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The Present Status and the Preservation Method of the Rice Terrace as Scenic Sites Resources in Northeast Asia (동북아시아 계단식 논의 명승지정 현황 및 보전방안)

  • Youn, Kyung-Sook;Lee, Chang-Hun;Kim, Hyung-Dae;Seo, Woo-Hyun;Lee, Jae-Keun
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.29 no.4
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    • pp.111-123
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    • 2011
  • This study aims to present the basic materials, which lead us to preserve the Korea Rice Terrace as scenic sites resources and study it continuously, through researching about the present status and the preservation method of the Rice Terrace in Korea, China and Japan. The results of this study are as follows. First, The Rice Terrace has a traditional agricultural technique which minimizing the damage of the scenic view while cultivating the slope. And also, it has the value of one of the Korea unique traditional scenic views. However, The no cultivation land or disappearing desert land of rice terrace were increasing by the disadvantage of operation in land cultivation. Therefore, The Government must need preparing the base of scene resources excavation by executed the established of Korea Rice Terrace Database for preserving of Korea traditional scene. however it is getting to disappearance. And also, The High valued of Rice Terrace by cultural and scenic view which is must managed by designation of scenic sites or monument. Second, The internal and external reference book researched and analyzed results are as followings for understanding about Korea Rice Terrace feature. First of all, The Rice Terrace's dictionary meaning is just difference by each nations. However, Generally speaking that It means the terraced land by cultivated of sloped land. The Rice Terrace has cross relation with mountain valley and piedmont slope cultivation in location of condition. It occurred era is before approximately estimated from 3000 of years until 6000 of years. It can divide two type by topography shape those are slope and valley type. However, The natural element of forest has very big position in this part. But, The Rice Terrace is just managed and designated by the scenic sites with the Cultural Properties Protection Law. It must needs more binding force and effectiveness for the Rice Terrace scenic view plan establishment by scenic laws and farming and fishing village laws etc. I think that it must need the Rice Terrace related law establishment as soon as possible for efficient preservation and management of the Rice Terrace. Third, The Rice Terrace were researched and analyzed results are as followings those were executed at the Korea, China and Japan. The Korea and Japan have good Rice Terrace Characteristic. And also, The high valued scenic sites area were good managed by the Cultural Properties Protection Law as well as the superior scenic valued Rice Terrace in China. Those are also managed by designated scenic sites for protection and preservation positively. Those were managed by each autonomous district management Department. The each nation's related laws of Rice Terrace protection were just little bit different. However, The basic purpose is same. for example, it based on superior scenic view preservation and protection. Especially, The Japan's Cultural Properties Law and Scenic law linkage, and China Autonomous district legislation and effectiveness. The Korea Government must need above elements for Korea Rice Terrace culture and scenic view preservation. Fourth, We need inducing the owner system and the policy of Rice Terrace preservation promotion association for efficient preservation of Rice Terrace in japan. The owner system in japan gives the owner of the land a permission to rent the land to Rice Terrace preservation promotion association and the local government. In this system the village would be revitalized by commons in the way of the management of the terraces, beautifying the area around the terraces and etc. And also, Making the each village management operating system for Rice Terrace management through educating civilization. The civilization could receive quick help from a consultative body comprised of experts such as representatives of Cultural Heritage Administration and professors. And it is in a hurry to solve the problem of revitalization of the region by exchange between cities and the village.

Spatial Distribution of Aging District in Taejeon Metropolitan City (대전광역시 노령화 지구의 공간적 분포 패턴)

  • Jeong, Hwan-Yeong;Ko, Sang-Im
    • Journal of the Korean association of regional geographers
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    • v.6 no.2
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    • pp.1-19
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    • 2000
  • This study is to investigate and analyze regional patterns of aging in Taejeon Metropolitan city-the overpopulated area of Choong-Cheong Province-by cohort analysis method. According to the population structure transition caused by rapid social and economic changes, Korea has made a rapid progress in population aging since 1970. This trend is so rapid that we should prepare for and cope with aging society. It is not only slow to cope with it in our society, but also there are few studies on population aging of the geographical field in Korea. The data of this study are the reports of Population and Housing Censuses in 1975 and 1985 and General Population and Housing Censuses with 10% sample survey in 1995 taken by National Statistical Office. The research method is to sample as the aging district the area with high aged population rate where the populations over 60 reside among total population during the years of 1975, 1985, 1995 and to sample the special districts of decreasing population where the population decreases very much and the special districts of increasing population in which the population increases greatly, presuming that the reason why aged population rate increases is that non-elderly population high in mobility moves out. It is then verified and ascertained whether it is true or not with cohort analysis method by age. Finally regional patterns in the city are found through the classification and modeling by type based on the aging district, the special districts of decreasing population, and the special districts of increasing population. The characteristics of the regional patterns show that there is social population transition and that non-elderly population moves out. The aging district with the high aged population rate is divided into high-level keeping-up type, relative falling type below the average of Taejeon city in aging progress, and relative rising type above the average of the city. This district can be found at both the central area of the city and the suburbs because Taejeon city has the characteristic of over-bounded city. But it cannot be found at the new built-up area with the in-migration of large population. The special districts of decreasing population where the population continues to decrease can be said to be the population doughnuts found at the CBD and its neighboring inner area. On the other hand, the special districts of increasing population where the population continues to increase are located at the new built-up area of the northern part in Taejeon city. The special districts of decreasing population are overlapping with the aging district and higher in aged population rate by the out-migration of non-elderly population. The special districts of increasing population are not overlapping with the aging district and lower in aged population rate by the in-migration of non-elderly population. To clarify the distribution map of the aging district, the special districts of decreasing and increasing population and the aging district are divided into four groups such as the special districts of decreasing population group-the same one as the aging district, the special districts of decreasing population group, the special districts of increasing population group, and the other district. With the cohort analysis method by age used to investigate the definite increase and decrease of aging population through population transition of each group, it is found that the progress of population aging is closely related to the social population fluctuation, especially that aged population rate is higher with the out-migration of non-elderly population. This is to explain each model of CBD, inner area, and the suburbs after modeling the aging district, the special districts of decreasing population, and the special districts of increasing population in Taejeon city. On the assumption that the city area is a concentric circle, it is possible to divide it into three areas such as CBD(A), the inner area(B), and the suburbs(C). The special districts of increasing and decreasing population in the city are divided into three districts-the special districts of decreasing population(a), the special districts of increasing population(b), and the others(c). The aging district of this city is divided into the aging district($\alpha$) and the others($\beta$). And then modeling these districts, it is probable to find regional patterns in the city. $Aa{\alpha}$ and $Ac{\beta}$ patterns are found in the CBD, in which $Aa{\alpha}$ is the special district of decreasing population and is higher in aged population rate because of aged population low in mobility staying behind and out-migration of non-elderly population. $Ba{\alpha}$, $Ba{\beta}$, $Bb{\beta}$, and $Bc{\beta}$ patterns are found in the inner area, in which neighboring area $Ba{\alpha}$ pattern is located. $Bb{\beta}$ pattern is located at the new developing area of newly built apartment complex. $Cb{\beta}$, $Cc{\alpha}$, and $Cc{\beta}$ patterns are found in the suburbs, among which $Cc{\alpha}$ pattern is highest in population aging. It is likely that the $Cc{\beta}$ under housing land readjustment on a large scale will be the $Cb{\beta}$ pattern. As analyzed above, marriage and out-migration of new family, non-elderly population, with house purchase are main factors in accelerating population aging in the central area of the city. Population aging is responsible for the great increase of aged population with longer life expectancy by the low death rate, the out-migration of non-elderly population, and the age group of new aged population in the suburbs. It is necessary to investigate and analyze the regional patterns of population aging at the time when population problems caused by aging as well as longer life expectancy are now on the increase. I hope that this will help the future study on population aging of the geographical field in Korea. As in the future population aging will be a major problem in our society, local autonomy should make a plan for the problem to the extent that population aging progresses by regional groups and inevitably prepare for it.

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Spatial effect on the diffusion of discount stores (대형할인점 확산에 대한 공간적 영향)

  • Joo, Young-Jin;Kim, Mi-Ae
    • Journal of Distribution Research
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    • v.15 no.4
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    • pp.61-85
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    • 2010
  • Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown

    . In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(${\gamma}$). From spatial coefficient(${\gamma}$) we can infer that when the diffusion in the vicinity of the diffusing center occurs, the diffusion is influenced by one in the diffusing center. The difference between the Bass model(II) and the spatial diffusion model(IV) is statistically significant with the ${\chi}^2$-distributed likelihood ratio statistic is 16.598(p=0.0023). Which implies that the spatial diffusion model is more effective than the Bass model to describe diffusion of discount stores. So the research question (1) is supported. In addition, we found that there are statistically significant relationship between similarity of retail environment and spatial effect by using correlation analysis. So the research question (2) is also supported.

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  • Development of Predictive Models for Rights Issues Using Financial Analysis Indices and Decision Tree Technique (경영분석지표와 의사결정나무기법을 이용한 유상증자 예측모형 개발)

    • Kim, Myeong-Kyun;Cho, Yoonho
      • Journal of Intelligence and Information Systems
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      • v.18 no.4
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      • pp.59-77
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      • 2012
    • This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.


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