• Title/Summary/Keyword: global estimate

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Application of Machine Learning Algorithm and Remote-sensed Data to Estimate Forest Gross Primary Production at Multi-sites Level (산림 총일차생산량 예측의 공간적 확장을 위한 인공위성 자료와 기계학습 알고리즘의 활용)

  • Lee, Bora;Kim, Eunsook;Lim, Jong-Hwan;Kang, Minseok;Kim, Joon
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1117-1132
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    • 2019
  • Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

Development of a deep neural network model to estimate solar radiation using temperature and precipitation (온도와 강수를 이용하여 일별 일사량을 추정하기 위한 심층 신경망 모델 개발)

  • Kang, DaeGyoon;Hyun, Shinwoo;Kim, Kwang Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.2
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    • pp.85-96
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    • 2019
  • Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

Estimation of Economic Impact on the Air Transport Industry based on the Volcanic Ash Dispersion Scenario of Mt. Baekdu (백두산 화산재 확산 시나리오에 따른 항공산업의 경제적 피해 예측)

  • Kim, Su-Do;Lee, Yeonjeong;Yoon, Seong-Min
    • Journal of International Area Studies (JIAS)
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    • v.18 no.3
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    • pp.109-144
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    • 2014
  • In 2010, large areas of European airspace were closed by the volcanic ash generated by the eruption of Icelandic volcano and it disrupted global trade, business and travel which caused a huge economic damage on the air transport industry. This brought concerned about the economic impact by the eruption of Mt. Baekdu volcano. In this paper, we analyze the affected areas of the air transport industry were decided by calculating the PM10 density of volcanic ash changed over time and by determining the safe upper limit of ash density in their airspace. We separate the sales in the air transport industry according to each airline, airport, and month to estimate the direct losses when all flights inside a restricted zone were canceled. Also, we estimate the indirect losses in regional output, income, and value-added of the different major industries using interindustry (input-output) analysis. There is no direct damage from VEI 1 to VEI 5. But when VEI is 6, all flights to and from Yangyang airport will be canceled due to the No Fly Zone. And some flights to and from the airports Gimhae, Ulsan and Pohang will be restricted due to the Time Limited Zone. When VEI is 7, Yangyang, Gimhae, Ulsan, Pohang and Daegu airports will be closed and all flights will be canceled and delayed. During this time, the total economic losses on the air transport industry are estimated at 8.1 billion won(direct losses of about 3.55 billion won, indirect losses of about 4.57 billion won). Gimhae international airport accounted for 92% of the total loss and is the most affected area according to the volcanic ash scenario of Mt. Baekdu.

Reconsideration of Rare and Endangered Plant Species in Korea Based on the IUCN Red List Categories (IUCN 적색목록 기준에 의한 환경부 멸종위기 야생식물종에 대한 평가)

  • Chang, Chin-Sung;Lee, Heung-Soo;Park, Tae-Yoon;Kim, Hui
    • The Korean Journal of Ecology
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    • v.28 no.5
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    • pp.305-320
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    • 2005
  • Recently 64 species in Korea have been ranked as rare and endangered taxa by the Ministry of Environment using two categories, I and II. The original threat categories produced by the Ministry of Environment were developed to provide a standard for specifying animals and plants in danger of extinction and has been influential sources of information used in species conservation in Korea. However, the criteria by Ministry of Environment were applied to the whole taxa only by regional boundaries, especially in South Korea, rather than international context, and it also lacked an explicit framework that was necessary to ensure repeatability among taxa because of the absence of quantitative criteria to measure the likelihood of extinction. The World Conservation Union (IUCN) has developed quantitative criteria for assessing the conservation status of species. The threatened species categories, the 2000 IUCN Red List, proposed by SSC (Species Survival Commission) of IUCN have become widely recognized internationally. Details of threatened Korean plants, identified by applying the IUCN threat categories and definitions, were listed and analyzed. The number of species identified as threatened was only 34 out of 64 taxa (48.4%), while the rest of taxa were rejected from the original lists. Many of the species (51.6%, 33 taxa) excluded from the original list proposed by Ministry of Environment do not qualify as Critically Endangered, Endangered or Vulnerable because these taxa were widely distributed either in Japan or in China/far eastern Russia and there is no evidence of substantial decline in these countries. An evaluation of taxa in Korea has been carried out only based on subjective views and qualitative data, rather than quantitative scientific data, such as rates of decline, distribution range size, population size, and risk of extinction. Therefore, the national lists undermine the credibility of threatened species lists and invite misuse, which have been raised by other cases, qualitative estimate of risk, political influence, uneven taxonomic or geographical coverage. The increasing emphasis on international responsibilities means that global scale is becoming more significant. The current listings by Environment of Ministry of Korea should be challenged, and the government should seek to facilitate the resolution of disagreements. Especially the list should be flexible enough to handle uncertainty and also incorporates detailed, quantitative data. It is suggested that the highest priorities for the Red List should be given to endemic species in Korea first. After setting up the list of endemic species to Korea, quantitative data on population size and structure, distributional range, rated of decline, and habitat fragmentation should be collected as one of long term projects for the Red list categories. Transparency and accountability are the most important key factors. Also, species assessors are named and data sources referenced are required for the future objective evaluations on Korean plant taxa.

Examining the Formation of Entrepreneurial Activities through Cognitive Approach (기업가적 활동 형성에 미치는 영향요인: 인지론적 접근)

  • Lee, Chaewon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.12 no.3
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    • pp.65-74
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    • 2017
  • There have been questions how entrepreneurs think, act and why individuals become entrepreneurs. The trait-based explanation of entrepreneurial activities has been main stream. However, the trait-based theory has been criticized because it assumes that entrepreneurial traits are inherited, stable and enduring over time. This research accepts the cognitive theory to see how entrepreneurs learn or accept others' values, how entrepreneurial perceptions of opportunity impact entrepreneurial actions and how individuals acquire the social legitimation of the formation of entrepreneurial activities. In order to capture the attitudes, activities and motivations of people who are involved in entrepreneurial activities, the author uses the GEM Korea 2016 data. The data from the Global Entrepreneurship Monitor(GEM) has been well known for the data to capture individuals early-stage entrepreneurial activities. This paper used the sample from the APS(Adult Population Survey) of the GEM which was completed by a representative sample of two thousand adults in Korea by the qualified survey vendor, with strict procedures and oversight by the GEM central data team. The hypotheses are tested with logit regression analysis to estimate the probability of the influence of perceptual variables such as individual perception in social learning, the opportunity recognition in the environment, and social legitimation in the entrepreneurial activities. Based on the results, individuals tend to have high entrepreneurial activities if individuals have high self-efficacy. Also, the existence of role models around the entrepreneurs encourages the individuals involve in entrepreneurial activities more however the perception of opportunity in the environment is not strongly associated with entrepreneurial activities. The media exposure of successful entrepreneurs is more important than others' perception of entrepreneurs on the desirable career option or respect from communities. This paper can contribute to the cognitive processes, particular perception about oneself, as well as perception which is impacted by a community or a society.

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Mobile Camera-Based Positioning Method by Applying Landmark Corner Extraction (랜드마크 코너 추출을 적용한 모바일 카메라 기반 위치결정 기법)

  • Yoo Jin Lee;Wansang Yoon;Sooahm Rhee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1309-1320
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    • 2023
  • The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

Re-Analysis of Clark Model Based on Drainage Structure of Basin (배수구조를 기반으로 한 Clark 모형의 재해석)

  • Park, Sang Hyun;Kim, Joo Cheol;Jeong, Dong Kug;Jung, Kwan Sue
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.6
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    • pp.2255-2265
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    • 2013
  • This study presents the width function-based Clark model. To this end, rescaled width function with distinction between hillslope and channel velocity is used as time-area curve and then it is routed through linear storage within the framework of not finite difference scheme used in original Clark model but analytical expression of linear storage routing. There are three parameters focused in this study: storage coefficient, hillslope velocity and channel velocity. SCE-UA, one of the popular global optimization methods, is applied to estimate them. The shapes of resulting IUHs from this study are evaluated in terms of the three statistical moments of hydrologic response functions: mean, variance and the third moment about the center of IUH. The correlation coefficients to the three statistical moments simulated in this study against these of observed hydrographs were estimated at 0.995 for the mean, 0.993 for the variance and 0.983 for the third moment about the center of IUH. The shape of resulting IUHs from this study give rise to satisfactory simulation results in terms of the mean and variance. But the third moment about the center of IUH tend to be overestimated. Clark model proposed in this study is superior to the one only taking into account mean and variance of IUH with respect to skewness, peak discharge and peak time of runoff hydrograph. From this result it is confirmed that the method suggested in this study is useful tool to reflect the heterogeneity of drainage path and hydrodynamic parameters. The variation of statistical moments of IUH are mainly influenced by storage coefficient and in turn the effect of channel velocity is greater than the one of hillslope velocity. Therefore storage coefficient and channel velocity are the crucial factors in shaping the form of IUH and should be considered carefully to apply Clark model proposed in this study.

Development of a Biophysical Rice Yield Model Using All-weather Climate Data (MODIS 전천후 기상자료 기반의 생물리학적 벼 수량 모형 개발)

  • Lee, Jihye;Seo, Bumsuk;Kang, Sinkyu
    • Korean Journal of Remote Sensing
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    • v.33 no.5_2
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    • pp.721-732
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    • 2017
  • With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

Relationship between Brand Personality and the Personality of Consumers, and its Application to Corporate Branding Strategy

  • Kim, Young-Ei;Lee, Jung-Wan;Lee, Yong-Ki
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.3
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    • pp.27-57
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    • 2008
  • Many consumers enjoy the challenge of purchasing a brand that matches well with their own values and personalities (for example, Ko et al., 2008; Ko et al., 2006). Therefore, the personalities of consumers can impact on the final selection of a brand and its brand personality in two ways: first, the consumers may incline to purchase a brand or a product that reflects their own personalities; second, consumers tend to choose a company that has similar brand personalities to those brands that are being promoted. Therefore, the objectives of this study are following: 1. Is there any empirical relationship between a consumer's personality and the personality of a brand that he or she chooses? 2. Can a corporate brand be differentiated by the brand personality? In short, consumers are more likely to hold favorable attitudes towards those brands that match their own personality and will most probably purchase those brands matching well with their personality. For example, Matzler et al. (2006) found that extraversion and openness were positively related to hedonic product value; and that the personality traits directly (openness) and indirectly (extraversion, via hedonic value) influenced brand effects, which in turn droved attitudinal and purchase loyalty. Based on the above discussion, the following hypotheses are proposed: Hypothesis 1: the personality of a consumer is related to the brand personality of a product/corporate that he/she purchases. Kuksov (2007) and Wernerfelt (1990) argued that brands as a symbolic language allowed consumers to communicate their types to each other and postulated that consumers had a certain value of communicating their types to each other. Therefore, how brand meanings are established, and how a firm communicate with consumers about the meanings of the brand are interesting topics for research (for example, Escalas and Bettman, 2005; McCracken, 1989; Moon, 2007). Hence, the following hypothesis is proposed: Hypothesis 2: A corporate brand identity is differentiated by the brand personality. And there are significant differences among companies. A questionnaire was developed for collecting empirical measures of the Big-Five personality traits and brand personality variables. A survey was conducted to the online access panel members through the Internet during December 2007 in Korea. In total, 500 respondents completed the questionnaire, and considered as useable. Personality constructs were measured using the Five-factor Inventory (NEO-FFI) scale and a total of 30 items were actually utilized. Brand personality was measured using the five-dimension scale developed by Aaker (1997). A total of 17 items were actually utilized. The seven-point Likert-type scale was the format of responses, for example, from 1 indicating strongly disagreed to 7 for strongly agreed. The Analysis of Moment Structures (AMOS) was used for an empirical testing of the model, and the Maximum Likelihood Estimation (MLE) was applied to estimate numerical values for the components in the model. To diagnose the presence of distribution problems in the data and to gauge their effects on the parameter estimates, bootstapping method was used. The results of the hypothesis-1 test empirically show that there exit certain causality relationship between a consumer's personality and the brand personality of the consumer's choice. Thus, the consumer's personality has an impact on consumer's final selection of a brand that has a brand personality matches well with their own personalities. In other words, the consumers are inclined to purchase a brand that reflects their own personalities and tend to choose a company that has similar brand personalities to those of the brand being promoted. The results of this study further suggest that certain dimensions of the brand personality cause consumers to have preference to certain (corporate) brands. For example, the conscientiousness, neuroticism, and extraversion of the consumer personality have positively related to a selection of "ruggedness" characteristics of the brand personality. Consumers who possess that personality dimension seek for matching with certain brand personality dimensions. Results of the hypothesis-2 test show that the average "ruggedness" attributes of the brand personality differ significantly among Korean automobile manufacturers. However, the result of ANOVA also indicates that there are no significant differences in the mean values among manufacturers for the "sophistication," "excitement," "competence" and "sincerity" attributes of the corporate brand personality. The tight link between what a firm is and its corporate brand means that there is far less room for marketing communications than there is with products and brands. Consequently, successful corporate brand strategies must position the organization within the boundaries of what is acceptable, while at the same time differentiating the organization from its competitors.

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Seasonal Variations of Mood and Behavior in Korean Medical Students (한국의 의과대학생에서 기분과 행동의 계절적 변동)

  • Kim, Sung-Jae;Lee, Heon-Jeong;Choi, Hyun-Seok;Jung, Hyun-Gang;Kim, Bong-Ju;Kim, Ju-Yeon;Lee, Young-Woo;Cho, Dong-Hyuk;Lee, Min-Soo;Joe, Sook-Haeng;Kim, Leen
    • Sleep Medicine and Psychophysiology
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    • v.11 no.2
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    • pp.95-99
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    • 2004
  • Objectives: Although many studies on seasonal variations in mood and behavior have been carried out in foreign countries, no such study has previously been undertaken in Korea. The goal of this study was to estimate the frequency of seasonal variations in mood and behavior among Korean medical students. Methods: 297 medical students from Korea University College of Medicine participated in this study. The subjects were surveyed with a Korean translation of the Seasonal Pattern Assessment Questionnaire (SPAQ), and their responses were evaluated for seasonal patterns of mood and behavioral change, including seasonal affective disorder (SAD) and subsyndromal seasonal affective disorder (S-SAD), derived from the case-finding criteria of Kasper et al. Results: The mean global seasonality score was 6.6 (SD=3.6). 83.5% (N=248) of the subjects reported some changes in behavior and mood associated with the seasons. Only 3.7% (N=11) reported no behavioral changes across the seasons. Total prevalence rates were 15.2% for SAD, and 2.7% for S-SAD. The estimated frequencies were 3.0% for summer SAD, 2.7% for summer S-SAD, 11.4% for winter SAD, and 5.8% for winter S-SAD. The prevalence rates for winter SAD or S-SAD were higher than the prevalence rates for summer SAD or S-SAD. Conclusion: These results suggest that seasonal variations in mood and behavior are common among Koreans. The higher prevalence rate of winter SAD or S-SAD than summer SAD or S-SAD is consistent with most western studies and stands in contrasts to studies in other Asian countries, such as Japan and China.

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