• Journal of Practical Agriculture & Fisheries Research
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• v.8 no.1
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• pp.3-20
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• 2006

The Ministry of Agriculture and Forestry announced promoting the project, 'Regional Agricultural Clusters,' in Feb. 2004 through 「The Comprehensive Plan for the Agriculture and Agricultural Communities」 and initiated a model project from 2005. The purpose of 'Regional Agricultural Clusters' is to develop regional agriculture by concentrating the resources and capacities of the region and maximizing the effect of integrating related projects. 31 towns in Geonggi and 2 towns (Ganghwa and Ongjin) in Incheon were chosen for the study based on the crop areas of 36 agricultural products from the Agricultural Census in 2000. For those 33 towns, factors such as the top 20 agricultural products, main producing districts and surveys on each towns were considered and we have concluded that these items are good subjects for 'Regional Agricultural Clusters' : We have decided on 18 items for what we call, 'Mini-Clusters,' a cluster in which the item's main producing district is in only one area of the town in question (in 30 projects out of 21 towns). Secondly, we have decided on 11 items for what we call, 'Base-Clusters,' a cluster in which the item's main producing district can be associated by name with the item, the production is sizeable, and can be found in several locations of the town in question (in 13 projects out of 11 towns). Finally, we have decided on 12 items for what we call, 'Broad-Based-Clusters, a cluster which the item's main producing district expands the past the vicinity of the town in question (in 19 projects out of 19 towns).

• Journal of Korean Society of Rural Planning
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• v.12 no.1 s.30
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• pp.37-48
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• 2006

The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

• Journal of Agricultural Extension & Community Development
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• v.29 no.4
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• pp.191-201
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• 2022

This study aims to segment the rural tourists markets according to benefits sought after the COVID-19 outbreak. Data were collected from 284 usable visits in 20 rural tourism village. Results show that it was classified into three clusters from factor-cluster analysis, The first cluster was 'negative participation type', and the overall pursuing benefit factor was low. The second cluster was 'complex pursuit type', and all the pursuing benefit factors were higher than the average. The third cluster was 'experience-seeking type', and the benefits of pursuing rural experiences, special experiences, and intimacy were high. Each cluster showed differences in educational background, age, residential area, type of visit, awareness, satisfaction, and behavioral intention of rural tourism villages.

• Journal of Korean Society of Rural Planning
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• v.16 no.1
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• pp.9-20
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• 2010

The aim of this paper is to identify Korean agricultural and agri-manufacturing cluster using a multi-regional input-output model. This paper derives a representative set of five agricultural and agri-manufacturing clusters in Korea in terms of spatial and industrial interdependency. The results show that agriculture and agri-manufacturing clusters agglomerated in Seoul Metropolitan Area and Chungcheong Area are linked both production and manufacture functions, whereas Gangwon Area is more focused on production and Jeolla Area is more concentrated on manufacture.

• Korean Journal of Agricultural Science
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• v.43 no.1
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• pp.40-51
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• 2016

This study analyzed settlement condition changes of Chungcheong region's mountain area during 10 years, from 2001 to 2012. We performed factor analysis and cluster analysis of data from the 'Census for Mountain Area' carried out by the Korea Forest Service in 2001 and 2012. Factors 1, 2, 3, and 4 represent 'the superiority of non-agricultural income', 'the industrialized mountainous area', 'residential conveniences and benefits', and 'the use of forest resources', respectively. Clusters 1, 2, 3, 4, and 5 are categorized as 'non-agricultural income', 'various mass social functions', 'production of forest products', 'industrialized mountainous region', and 'ordinary mountain region', respectively. We suggest that cluster 1 has potential for development and should be promoted as a possible tourist attraction by digging up geographically unique themes. Cluster 2 has great potential for development and needs planned management through the maintenance or expansion of existing infrastructure. Cluster 3 has potential for development with various high value added industries uncovered. Cluster 4 shows vitality as it holds plenty of more job opportunities than other regions. Cluster 5 is deteriorating as a mountainous region because of an aging population, and it urgently demands development. For a decade, 45 of the 60 regions belonged to a single category, which are now differentiated broadly into two types: Firstly, deterioration changes to potential development and Secondly, vitality is differentiated into potential development and deterioration.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.33-45
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• 2005

This study investigates the core elements of the formation and development of cluster using a multi-disciplinary approach and suggests a promoting strategy by development stage of cluster. As a sub-category of regional innovation system, the cluster has been considered as one of the most noticeable methodological argument to make the regional innovation system come true. In the meantime, this study examines the core elements of cluster shown in the theories and examples through six academic fields such as economics, geography, regional development, business administration, sociology and pedagogy and their educational back-ground. By means of establishing the incubation stage in the development of cluster, core elements are composed in the stages of birth, incubation and evolution in subsequent manner. A promoting strategy will be suggested through the implication of core elements in the reestablished stages.

• The Korean Journal of Community Living Science
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• v.21 no.4
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• pp.619-631
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• 2010

The purpose of this study is to segment and examine urban farmers behavior by applying a two-step cluster analysis and multi-nominal logit model. The data were collected by a telephone survey with two-staged stratified random sampling in the cities around the country for the purpose of acquiring representative data. Respondents were asked to describe their awareness of urban agriculture, their agricultural activity, and sociodemographic characteristics. Among 2,000 cases, 381 cases(19.1%) which were of participants in urban agriculture were analysed in SPSS. From the findings, 27.3% of respondents had heard the word 'urban agriculture', and 25.5% of them regarded themselves as urban farmers. Four different clusters were derived from two-step clusters based on motive, place, companion, area and hours. They were 'Large scale hobby farming(cluster 1)', ‘Weekend farm/ hobby farming(cluster 2)', 'Land/ Self-supporting farming(cluster 3)', and 'Small scale hobby farming(cluster 4)'. The result of multinomial logistic regression showed that there were significant differences among these four segmented groups in terms of age, city size and housing type. In other words, there is quite a possibility that urbanites select different urban farming types according to their socio-demographic profiles. Therefore, the urbanite profiles can be used as the basis for promoting policy of several urban agriculture types. According to the result, policy directions for facilitating urban agriculture were presented.

• Korean Journal of Environmental Biology
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• v.36 no.1
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• pp.21-32
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• 2018

This study was carried out to define the characteristics of the identified ground-dwelling invertebrate communities at Nari basin and Tonggumi area in Ulleungdo Island, designated as a nationally important agricultural heritage. The habitat types were divided into the following categories: crop land, forest, and ecotone, and the soil-dwelling invertebrates were collected according to habitat type. The ground-dwelling invertebrates were collected using a pitfall trap, and a self-organizing map (SOM) was applied to the invertebrates dataset to define the characteristics in invertebrates distribution. The SOM clearly classified the relevant information into four clusters, and extracted ecological information from the invertebrates dataset. The cluster II was composed of invertebrate communities which are collected in the Tonggumi area. The Tonggumi area is where mountainous areas were developed for agricultural purposes, which has geographical features commonly observed in Ulleungdo Island. It is noted that the cluster II has different characteristics as compared other clusters. The results of this study are expected to be used for the preservation of agricultural environment and maintenance of biodiversity by providing basic data, on the biotope of Ulleungdo Island designated as a nationally important agricultural heritage and information on the characteristics of the applicable ground-dwelling invertebrate communities.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1282-1291
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• 1993

The color image of the rose was segmented by the cluster analysis on the color space into the characteristic sub-regions, the degree of bloom of the flower was represented numerically base on the segmented image and judged by the artificial neural network system whose input variable were the characteristic regions. Judgement by neural system were compared with that of the farmers and it was found that degree of agreement were fairly good.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.1
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• pp.59-67
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• 2015

Because reservoirs that supply irrigation water play an important role in water resource management, it is necessary to evaluate the vulnerability of this particular water supply resource. The purpose of this study is to provide water supply risk maps of agricultural reservoirs in South Korea using irrigation vulnerability model and cluster analysis. To quantify water supply risk, irrigation vulnerability indices are estimated to evaluate the performance of the water supply on the agricultural reservoir system using a probability theory and reliability analysis. First, the irrigation vulnerability probabilities of 1,346 reservoirs managed by Korea Rural Community Corporation (KRC) were analyzed using meteorological data on 54 meteorological stations over the past 30 years (1981-2010). Second, using the K-mean method of non-hierarchical cluster analysis and pre-simulation approach, cluster analysis was applied to classify into three groups for characterizing irrigation vulnerability in reservoirs. The morphology index, watershed area, irrigated area, and ratio between watershed and irrigated area are selected as the clustering analysis parameters. It is suggested that the water supply risk map be utilized as a basis for the establishment of risk management measures, and could provide effective information for a reasonable decision making on drought risk mitigation.