• Journal of Environmental Impact Assessment
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• v.33 no.4
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• pp.143-154
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• 2024

Heat waves caused by climate change are rapidly increasing health damage to vulnerable groups, and to prevent this, the national, regional, and local governments are establishing climate crisis adaptation policy. A representative climate crisis adaptation policy to reduce heat wave damage is to expand the number of cooling centers. Because it is highly effective in a short period of time, most metropolitan local governments, except Jeonbuk, include the project as an adaptation policy. However, the criteria for selecting a cooling centers are different depending on the budget and non-budget, so the utilization rate and effectiveness of the cooling centers are all different. Therefore, in this study, we developed logistic regression models that can predict and evaluate areas with a high probability of expanding cooling centers in order to implement adaptation policy in local governments. In Incheon Metropolitan City, which consists of various heat wave-vulnerable environments due to the coexistence of the old city and the new city, a logistic model was developed to predict areas where heat waves can be cooling centered by dividing it into Ganghwa·Ongjin-gun and other regions, taking into account socioeconomic and environmental differences. As a result of the study, the statistical model for the Ganghwa·Ogjin-gun region showed that the higher the ground surface temperature and the more and more the number of elderly people over 65 years old, the higher the possibility of location of cooling centers, and the prediction accuracy was about 80.93%. The developed logistic regression model can predict and evaluate areas with a high potential as cooling centers by considering regional environmental and social characteristics, and is expected to be used for priority selection and management when designating additional cooling centers in the future.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.121-131
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• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.379-388
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• 1999

As a first step for delineating the provenance regions of the forest trees in Korea, horizontal zones have been deduced primarily from the various climatic factors such as annual mean temperature, extremely low temperature, relative humidity, annual gum of possible growing days, duration of sunshine and dry index. The basic concept to the delineation of the provenance regions was based on the ecological regions, which was likely to be more practical than that on the basis of the typical provenance regions at the species level. Primary classification of the regions has been based on the forest zones(sub-tropical, warm-temperate, mid-temperate and cool-temperate) as a broad geographic region. Further classification has been carried out using cluster analyses among the basic regions within forest zone. On the basis of clustering, a total of 19 regions including 3 from sub-tropical, 6 from warm-temperate, 8 from mid-temperate and 2 from cool-temperate was horizontally delineated. Of the mean values of 6 climate factors at the broad geographic region level, three factors such as annual mean temperature, extremely low temperature, annual growing days showed directional tendencies from subtropical to cool-temperate, while the others didn't. The values of relative humidity, duration of sunshine and dry index varied among the provenance regions within forest zone. These three factors might he more sensitive by the micro-environment condition than by the macro-environment condition. Present study aimed to delineate the primary provenance regions for tentative application to forest practices. These will be stepwise revised through the supplement using accumulated information regard to genecological data.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.2
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• pp.149-155
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• 2017

To establish cultivation areas for the stable production of yacon, this study investigated the productivity and functional component contents of yacon in eight regions of Korea from 2011 to 2013. The results of principal component analysis using these data were as follows. A survey of 16 agricultural traits and meteorological data in the eight yacon cultivation areas showed that five factors (average temperature, maximum temperature, minimum temperature, frost-free days, and fructooligosaccharide content) were highly significant at the p < 0.001 level. Among the 16 agricultural traits and meteorological data used in the main component analysis of yacon cultivation areas, approximately eight contributed to the first principal component, and approximately four contributed to each of the second and third principal components. In particular, factors related to productivity, fructooligosaccharide content, and temperature change were considered important criteria for the classification of cultivation areas. The cultivation areas were divided into three groups by principal component analysis. In Group I, containing the Jinbu and Bonghwa areas in the mid-highland region at 500-560 m above sea level, the product yield was the highest at 2,622-3,196 kg/10a, the fructooligosaccharide content was also the highest at 9.04-9.62%, and the mean temperature was $17.3-18.5^{\circ}C$. In Group II, the areas Suncheon, Okcheon, Yeoju, and Gangneung, at 20-180 m above sea level, had the lowest yield, relatively lower fructooligosaccharide content, and the highest temperature. The areas in Group III showed values intermediate between those of Group I and Group II. For the different yacon cultivation areas, the product quantity and fructooligosaccharide content differed according to the environmental temperature, and the temperature conditions and number of frost-free days are considered important indicators for cultivation sites. Therefore, in terms of producing yacon with high quality, cultivation at 500-560 m is considered to give a higher yield and functional fructooligosaccharide content.

• Journal of The Korean Society of Grassland and Forage Science
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• v.38 no.1
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• pp.53-60
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• 2018

Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.

• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.4
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• pp.437-446
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• 2012

As a part of establishing suitability classification for forage production, use of the national soil and climate database was attempted for Italian ryegrass (Lolium multiflorum Lam., IRG) in Gangwon Province. The soil data base were from Heugtoram of the National Academy of Agricultural Science, and the climate data base were from the National Center for Agro-Meteorology, respectively. Soil physical properties including soil texture, drainage, slope available depth and surface rock contents, and soil chemical properties including soil acidity and salinity, organic matter content were selected as soil factors. The crieria and weighting factors of these elements were scored. Climate factors including average daily minimum temperature, average temperature from March to May, the number of days of which average temperature was higher than $5^{\circ}C$ from September to December, the number of days of precipitation and its amount from October to May of the following year were selected, and criteria and weighting factors were scored. The electronic maps were developed with these scores using the national data base of soil and climate. Based on soil scores, the area of Goseong, Sogcho, Gangreung, and Samcheog in east coastal region with gentle slope were classified as the possible and/or the proper area for IRG cultivation in Gangwon Province. The lands with gentle or moderate slope of Cheolwon, Yanggu, Chuncheon, Hweongseong, Pyungchang and Jeongsun in west side slope of Taebaeg mountains were classified as the possible and/or proper area as well. Based on climate score, the east coastal area of Goseong, Sogcho, Yangyang, Gangreung and Samcheog could be classified as the possible or proper area. Most area located on west side of the Taebaeg mountains were classified as not suitable for IRG production. In scattered area in Chuncheon and Weonju, where the scores exceeded 60, the IRG cultivation should be carefully managed for good production. For better application of electronic maps.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.185-194
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• 2012

The purpose of this contribution is to develop the framework of a methodology for identifying potential errors in georeferencing and in an application of it using specimens of Ox-Knee, Achyranthes bidentata Blume in Korea. At infraspecific level, uncertainty of identification showed that 41% of A. bidentata var. japonica and 28% of var. bidentata were misidentified, suggesting that the uncertainty level was independent of the reliability of experts' identification. For georeference specimen records, 71 specimens out of total 303 were selected and utilized as occurrence data: Uncertainty was 32.4 km at maximum and was 0.1297 km at minimum (mean = 4,055 m, s.d. = 5,772 m). Var. japonica is common throughout most of the southeastern Korea and west coastal areas, while var. bidentata has been found as far north as Gyeonggi and Gangwon provinces. We modelled the potential distribution of two varieties using Bioclim approach in Korea based on several environmental factors. Our results indicated the most important region for var. japonica lies the west coast ranges and southern area, while for Chungcheongnam-do of potential high diversity occurs for var. bidentata. This study shows that the major factors to determine the distribution patterns of two varieties were thermal factors, rather than precipitation. The Bioclim model using geocode and georeferencing data makes the information increasingly useful and reliable. To improve data quality, it requires full management from data collection to final databases including data cleaning.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Korean Journal of Heritage: History & Science
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• v.55 no.3
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• pp.60-72
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• 2022

A number of wooden built heritage remain in Korea, and most have been damaged by various biological factors including termite. Owing to the irreversible damage caused by termites, wooden built heritage are losing their authenticity and structural stability. In this study, Area-Wide Integrated Termite Management(AW-ITM) was proposed to prevent termite damage. First, to understand the locational characteristics of these sites, the distance from adjacent forests and surrounding forest areas was analyzed for 182 national designated wooden built heritage(national treasures, treasures) using the Geographic Information System(GIS). By analyzing existing pest control projects(2003-2020) and the components of the ITM, the characteristics of termite control for cultural heritages were determined. Based on these results, the cultural heritage sites and their surrounding spaces were divided into three areas, and the types of cultural properties were divided into six types according to the location and number of buildings. Along with this, termite control measures were proposed for each area and type. The concept of AW-ITM has been partially applied to the "Comprehensive Control of Termites in wooden built heritages Sites" by the Cultural Heritage Administration. Caution must be taken with regard to the establishment of a cultural heritage management policy; AW-ITM should be applied on a trial basis with the results then being carefully analyzed and reflected in the establishment of policies pertaining to the conservation management of cultural heritage.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.403-407
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• 2006

This research aims to reduce severe damages to human beings and properties from floods that ravage Korea every year, by estimating right time to hydraulic structures based on the characteristics of variations in flood flows. To establish this permanent means for the flood mitigation, this research analyse design floods of various dams and hydraulic structures in connection with time of occurrence of the weather abnormalities in Korea. This research was derived the optimal regionalization of the precipitation data which can be classified by the climatologically and geographically homogeneous regions in Korea. Using the L-moment ratios and Kolmogorov-Smimov test, the underlying regional probability distribution was identified to be the GEV distribution among applied distributions. The regional and at-site analyses using L-moment for the design rainfall were tested by Monte Carlo simulation. Error tests were computed and compared with those resulting from at-site Monte Carlo simulation. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.