.e., temperature and precipitation) from the Automated Weather System (AWS) of Korea Meteorological Administration (KMA) and the yield data of Chinese cabbage and Radish from local Nonghyup (NCAF:National Agricultural Cooperative Federation) and Farmers' Corporate Association. The agricultural data were classified into two groups. These groups are comprised of the farmers who produced a crop under 30 kg per $3.3m^2$ and over 30k g per $3.3m^2$ respectively. The daily meteorological data were calculated from the average value for ten days. Based on the regression analysis, we concluded that the yield of Chinese cabbage (Haenam) was related to average temperature, minimum temperature, precipitation, and number of days with precipitation, whereas that of Radish (Jeju) was related to average temperature, maximum temperature, and minimum temperature. The result suggests that these meteorological data can be used more effectively for the prediction of crop yield.

• Journal of the Society of Disaster Information
• /
• v.16 no.3
• /
• pp.430-439
• /
• 2020

Purpose: As the frequency of impact typhoons increases and the form of damage becomes more complicated, the need for information to help disaster response workers recognize the typhoon situation in advance is growing. In this study, Definitions and implementation measures for information utilized at each stage of the task were proposed in carrying out typhoon response tasks that occur every year. Method: In 2019, the government classified information that was used for each step of work and conducted analysis on necessary information for the situation. Based on the analyzed information, typhoon status information was established through an opinion survey by central and local government officer. Result: The task of typhoon situations was the most important part of monitoring weather conditions and sharing damage situations, and the information utilized was analyzed to require information derived through the convergence of historical and situation information. Conclusion: As the correlation between work and information between the response departments increases as the typhoon situation progresses, information about typhoon situation should be applied to the actual typhoon situation in the future to enhance information and establish a related system.

• Atmosphere
• /
• v.25 no.2
• /
• pp.221-233
• /
• 2015

Pollen is closely related to health issues such as allergenic rhinitis and asthma as well as intensifying atopic syndrome. Information on current and future spatio-temporal distribution of allergenic pollen is needed to address such issues. In this study, the Community Multiscale Air Quality Modeling (CMAQ) was utilized as a base modeling system to forecast pollen dispersal from oak trees. Pollen emission is one of the most important parts in the dispersal modeling system. Areal emission factor was determined from gridded areal fraction of oak trees, which was produced by the analysis of the tree type maps (1:5000) obtained from the Korea Forest Service. Daily total pollen production was estimated by a robust multiple regression model of weather conditions and pollen concentration. Hourly emission factor was determined from wind speed and friction velocity. Hourly pollen emission was then calculated by multiplying areal emission factor, daily total pollen production, and hourly emission factor. Forecast data from the KMA UM LDAPS (Korea Meteorological Administration Unified Model Local Data Assimilation and Prediction System) was utilized as input. For the verification of the model, daily observed pollen concentration from 12 sites in Korea during the pollen season of 2014. Although the model showed a tendency of over-estimation in terms of the seasonal and daily mean concentrations, overall concentration was similar to the observation. Comparison at the hourly output showed distinctive delay of the peak hours by the model at the 'Pocheon' site. It was speculated that the constant release of hourly number of pollen in the modeling framework caused the delay.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.8
• /
• pp.521-529
• /
• 2020

Forest fires are one of the most important environmental risks that have adverse effects on many aspects of life, such as the economy, environment, and health. The early detection, quick prediction, and rapid response of forest fires can play an essential role in saving property and life from forest fire risks. For the rapid discovery of forest fires, there is a method using meteorological data obtained from local sensors installed in each area by the Meteorological Agency. Meteorological conditions (e.g., temperature, wind) influence forest fires. This study evaluated a Data Mining (DM) approach to predict the burned area of forest fires. Five DM models, e.g., Stochastic Gradient Descent (SGD), Support Vector Machines (SVM), Decision Tree (DT), Random Forests (RF), and Deep Neural Network (DNN), and four feature selection setups (using spatial, temporal, and weather attributes), were tested on recent real-world data collected from Gyeonggi-do area over the last five years. As a result of the experiment, a DNN model using only meteorological data showed the best performance. The proposed model was more effective in predicting the burned area of small forest fires, which are more frequent. This knowledge derived from the proposed prediction model is particularly useful for improving firefighting resource management.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
• /
• v.4 no.1
• /
• pp.31-42
• /
• 2000

The dry deposition velocities and fluxes of air pollutants such as SO2(g), O3(g), HNO3(g), sub-micron particulates, NO3(s), and SO42-(s) were estimated according to local meteorological elements in the atmospheric boundary layer. The model used for these calculations was the multiple layer resistance model developed by Hicks et al.1). The meteorological data were recorded on an hourly basis from July, 1990 to June, 1991 at the Austin Cary forest site, near Gainesville FL. Weekly integrated samples of ambient dry deposition species were collected at the site using triple-fiter packs. For the study period, the annual average dry deposition velocities at this site were estimated as 0.87$\pm$0.07 cm/s for SO2(g), 0.65$\pm$0.11 cm/s for O3(g), 1.20$\pm$0.14cm/s for HNO3(g), 0.0045$\pm$0.0006 cm/s for sub-micron particulates, and 0.089$\pm$0.014 cm/s for NO3-(s) and SO42-(s). The trends observed in the daily mean deposition velocities were largely seasonal, indicated by larger deposition velocities for the summer season and smaller deposition velocities for the winter season. The monthly and weekly averaged values for the deposition velocities did not show large differences over the year yet did show a tendency of increased deposition velocities in the summer and decreased values in the winter. The annual mean concentrations of the air pollutants obtained by the triple filter pack every 7 days were 3.63$\pm$1.92 $\mu\textrm{g}$/m3 for SO42-, 2.00$\pm$1.22 $\mu\textrm{g}$/m-3 for SO2, 1.30$\pm$0.59 $\mu\textrm{g}$/m-3 for HNO3, and 0.704$\pm$0.419 $\mu\textrm{g}$/m3 for NO3-, respectively. The air pollutant with the largest deposition flux was SO2 followed by HNO3, SO42-(S), and NO3-(S) in order of their magnitude. The sulfur dioxide and NO3- deposition fluxes were higher in the winter than in the summer, and the nitric acid and sulfate deposition fluxes were high during the spring and summer.

• Journal of the Korean earth science society
• /
• v.33 no.3
• /
• pp.219-232
• /
• 2012

The intensive observation (ProbeX-2010) was performed to investigate an urban effect on summer rainfall over the Seoul metropolitan area from 13 August to 3 September 2010. Two kinds of urban effect were detected. First, weak rainfall (${\leq}1\;mm\;hr^{-1}$) was observed more frequently in the downwind area of Seoul than any other area of the country. The high frequency of weak rainfall in the downwind area was also confirmed from the recent five years of observational data (2006-2010). Because the high frequency was more apparent in mountainous regions during nighttime, the weak rainfall seems to be caused by a combined effect of urbanization and topography. Second, sporadically, a convective system was developed rapidly in the downwind area of Seoul, causing heavy rainfall (${\geq}10\;mm\;hr^{-1}$). It can be most clearly seen in series of radar images around 1300-1500 KST 27 August 2010. We investigated in detail the synoptic and local weather and upper air conditions. As a result, not only urban-induced high sensible heat but also conditionally unstable atmosphere (especially unstable in low level) and low level moisture were pointed out as important factors that contributed to urban-induced heavy rainfall.

• Atmosphere
• /
• v.25 no.4
• /
• pp.623-637
• /
• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• Journal of Korean Society for Geospatial Information Science
• /
• v.22 no.3
• /
• pp.99-105
• /
• 2014

Since traffic accidents account for the highest proportion of the artificial disasters which occur in urban areas along with fire, more scientific an analysis on the causes of traffic accidents and various prevention measures against traffic accidents are needed. In this study, the research selected Jinju-si, which belongs to local small and medium-sized cities as a research target to analyze the characteristics of temporal and spacial distribution of traffic accidents by associating the data of traffic accidents, occurred in 2013 with the causes of traffic accidents and location information that includes occurrence time and seasonal features. It subsequently examines the spatial correlation between traffic accidents and the characteristics of urban space development according to the plans of land using. As a result, the characteristics of accident distribution according to the types of accidents reveal that side right-angle collisions (car versus car) and pedestrian-crossing accident (car versus man) showed the highest clustering in the density analysis and average nearest neighbor analysis. In particular, traffic accidents occurred the most on roads which connect urban central commercial areas, high-density residential areas, and industrial areas. In addition, human damage in damage conditions, clear day in weather condition, dry condition in the road condition, and three-way intersection in the road way showed the highest clustering.