• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.43-54
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• 2023

Due to climate change, drought and flood occurrences have been increasing. Accurate projections of watershed discharges are imperative to effectively manage natural disasters caused by climate change. However, climate change and hydrological model uncertainty can lead to imprecise analysis. To address this issues, we used two lumped models, IHACRES and GR4J, to compare and analyze the changes in discharges under climate stress scenarios. The Hapcheon and Seomjingang dam basins were the study site, and the Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) were used for parameter optimizations. Twenty years of discharge, precipitation, and temperature (1995-2014) data were used and divided into training and testing data sets with a 70/30 split. The accuracies of the modeled results were relatively high during the training and testing periods (NSE>0.74, KGE>0.75), indicating that both models could reproduce the previously observed discharges. To explore the impacts of climate change on modeled discharges, we developed climate stress scenarios by changing precipitation from -50 % to +50 % by 1 % and temperature from 0 ℃ to 8 ℃ by 0.1 ℃ based on two decades of weather data, which resulted in 8,181 climate stress scenarios. We analyzed the yearly maximum, abundant, and ordinary discharges projected by the two lumped models. We found that the trends of the maximum and abundant discharges modeled by IHACRES and GR4J became pronounced as changes in precipitation and temperature increased. The opposite was true for the case of ordinary water levels. Our study demonstrated that the quantitative evaluations of the model uncertainty were important to reduce the impacts of climate change on water resources.

• Asia Marketing Journal
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• v.13 no.1
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• pp.51-84
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• 2011

It seems essential to examine the factors that may affect relationship commitment of subcontractors to parent companies in the industrial market in Korea in an effort to construct a win-win-type cooperative network among them. Lots of studies have been focusing on the consumer goods market. Relatively few studies have been focused on industrial market. In the industrial goods market subcontractors used to sell their parts or services only to a small number of parent companies in a large quantity, resulting in decisive control of subcontractors over the quality of parent companies' finished goods. This is why relationship between subcontractors and parent companies is extremely important. From this viewpoint, this study aims to survey and analyze empirically the paths leading to relationship commitment of subcontractors toward the parent companies which are required to incite them to build up a collaborative network by means of subcontractors' entrepreneurship. For this aim, market orientation effects of entrepreneurship as well as factors of performance and trust are particularly set forth as the bases of developing hypotheses in this study in order to explore the paths from entrepreneurship to relationship commitment as follows. First, the path of entrepreneurship-market orientation-communication-trust- relationship commitment; second, the path of entrepreneurship-market orientation-performance-relationship commitment; third, the path of entrepreneurship-market orientation-transaction specific asset investment -trust-relationship commitment; and fourth, the path in which the entrepreneurship is expected to promote direct transaction specific asset investment by parent companies to induce their trust and, eventually, relationship commitment of subcontractors. The outcomes of the empirical analysis in this study may be summed up as follows: First, the conclusions of preceding studies are also supported here by the fact that the entrepreneurship of subcontractors promotes their market orientation (hypothesis 9), indicating that the entrepreneurship can facilitate collection, proliferation of and response to market informations. On the contrary, however, the assumption that the entrepreneurship of subcontractors might directly accelerate transaction specific asset investment by parent companies (hypothesis 8) is rejected. Second, although the influence of subcontractors' entrepreneurship on parent companies' investment of assets peculiar to their transactions is not affirmed, the assumption is found to be supported that subcontractors' market orientation would expedite the parent companies' investment of assets peculiar to their transactions. Moreover, it is also confirmed that parent companies' investment of assets peculiar to transactions would promote subcontractors' trust toward the parent companies (hypothesis 6), signifying that parent companies may level up their trust in subcontractors when they make great amount of efforts to invest in the assets peculiar to transactions, not behaving opportunistically, Third, the hypotheses 4 and 5 also turn out to be supported by the analysis as the former assumes that market orientation could promote communication and the latter relates that the communication between subcontractors and parent companies would prompt trust, both results in affirming that market orientation could introduce open communication to speed up sharing of information and that sharing of information by way of communication might give an impetus to trust. Fourth, the assumption that subcontractors' market orientation would expedite performance (hypothesis 3) is also proved favorably to the significant level equivalent to that of preceding studies. Fifth, same as preceding studies, it is also verified in this study that the benefit (outcomes) awarded by parent companies to subcontractors will be a direct cause exercising a positive impact upon relationship commitment(hypothesis 2) and that the trust of subcontractors toward parent companies may have affirmative influence on the relationship commitment(hypothesis 1). Overall, the first, second and third paths are identified as being supported by the hypotheses among constituent factors, while the fourth path is deemed meaningless since it is shown that the entrepreneurship exercises no effects on parent companies' investment in the assets peculiar to transactions.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.28-41
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• 2024

The carbon balance serves as a valuable indicator of a plant's physiological status under diverse environmental conditions. We investigated the photosynthetic and respiratory responses of the Asian surfgrass Phyllospadix iwatensis along the northeast coast of the Korean peninsula in response to changing water temperature (ranging from 5℃ to 30℃) to estimate the seasonal whole-plant carbon balance through a series of incubation experiments. The maximum gross photosynthetic rate (P_max) showed a significant difference among the temperature treatments, while there was no significant difference in photosynthetic efficiency (α). The maximum gross photosynthetic rate of P. iwatensis reached its peaks at 20℃ treatment (101.65 μmol O₂ g^-1 DW h^-1) but decreased rapidly at 30℃. The saturation irradiance (I_k), compensation irradiance (I_c), and respiration rate (R) of P. iwatensis exhibited significant differences among the temperature treatments. The saturation irradiance increased up to 20-25℃ (121.59-124.50 μmol photons m^-2 s^-1) and sharply decreased at 30℃. The compensation irradiance and respiration rate increased steadily with rising water temperature. The ratio of P_max to R (P_max:R ratio) was the highest at 5℃ but dramatically decreased at 30℃. The whole-plant carbon balance, calculated based on photosynthetic parameters, respiration rates, and biomass, exhibited distinct seasonal variation, increasing during winter and spring and decreasing during summer and fall, which is consistent with the highest in situ growth in spring and severely limited growth at the highest water temperature conditions. Phyllospadix iwatensis displayed a negative carbon balance during late summer, fall, and winter, but demonstrated a positive carbon balance during spring and early summer. Our findings suggest that the rising seawater temperatures associated with climate change may lead to significant alterations in the seagrass ecosystem functioning along the rocky shores of the Korean east coast.

• The Journal of Small Business Innovation
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• v.19 no.4
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• pp.19-39
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• 2016

With increasing adoption of smart products and complexity, companies have shifted their strategies from stand alone and competitive strategies to business ecosystem oriented and cooperative strategies. The win-win growth of business refers to corporate efforts undertaken by companies to pursue the healthiness of business between conglomerates and partnering companies such as suppliers for mutual prosperity and a long-term corporate soundness based on their business ecosystem and cooperative strategies. This study is designed to validate a theoretical proposition that the win-win growth strategy of Samsung Electronics and cooperative efforts among companies can create a healthy business ecosystem, based on results of case studies and surveys. In this study, a level of global market access of small and mid-sized companies is adopted as the key achievement index. The foreign market entry is considered as one of vulnerabilities in the ecosystem of small and mid-sized enterprises (SMEs). For SMEs, the global market access based on the research and development (R&D) has become the critical component in the process of transforming them into global small giants. The results of case studies and surveys are analyzed mainly based on a model of a virtuous cycle of Creativity, Opportunity, Productivity, and Proactivity (the COPP model) that features the characteristics of the healthiness of a business ecosystem. In the COPP model, a virtuous circle of profits made by the first three factors and Proactivity, which is the manifestation of entrepreneurship that proactively invests and reacts to the changing business environment of the future, enhances the healthiness of a given business ecosystem. With the application of the COPP model, this study finds major achievements of the win-win growth of Samsung Electronics as follows. First, Opportunity plays a role as a parameter in the relations of Creativity, Productivity, and creating profits. Namely, as companies export more (with more Opportunity), they are more likely to link their R&D efforts to Productivity and profitability. However, companies that do not export tend to fail to link their R&D investment to profitability. Second, this study finds that companies with huge investment on R&D for the future, which is the result of Proactivity, tend to hold a large number of patents (Creativity). And companies with significant numbers of patents tend to be large exporters as well (Opportunity), and companies with a large amount of exports tend to record high profitability (Productivity and profitability), and thus forms the virtuous cycle of the COPP model. In addition, to access global markets for sustainable growth, SMEs need to build and strengthen their competitiveness. This study concludes that companies with a high level of proactivity to invest for the future can create a virtuous circle of Creativity, Opportunity, Productivity, and Proactivity, thereby providing a strategic implication that SMEs should invest time and resources in forming such a virtuous cycle which is a sure way for the SMEs to grow into global small giants.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.59-80
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• 2008

Recently, e-sports are growing with potentiality as a new industry with conspicuous profit model. But studies that dealing with e-sports are not enough. Hence, proposes of this paper are both to establish basic model that is for the design of e-sport marketing strategy and to contribute toward future studies which are related to e-sports. Recently, the researches to explain sports-sponsorship through the identification theory have been discovered. Many researches say that somewhat proper identification is a requirement for most sponsors to improve the their images which is essential to sponsorship activity. Consequently, the research for sponsorship associated with identification in the e-sports, not in the physical sports is the core sector of this study. We extracted the variables from online's major characteristics and existing sport sponsorship researches. First, because e-sports mean the tournaments or leagues in the use of online game, the main event of the game is likely to call it online game. Online media's attributes are distinguished from those of offline. Especially, interactivity, anonymity, and expandibility as a e-sport game attributes are able to be mentioned. So, these inherent online attributes are examined on the relationship with flow. Second, in physical sports games, Fisher(1998) revealed that team similarity and team attractivity were positively related to team identification. Wann(1996) said that the result of former game influenced the evaluation of the next game, then in turn has an effect on the identification of team supporters. Considering these results in the e-sports side, e-sports gamer' attractivity, similarity, and match result seem to be important precedent variables of the identification with a gamer. So, these e-sport gamer attributes are examined on the relationship with both flow and identification with a gamer. Csikszentmihalyi(1988) defined the term flow as feeling status for him to be making current positive experience optimally. Hoffman and Novak(1996) also said that if a user experienced the flow he would visit a website without any reward. Therefore flow might be positively associated with user's identification with a gamer. And, Swanson(2003) disclosed that team identification influenced the positive results of sponsorship, which included attitude toward sponsors, sponsor patronage, and satisfaction with sponsors. That is, identification with a gamer expect to be connected with corporation identification significantly. According to the above, we can design the following research model. All variables used in this study(interactivity, anonymity, expandibility, attractivity, similarity, match result, flow, identification with a gamer, and identification with a sponsor) definitely were defined operationally underlying precedent researches. Sample collection was carried out to the person who has an experience to have enjoyed e-sports during June 2006. Much portion of samples is men because much more men than women enjoy e-sports in general. Two-step approach was used to test the hypotheses. First, confirmatory factor analysis was committed to guarantee the validity and reliability of variables. The results showed that all variables had not only intensive and discriminant validity, but also reliability. Then, research model was examined with fully structural equation using LISREL 8.3 version. The fitness of the suggested model mostly was at the acceptable level. Shortly speaking about the results, first of all, in e-sports game attributes, only interactivity which is called a basic feature in online situation affected flow positively. Secondly, in e-sports gamer's attributes, similarity with a gamer and match result influenced flow positively, but there was no significant effect in the relationship between the attractivity of a gamer and flow. And as expected, similarity had an effect on identification with a gamer significantly. But unexpectedly attractivity and match result did not influence identification with a gamer significantly. Just the same as the fact verified in the many precedent researches, flow greatly influenced identification with a gamer, and identification with a gamer continually had an influence on the identification with a sponsor significantly. There are some implications in these results. If the sponsor of e-sports supports the pro-game player who absolutely should have the superior ability to others and is similar to the user enjoying e-sports, many amateur gamers will feel much of the flow and identification with a pro-gamer, and then after all, feel the identification with a sponsor. Such identification with a sponsor leads people enjoying e-sports to have purchasing intention for products produced by the sponsor and to make a positive word-of-mouth for those products or the sponsor. For the future studies, we recommend a few ideas. Based on the results of this study, it is necessary to find new variables relating to the e-sports, which is not mentioned in this study. For this work to be possible, qualitative research seems to be needed to consider the inherent e-sport attributes. Finally, to generalize the results related to e-sports, a wide range of generations not a specific generation should be researched.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of Distribution Research
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• v.17 no.2
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• pp.1-28
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• 2012

I. Introduction : The purpose of this study is to test empirically hypothetical causality among constructs used in previous studies to build the model of relational market behavior on customers' participation and consumer-brand relationship after introducing theories of relationship marketing, loyalty program, consumer-brand relationship, customers' participation in service marketing as previous studies with regard to relational market behavior, which Bagozzi(1995) and Peterson(1995) commented on constructs and definition suggested by Sheth and Parvatiyar (1995). For this purpose, loyalty program by the service provider, customers' participation and consumer-brand relationship as preceding variables explain relational market behavior defined by Sheth and Parvatiyar(1995). This study proposes that loyalty program as a tool of relationship marketing will be effective in that consumers' participation in marketing relationship results in a narrow range of choice(Sheth and Parvatiyar, 1995) because consumers think that their participation motive result in benefits(Peterson, 1995). Also, it is proposed that the quality of consumer-brand relationship explain the performance of relationship as well as the intermediary effect because the loyalty program could be evaluated based on relationship with customers. We reviewed the variables with regard to performance of relationship based on relation maintain in marketing literature, and then tested our hypotheses related to several performance variables including loyalty and intention of relation maintain based on the previous studies and constructs(Bendapudi and Berry, 1997 ; Bettencourt, 1997 ; Palmatier, Dant, Grewal and Evans, 2006 ; You Jae Yi and Soo Jin Lee, 2006). II. Study Model : Analyses about hypothetical causality were proceeded. The marketing effect of loyalty program on relational market behavior was empirically tested in study regarding a service provider. The research model in according to the path hypotheses (loyalty program ${\rightarrow}$ customers' participation ${\rightarrow}$ consumer-brand relationship ${\rightarrow}$ relational market behavior and loyalty program ${\rightarrow}$ consumer-brand relationship, and loyalty program ${\rightarrow}$ relational market behavior and customers' participation ${\rightarrow}$ consumer-brand relationship, and customers' participation ${\rightarrow}$ relational market behavior) proceeded as an activity for customer relation management was suggested. The main purpose of study is to see if relational market behavior could be brought as a result of developing relationship between consumers and a corporate into being stronger and more valuable when a corporate or a service provider try aggressively to build the relationship with customers (Bettencourt, 1997; Palmatier, Dant, Grewal and Evans, 2006; Sheth and Parvatiyar, 1995). III. Conclusion : The results of research into the membership fitness club, one of service areas with high level of customer participation (Bitner, Faranda, Hubbert and Zeithaml, 1997; Chase, 1978; Kelley, Donnelly, Jr. and Skinner, 1990) are as follows: First, causalities in according to path hypotheses were tested, after the preceding variables affecting relational market behavior and conceptual frame were suggested. In study, all hypotheses were supported as expected. This result confirms the proposition suggested by Sheth and Parvatiyar(1995), who claimed that intention of consumer and corporate to participate in marketing relationship brings high level of marketing productivity. Also, as a corporate or a service provider try aggressively to build relationship with customers, the relationship between consumers and a corporate can be developed into stronger and more valuable one (Bettencourt, 1997; Palmatier, Dant, Grewal and Evans, 2006). This finding supports the logic of relationship marketing. Second, because the question regarding the path hypothesis of consumer-brand relationship ${\rightarrow}$ relational market behavior are still at issue, the further analyses were conducted. In particular, there existed the mediating effects of consumer-brand relationship toward relational market behavior. Also, multiple regressions were conducted to see if which one strongly influences relational market behavior among specific question items with regard to consumer-brand relationship. As a result, the influence between items composing consumer-brand relationship and ones composing relational market behavior was different. Among items composing consumer-brand relationship, intimacy was an influence of sustaining relationship, word of mouth, and recommendation, intimacy and interdependence were influences of loyalty, intimacy and self-connection were influences of tolerance and advice. Notably, commitment among items measuring consumer-brand relationship had the negative influence with relational market behavior. This means that bringing relational market behavior is not consumer-brand relationship without personal commitment, but effort to build customer relationship like intimacy, interdependence, and self-connection. This finding confirms the results of Breivik and Thorbjornsen(2008). They reported that six variables composing the quality of consumer-brand relationship have higher explanation in regression model directly affecting performance of consumer-brand relationship. As a result of empirical analysis, among the constructs with regard to consumer-brand relationship, intimacy(B=0.512), interdependence(B=0.196), and quality of partner(B=0.153) had the effects on relation maintain. On the contrary, self-connection, love and passion, and commitment had little effect and did not show the statistical significance(p<0.05). On the other hand, intimacy(B=0.668) and interdependence(B=0.181) had the high regression estimates on word of mouth and recommendation. Regarding the effect on loyalty, explanation level of the model was high(R2=0.515), intimacy(0.538), interdependence(0.223), and quality of partner(0.177) showed the statistical significance(p<0.05). Furthermore, intimacy(0.441) had the strong effect as well as self-connection(0.201) and interdependence (0.163) had the effect on tolerance and forgive. And these three variables showed effects even on advice and suggestion, intimacy(0.373), self-connection(0.270), interdependence (0.155) respectively. Third, in study with regard to the positive effect(loyalty program ${\rightarrow}$ customers' participation, loyalty program ${\rightarrow}$ consumer-brand relationship, loyalty program ${\rightarrow}$ relational market behavior, customers' participation ${\rightarrow}$ consumer-brand relationship, customers' participation ${\rightarrow}$ relational market behavior, consumer-brand relationship ${\rightarrow}$ relational market behavior), the path hypothesis of customers' participation ${\rightarrow}$ consumer-brand relationship, was supported. The fact that path hypothesis of customers' participation ${\rightarrow}$ consumer-brand relationship was supported confirms assertion by Bitner(1995), Fournier(1994), Sheth and Parvatiyar(1995) about consumer relationship to participate in marketing relationship.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.448-464
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• 2016

The purpose of this study is to optimize the parameters related to consensus coherency within the PCL 1300, the operating program of wind profiler, from a validation of wind data between rawinsonde and wind profiler at Chupungryeong ($36^{\circ}13^{\prime}$, $127^{\circ}59^{\prime}$) site in Korea. It is then to analyze the diurnal and seasonal characteristics of the turbulence energy dissipation rate (${\varepsilon}$) in clear and rainy days from March 2009 to February 2010. In comparison of the wind data between wind profiler and rawinsonde during April 22-23, 2010, it was shown in a big error more than $10ms^{-1}$ over the height of 3,000 meters in the zonal (u) and meridional (v) wind components. When removing more than $10ms^{-1}$ in each wind speed difference of u an v components between the two instruments, the correlation coefficients of these wind components were 0.92 and 0.88, respectively, and the root mean square errors were 3.07 and $1.06ms^{-1}$. Based on these results, when the data processing time and the minimum available data within the PCL 1300 program were adjusted as 30 minutes and 60%, respectively, the bias errors were small. In addition, as a result of an analysis of sensitivity to consensus coherency of u and v components within the PCL1300 program, u components were underestimated in radial coherency, instantaneous and winbarbs coherency, whereas v components were overestimated. Finally by optimizing parameters of the PCL1300 program, the diurnal and seasonal means of ${\varepsilon}$ at each height were higher in rainy days than those in clear days because of increasing in the vertical wind speed due to upward and downward motions. The mean ${\varepsilon}$ for clear and rainy days in winter was lower than those of other seasons, due to stronger horizontal wind speed in winter than those in other seasons. Consequently, when the turbulence energy dissipation rates in the vertical wind speed of more than ${\pm}10cm\;s^{-1}$ were excluded for clear and rainy days, the mean ${\varepsilon}$ in rainy days was 6-7 times higher than that in clear days, but when considering them, it was 4-5 times higher.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.