• Korean Journal of Soil Science and Fertilizer
• /
• v.45 no.5
• /
• pp.711-716
• /
• 2012

Due to the climate change in South Korea the annual total precipitation will increase by 17 percent by 2100. Rainfall is concentrated during the summer in South Korea and the landslide of farmland by heavy rain is expected to increase. Because regional torrential rains accompanied by a storm continue to cause the damage in farmland urgent establishment of adaptation plant for minimizing the damage is in need. In this study we assessed vulnerability of landslide of farmland by heavy rain for local governments. Temporal resolution is 2000 year and the future 2020 year, 2050 year, 2100 year via A1B scenario. Vulnerability of local government were evaluated by three indices such as climate exposure, sensitivity, adaptive capacity and each index is calculated by selected alternative variable. Collected data was normalized and then multiplied by weight value that was elicited in delphi investigation. Current vulnerability is concentrated in Jeju island and Gyeongsangnam-do, however, it is postulated that Kangwon-do will be vulnerable in the future. Through this study, local governments can use the data to establish adaptation plans for farmland landslide by climate change.

• Journal of Korea Water Resources Association
• /
• v.44 no.5
• /
• pp.339-350
• /
• 2011

This study developed a climate informed Bayesian nonstationary frequency model which allows us to forecast seasonal summer rainfall at Nakdong River. We constructed a 37-year summer rainfall data set from 10 weather stations within Nakdong river basin, and two climate indices from sea surface temperature (SST) and outgoing longwave radiation (OLR) were derived through correlation analysis. The selected SST and OLR have been widely acknowledged as a climate driver for summer rainfall. The developed model was applied first to the 2010-year summer rainfall (888.1 mm) in order to assure ourself. We demonstrated model performance by comparing posterior distributions. It was confirmed that the proposed model is able to produce a reasonable forecast. The forecasted value is about 858.2 mm, and the difference between forecast and observation is about 30 mm. As the second case study, 2011-year summer rainfall forecast was made using an observed winter SSTs and an assumed 50% value of OLRs. The forecasted value is 967.7 mm and associated exceedance probability over average summer rainfall 680 mm is 92.9%. In addition, 50-year return period for summer rainfall was projected through the nonstationary frequency model. An exceedance probability over 1,400 mm corresponding to the 50-year return level is about 73.7%.

• Korean Journal of Remote Sensing
• /
• v.35 no.3
• /
• pp.375-387
• /
• 2019

The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.1B
• /
• pp.41-53
• /
• 2008

Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.4D
• /
• pp.513-521
• /
• 2008

The objective of this study is the evaluation of the impact on the construction condition due to historical observation data and IPCC SRES A2 climate change scenario. For this purpose, daily precipitation and daily mean temperature data which have been observed over the past 30 years by Korea Meteorological Administration are collected and applied. Also, A2 scenarios during 2011~2040 and 2051~2080 are used for this analysis. According to the results of trend analyses on annual precipitation and annual mean temperature, they are on the increase mostly. The available working day and the day occurred an extreme event are used as correlation indices between climate factor and construction condition. For the past observation data, linear regression and Mann-Kendall test are used to analyze the trend on the correlation index. As a result, both working day and extreme event occurrence day are increased. Likewise, for the future, variation analysis showed the similar result to that of the past and the occurrence frequency of extreme events is increased obviously. Therefore, we can project to increase flood damage potential on the construction site by climate change.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.2
• /
• pp.1-23
• /
• 2018

This study aims to propose a way for evaluating thermal environment vulnerability associated with policy to improve thermal environment. For this purpose, a variety of indices concerning thermal vulnerability assessment and adaptation policies for climate change applied to 17 Korean cities were reviewed and examined. Finally, 15 indices associated with policies for improving thermal environment were selected. The selected indices for thermal vulnerability assessment were applied to Daegu Metropolitan City of South Korea as a case study. As results, 15 vulnerability maps based on the standardized indices were established, and a comprehensive map with four grades of thermal vulnerability were established for Daegu Metropolitan City. As results, the area with the highest rated area in the first-grade(most vulnerable to heat) was Dong-gu, followed by Dalseo-gu and Buk-gu, and the highest area ratio of the first-grade regions was Ansim-1-dong in Dong-gu. Based on the standardized indices, the causes of the thermal environment vulnerability of Ansim-1-dong were accounted for the number of basic livelihood security recipients, the number of cardiovascular disease deaths, heat index, and Earth's surface temperature. To improve the thermal environment vulnerability of Ansim-1-dong, active policy implementation is required in expansion and maintenance of heat wave shelters, establishment of database for the population with diseases susceptible to high temperature environments, expansion of shade areas and so on. This study shows the applicability of the vulnerability assessment method linked with the policies and is expected to contribute to the strategic and effective establishment of thermal environment policies in urban master district plans.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1393-1396
• /
• 2009

일반적으로 확률강우량은 관측된 강우자료의 분석을 통해 산정하게 된다. 관측된 강우자료의 빈도해석을 통해 산정된 확률강우량은 기후변화 등을 반영하기 매우 어렵다. 따라서 본 연구에서는 통계적 기법을 이용하여 수문기상인자를 반영하여 서울지점의 확률강우량을 산정하였다. 수문기상인자와 연최대시간강우량사이의 상관관계에 기초하여 확률강우량을 산정할 수 있는 CPPM(Climate Pattern and Precipitation Model)을 구축하고 서울 지점을 대상으로 분석을 수행하였다. 분석결과에서 매개변수적 지점빈도해석의 결과와 CPPM 확률강우량은 비슷한 Qunatile을 산정하는 것으로 나타났다. 또한 본 연구의 결과를 지구온난화 등에 따른 기후변화에 따라 극한강우인 연최대강우량의 변화를 예측하는데 있어 기초자료로 활용 할 수 있을 것으로 기대 된다.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.41 no.2
• /
• pp.17-33
• /
• 2016

Clustering is one of the leading methods to analyze big data and is used in many different fields. This study deals with Clustering Validity Index (CVI) to verify the effectiveness of clustering results. We compare the performance of CVIs with business applications of various field. In this study, the used CVIs for comparing performance are DU, CH, DB, SVDU, SVCH, and SVDB. The first three CVIs are well-known ones in the existing research and the last three CVIs are based on support vector data description. It has been verified with outstanding performance and qualified as the application ability of CVIs based on support vector data description.

• Journal of Korean Society of Rural Planning
• /
• v.17 no.3
• /
• pp.1-13
• /
• 2011

This study aims to analyse the landscape ecological characteristics of 39 rural villages in Korea and classify them according to their characteristics. After producing a land-use map of rural villages, this study quantified the landscape ecological characteristics of the subject sites as 18 landscape indexes using Fragstats. By applying the landscape index as a variable, selecting 4 factor through principal component analysis and conducting a cluster analysis, it classified them into 3 groups. Rural villages of Korea have their unique types of land-use due to the influence of physical environment such as geography, climate and ecology as well as the social and cultural influence, and the characteristics of land-use can be analysed and classified using the landscape index, the quantified landscape ecological characteristics.

• 한국데이터정보과학회:학술대회논문집
• /
• 2002.06a
• /
• pp.9-15
• /
• 2002

This paper presents the seasonal forecasting of the occurrence of tropical cyclone (TC) over Western North Pacific (WNP) using the generalized linear model (GLM) and dynamic linear model (DLM) based on 51-year-data (1951-2001) in TC season (June to November). The numbers of TC and TY are predictands and 16 indices (the E1 Nino/Southern Oscillation, the synoptic factors over East asia and WNP) are considered as potential predictors. With 30-year moving windowing, the estimation and prediction of TC and TY are performed using GLM. If GLM forecasts have some systematic error like a bias, DLM is applied to remove the systematic error in order to improve the accuracy of prediction.