• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.2
• /
• pp.44-54
• /
• 2005

In this study the tidal area in Seo han bay, North Korea was detected and extracted by using various satellite images (ASTER, KOMPSAT EOC, Landsat TM/ETM+) and GIS spatial analysis. Especially, the micro-landform was classified through the spectral characteristic of each satellite image and the change of tidal flat size was detected on passing year. For this, the spectral characteristics of eight tidal flat area in Korea, which are called as Seo han bay, Gwang ryang bay, Hae iu bay, Gang hwa bay, A san bay, Garorim bay, Jul po bay and Soon chun bay, were analyzed by using multi band of multi spectral satellite images such as Landsat TM/ETM+. Moreover, the micro-landform tidal flat in Seo han bay, North Korea was extracted by using ISODATA clustering based on the result of spectral characteristic. In addition, in order to detect the change of tidal flat size on passing years, the ancient topography map (1918-1920) was constructed as GIS DB. Also, the tidal flat distribution map based on the temporal satellite images were constructed to detect the tidal flat size for recent years. Through this, the efficient band to classify the micro-landform and detect its boundary was clarified and one possibility of KOMPSAT EOC application could be also introduced by extracting the spatial information of tidal flat efficiently.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.13 no.1
• /
• pp.31-38
• /
• 1988

This paper presents a methodology for the development of a part classification and coding system suited to each individual company. When coding a group of parts for a specific company by a general purpose part classification & coding system like OPITZ system, it is frequently observed that we use only a small subset of total available code numbers. Such sparsity in the actual occurrences of code numbers implies that we can design a better system which uses digits of the system more parsimoniously. A 2-dimensional fuzzy ISODATA algorithm is developed to extract the important characteristics for the classification from the set of given parts. Based on the extracted characteristics nd the distances between fuzzy clustering cenetroids, a company-unique classification and coding system can be developed. An example case study for a medium sized machine shop is presented.

• Atmosphere
• /
• v.19 no.2
• /
• pp.169-182
• /
• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2011.06a
• /
• pp.34-36
• /
• 2011

ENCs is edited based on the numerical charts for publishing paper charts and serviced in forms of grid styles. For this reason, the density of sounding information of ENCs is not consistent and was required for improvement. In this study, K-Means, ISODATA clustering algorithm as classification methods for satellite image was reviewed and adopted to case study. The developed results include loading module of ENC data, improvement algorithm of sounding information, writing module of ENC data. According to the results of algorithm, we could confirm the improved result.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.6
• /
• pp.2511-2520
• /
• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• KCID journal
• /
• v.21 no.1
• /
• pp.45-54
• /
• 2014

In this study, Agricultural Infrastructures of Shincheon-gun in North Korea are investigated using Kompsat-2 and RapidEye satellite imagery. Target agricultural infrastructures are agricultural landuse, irrigation and drainage canals, dammed pools for irrigation and pumping stations. KOMPSAT-2 satellite imagery are use to investigate agricultural hydraulic structures and agricultural landuse are investigated by RapidEye Imagery. Geometric correction are performed using 28 GCP and QUAC method are used for atmospherical correction in all imagery. ISODATA clustering and naked-eye classification method are used for extracting agricultural hydraulic structures and Object-based analysis is applied to classifying the agricultural landuse. Extraction results of agricultural hydraulic structures and agricultural are presented and we suggest the applicability of satellite imagery to investigate agricultural infrastructures in North Korea.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2004.03a
• /
• pp.593-598
• /
• 2004

본 연구에서는 위성영상자료 Landsat TM(1999.8.16), ETM+(2002.9.17)을 활용하여 북한 서한만 지역의 NDVI, 토지피복, 지표온도 분포도를 작성하여 경년에 따른 환경변화를 탐지 및 분석하였으며 ISODATA Clustering 기법을 적용하여 북한 서한만 일대의 간석지 분포도를 작성하였다. 북한 서해안 간석지 면적변화 탐지를 위하여 고지형도 (1918)를 디지털 자료로 변환하여 북한 서해안 전역의 간석지 GIS DB를 구축하였으며 위성영상자료를 이용하여 작성된 간석지 공간 분포도와의 비교ㆍ분석을 통하여 북한 서한만 일대의 84년간의 간석지 면적변화를 탐지하였다. 이러한 연구 결과를 바탕으로 북한 서해안 지역의 간석지 퇴적 환경정보 및 다양한 연안 환경정보를 구축할 수 있었으며 북한 서해안 지역과 남한 서해안 지역의 간석지 연안환경 비교 분석 등을 위한 기초자료로 활용될 것으로 판단된다.

• The KIPS Transactions:PartC
• /
• v.8C no.3
• /
• pp.311-318
• /
• 2001

본 논문에서는 연결수락 제어시 사용자가 전송하는 트래픽 파라메타(샐 개수의 분산값과 평균값)를 압축하여 망에 신고하는 방법을 제안하고, 압축방법에 의한 연결수락제어의 성능을 분석 비교한다. 트래픽 파라메타 압축방법은 K-means, CL(Competitive Learning), Fuzzy ISODATA,FNC(Fuzzy Neural Clustering)를 사용한다. 제안한 트래픽 파라메타의 압축에 의한 연결수락제어는 퍼지 매핑함수(Fuzzy Mapping Funciton)fp 의해 신고한 트래픽 패턴을 추정하고, 전방향 구조의 신경망을 사용하여 연결의 수락/거절을 결정한다. ON-OFF 트래픽 모델 환경에서 컴퓨터 실험을 통하여 여러 가지 압축방법들을 사용한 연결수락제어의 성능을 Fuzziness 값에 따라 비교하였고, 그 결과 FNC 방법이 우수함을 알 수 있었다. EH한 연결수락제어의 성능을 높히기 위해서 관측 프레임의 셀 분산값이 크면 Fuzziness 값을 작게 선정하고, 작으면 상대적으로 크게 선정해야 함을 알 수 있었다.

• Journal of Environmental Impact Assessment
• /
• v.27 no.5
• /
• pp.489-508
• /
• 2018

As climate changes, it is necessary to predict changes in the habitat environment in order to establish more aggressive adaptation strategies. The bioclimatic classification which clusters of areas with similar habitats can provide a useful ecosystem management framework. Therefore, in this study, biological habitat environment of Northeast Asia was identified through the establishment of the bioclimatic zones, and the impac of climate change on the biological habitat was analyzed. An ISODATA clustering was used to classify Northeast Asia (NEA)into 15 bioclimatic zones, and climate change impacts were predicted by projecting the future spatial distribution of bioclimatic zones based upon an ensemble of 17 GCMs across RCP4.5 and 8.5 scenarios for 2050s, and 2070s. Results demonstrated that significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward, and some zones were predicted to be greatly expanded or shrunk where we suggested as regions requiring intensive management. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

• Korean Journal of Remote Sensing
• /
• v.27 no.4
• /
• pp.457-466
• /
• 2011

The objectives of this study are to produce level 3 type LULC map and analysis of phenological features of North Korea, ISODATA clustering of the 88scenes of MVC of MODIS NDVI in 2008 and 8scenes in 2009 was carried out. Analysis of phenological phases based mapping method was conducted, In level 2 type map, the confusion matrix was summarized and Kappa coefficient was calculated. Total of 27 typical habitat types that represent the dominant species or vegetation density that cover land surface of North Korea in 2008 were made. The total of 27 classes includes the 17 forest biotopes, 7 different croplands, 2 built up types and one water body. Dormancy phase of winter (${\sigma}^2$ = 0.348) and green up phase in spring (${\sigma}^2$ = 0.347) displays phenological dynamics when much vegetation growth changes take place. Overall accuracy is (851/955) 85.85% and Kappa coefficient is 0.84. Phenological phase based mapping method was possible to minimize classification error when analyzing the inaccessible land of North Korea.