• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.171-188
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• 2013

Landuse changes and cadastral information error categories in the four major river areas were analyzed for the use of policy data as cadastral re-arrangement of national and public lands would be required, using high-resolution air-photographs and cadastral maps before and after the river development. The study sites were the river areas of 40km around four dams of the Nakdong river where their landuses were changed most. As the results, national and public lands reached 79.9% of land parcels and 93.3% of land areas of the study sites similar with those of the four river areas, 84.3% of land parcels and 85.5% of land areas. The landuse classification of the study sites before the four river development was consisted most of 'river'(71.6%) and 'rice field'(12.3%), but after the development the 'river' was reduced to 42.7% and 'park area'(19.6%) including sport fields and 'mixed lots'(20.8%) were increased. Also, 86.7% of land parcels before the development could be reduced after the development if administrative districts and land ownerships were not considered. Cadastral information error categories can be found as cadastral polygon missing, polygon overlap, location and boundary non-coincidence, small polygon generation, and non-coincidence between cadastral boundary and river boundary. Landuse change monitoring method using air-photographs will be useful to analyze landuse state through fast information aquisition and to manage properties of national and public lands such as river areas.

• The Korean Journal of Ecology
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• v.19 no.5
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.591-600
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• 2018

Recent SAR systems provide fully polarimetric SAR data, which is known to be useful in a variety of applications such as disaster monitoring, target recognition, and land cover classification. The objective of this study is to evaluate the performance of polarization SAR data for landslide detection. The detectability of different SAR parameters was investigated based on the supervised classification approach. The classifier used in this study is the Adaptive Boosting algorithms. A fully polarimetric L-band PALSAR-2 data was used to examine landslides caused by the 2016 Kumamoto earthquake in Kyushu, Japan. Experimental results show that fully polarimetric features from the target decomposition technique can provide improved detectability of landslide site with significant reduction of false alarms as compared with the single polarimetric observables.

• Journal of the Korean Institute of Landscape Architecture International Edition
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• no.2
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• pp.51-56
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• 2004

This paper discussed the use of the urban greening space beside nature land----special sites of urban Greening. Consider: the special sites of urban greening are referred to the space formed by urban building and framing, where plants can grow under natural or artificial condition. Filly using those spaces will efficiently increase green area, improving ecological environment and landscape in urban area. A classification to special sites of urban greening was put forward, which are the habits of plant combine with the form of buildings. The present status and future trends on urban greening at special sites was discussed and analyzed. Consider: there are two developing trends of the research of urban greening at special sites. Firstly, it is more naturalize and ecologize greening landscape. Secondly, It will take form a techologize in the process of constructing and materials.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.215-225
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• 2004

A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The 'local' segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. The 'global' segmentor of the second stage, which has not spatial constraints for merging, clusters the segments resulting from the previous stage, using the conventional agglomerative approach. Using simulation data, the proposed method was compared with another hierarchical clustering technique based on 'mutual closest neighbor.' The experimental results show that the new approach proposed in this study considerably increases in computational efficiency for larger images with a low number of bands. The technique was then applied to classify the land-cover types using the remotely-sensed data acquired from the Korean peninsula.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.303-306
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• 2006

이 연구에서는 C 밴드 SAR 자료이면서 서로 다른 편광 상태의 자료를 제공할 수 있는 다중 시기 Radarsat-1 자료와 ENVISAT ASAR 자료를 이용한 토지 피복 분류를 수행하였다. 다중 시기/편광 자료로부터 평균 후방산란계수, 시간적 변이도, 긴밀도 등의 특징을 기본적으로 추출하였고, 이외에 상호 비교를 위해 주성분 분석을 이용한 특징 추출을 시도하였다. 특징들을 이용한 분류기법으로는 Random Forests를 적용하였다. 충남 예당평야 일대를 대상으로 사례연구를 수행한 결과, 주성분 분석을 통한 특징과 다편광 자료를 이용하였을 때 분류 정확도가 향상되는 것으로 나타났다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1058-1061
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• 1993

Fuzzy set theory has been extensively researched in various fields of engineering. In nuclear science, a significant influence of fuzzy sets can be noticed. However, applications of fuzzy set theory to nuclear engineering is novel. In this paper, we start with a basic statement of the decision-making process based on fuzzy set theory, and then apply it to nuclear science with some practical applications (a fuzzy decision making in an accidental release to the atmosphere as well as in a problem of land suitability classification). We believe that the use of fuzzy set theory in nuclear science has potential advantages.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.3
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• pp.153-162
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• 2015

Land information is important for the international agricultural companies. This study investigated the agriculture and soil information in Sri Lanka. This study is the results from investigation of soil properties and agricultural properties determined by the Soil Taxonomy classification system for the soils in Sri Lanka. The order of the main agricultural imports in Sri Lanka was wheat > refined Sugar > dry Onion > Rice > Lentils. The climate of Sri Lanka is divided into three climatic zones. There are a wet zone, an intermediate zone, and a dry zone. Rainfall of the wet zone was $3,000-5,000mm\;year^{-1}$. The rainfall of the dry zone was less than $1,000m^{-1}$. The intermediate zone was in the middle area. Soil series of Sri Lanka were 109 in total. Detailed information of soil series was: 6 of soil Orders, 15 of Suborders, 39 of Great groups, and 56 of Subgroups. Soil texture of topsoil was much more coarse, but subsoil was gravelly coarse soil. Soil of Sri Lanka was classified as a Soil Order. The orders were Entisols > Alfisols > Ultisols > Inceptisols > Histosols > Vertisols.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.81-86
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• 2009

This research is a part of the Intelligent Urban Facility Management project of the Korean Land Spatialization Group (KGSL). First, this study started from the investigation of existing u-City service model in order to drive essential components and considerations for the urban facilities management system. Considering the driven conclusions, this study finally proposed the new classification system of urban facilities management service model and the adequate application method in u-City.

• Management & Information Systems Review
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• v.3
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.