• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2009.04a
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• pp.138-141
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• 2009

• Journal of the Korean association of regional geographers
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• v.12 no.4
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• pp.496-507
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• 2006

A hybrid approach integrating both high-resolution and hyperspectral data sets was used to map vegetation cover of a coastal lowland area in the Hawaii Volcanoes National Park. Three common grass species (broomsedge, natal redtop, and pili) and other non-grass species, primarily shrubs, were focused in the study. A 3-step, hybrid approach, combining an unsupervised and a supervised classification schemes, was applied to the vegetation mapping. First, the IKONOS 1-m high-resolution data were classified to create a binary image (vegetated vs. non--vegetated) and converted to 20-meter resolution percent cover vegetation data to match AVIRIS data pixels. Second, the minimum noise fraction (MNF) transformation was used to extract a coherent dimensionality from the original AVIRIS data. Since the grasses and shubs were sparsely distributed and most image pixels were intermingled with lava surfaces, the reflectance component of lava was filtered out with a binary fractional cover analysis assuming that tile total reflectance of a pixel was a linear combination of the reflectance spectra of vegetation and the lava surface. Finally, a supervised approach was used to classify the plant species based on tile maximum likelihood algorithm.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.65-68
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• 2005

In order for effective disaster prevention, it is necessary to have some idea of when, where, why and what kind of weather disasters may occur, and how large they may be. But the regional characteristics of Shizuoka Prefecture from the viewpoint of weather disasters have not been studied before. In this study, the authors gathered the data which represent how many times weather disasters occurred in Shizuoka Prefecture in the last fourteen years, and then divided it into some regions using a multivariate analysis. The authors adopted principal component analysis on this data, and then adopted cluster analysis with principal component scores which must be significant in the previous analysis. Finally the authors set the regional division based on these clusters and described the regional characteristics. This study could contribute to the weather disaster prevention in Shizuoka Prefecture.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.613-619
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• 2006

This study proposed an unsupervised image classification through the dendrogram of agglomerative clustering as a higher stage of image segmentation in image processing. The proposed algorithm is a hierarchical clustering which includes searching a set of MCSNP (Mutual Closest Spectral Neighbor Pairs) based on the data structures of RAG(Regional Adjacency Graph) defined on spectral space and Min-Heap. It also employes a multi-window system in spectral space to define the spectral adjacency. RAG is updated for the change due to merging using RNV (Regional Neighbor Vector). The proposed algorithm provides a dendrogram which is a graphical representation of data. The hierarchical relationship in clustering can be easily interpreted in the dendrogram. In this study, the proposed algorithm has been extensively evaluated using simulated images and applied to very large QuickBird imagery acquired over an area of Korean Peninsula. The results have shown it potentiality for the application of remotely-sensed imagery.

• Journal of Integrative Natural Science
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• v.17 no.1
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• pp.1-12
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• 2024

Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

• Korean Journal of Environment and Ecology
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• v.24 no.1
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• pp.78-86
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• 2010

The classification of biotope type in major Korean cities was made based on the land use concept rather than the ecological concept of the land as the habitat of biological communities. Therefore, biotope type need to be reclassified according to ecological concerns and regional characteristics. This study attempts to clearly define various critical concepts regarding the classification of biotope type, such as classification hierarchy, classification criteria, classification factor, classification indicator, classification key, and classification standard. Furthermore, it also attempts to suggest the ways to improve the classification system of biotope type by sampling the cases of major Korean cities. The classification system of biotope type is required to have a coherent system that provides basic guidelines, standards and hierarchy with regard to biotic, abiotic and anthropotic factors, as well as classification indicators and classification keys.

• Journal of the Korean association of regional geographers
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• v.11 no.2
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• pp.211-232
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• 2005

Recently, Korean agriculture and rural areas face a huge crisis due to the change in the market environment of agricultural products under WTO and FTA. Thus, rural policy needs to break from the agriculture-centered sectoral perspective and to develop the various potentials in rural areas. The transformation of rural policy is also required from the aspect of increasing regional differentiation in rural areas. In this context, the paper aims to classify the regional types of rural areas and analyse their features in geographical location, population, farming, public finance and so an. The result of analysis shows that rural areas can be classified into 5, 9 or 15 regional types by stages. This implies that there is significant regional differentiation ill rural areas. However, there is regional polarization as much as differentiation in rural areas. In this point, rural policy should catch up regional polarization as well as diversity in rural areas.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.959-962
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• 1988

This paper describes an automatic visual inspection system for fabric defects based on pattern recognition techniques. The inspection for fabric defects can be separated into three sequences of operations which are the detection of fabric defects[1], the classification of figures of fabric defects, and the classification of fabric defects. Comparing projections of defect-detected images with the predefined complex, the classification accuracy of figures of fabric defects was found to be 95.3 percent. Employing the Bayes classifier using cluster shade in SGLDM and variance in decorrelation method as features, the classification accuracy of regional figure defects was found to be 82.4 percent. Finally, some experimental results for line and dispersed figures of fabric defects are included.

• Journal of the Korean association of regional geographers
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• v.17 no.1
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• pp.96-108
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• 2011

In spite of arduous policy efforts to address the deprived region problem emerged in the rapid industrialization and urbanization processes since the 1960s, it is well acknowledged that there are some policy limitations. In a recent effort to improve the policy for the deprived regions, the national territory is divided into 4 groups such as urban, rural, growth promotion, and special situation areas and various policies for the deprived regions have been consolidated into a policy for the growth promotion areas. The purpose of the study is to classify the already-designated 70 growth promotion areas and examine the differentiated characteristics of different types in order to propose more regionally situated policy approach to the deprived areas. The study shows that the types of the 70 growth promotion areas are much differentiated one another in terms of internal characteristics and dynamics. It is therefore further argued that the policy efforts need to be area-specific in order to address the policy demand for the deprives regions in a more efficient way.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.129-138
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• 2017

The aim of this paper is to suggest methodology for local governments when discovering locally customized future promising industries with regard to policies of central government, regional competencies, and industrial promising. Firstly, key industries by region specified in '5-years regional industrial development master plan(2014)' were utilized. Secondly, science and technology competency by region was calculated with analyzing patent data in each key industries. Thirdly, industrial promising was verified by calculating Knowledge Stock and Activity Index based on measuring industry-IPC linkage. Based on the methodology proposed above, case study(case of Busan city) was done. Finally, 7 core industries and 94 candidates of future promising industries were extracted on the basis of 5 digit of KSIC subdivision. The methodology is expected to contribute local governments to establish evidence-based, efficient, and future-oriented local R&D roadmapping.