• Title, Summary, Keyword: Wide Area Classification

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Land Cover Classification of a Wide Area through Multi-Scene Landsat Processing (다량의 Landsat 위성영상 처리를 통한 광역 토지피복분류)

  • 박성미;임정호;사공호상
    • Korean Journal of Remote Sensing
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    • v.17 no.3
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    • pp.189-197
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    • 2001
  • Generally, remote sensing is useful to obtain the quantitative and qualitative information of a wide area. For monitoring earth resources and environment, land cover classification of remotely sensed data are needed over increasingly larger area. The objective this study is to propose the process for land cover classification method over a wide area using multi-scene satellite data. Land cover of Korean peninsula was extracted from a Landsat TM and ETM+ mosaic created from 23 scenes at 100-meter resolution. Well-known techniques that used to general image processing and classification are applied to this wide area classification. It is expected that these process is very useful to promptly and efficiently grasp of small scale spatial information such as national territorial information.

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Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection

  • Lee, Jae-Won;Kim, Won-Ki;Oh, Yun-Sik;Seo, Hun-Chul;Jang, Won-Hyeok;Kim, Yoon Sang;Park, Chul-Won;Kim, Chul-Hwan
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.729-739
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    • 2015
  • An algorithm for fault detection and classification method for wide-area protection in Korean transmission systems is proposed. The modeling of 345-kV and 765-kV Korean power system transmission networks using the Electro Magnetic Transient Program - Restructured Version (EMTP-RV) is presented and the algorithm for fault detection and classification in transmission lines is developed. The proposed algorithm uses the Wavelet Transform (WT) and Singular Value Decomposition (SVD). The Singular value of Approximation coefficient (SA) and part Sum of Detail coefficient (SD) are introduced. The characteristics of the SA and SD at the fault conditions are analyzed and used in the algorithm for fault detection and classification. The validation of the proposed algorithm is verified by various simulation results.

A study of Land-Cover Classification technique Using Fuzzy C-Mean Algorithm (Fuzzy C-Mean 알고리즘을 이용한 토지피복분류기법 연구)

  • 신석효;안기원;이주원;김상철
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • pp.267-273
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    • 2004
  • The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study is used to the high-resolution (6.6m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data(36 bands).We accomplished FCM classification technique with MLC technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method.

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A Study of Land-Cover Classification Technique for Merging Image Using Fuzzy C-Mean Algorithm (Fuzzy C-Mean 알고리즘을 이용한 중합 영상의 토지피복분류기법 연구)

  • 신석효;안기원;양경주
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.2
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    • pp.171-178
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    • 2004
  • The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study was presented more better land cover classification method through an algorithm development. We accomplished FCM(Fuzzy C-Mean) classification technique with MLC (Maximum Likelihood classification) technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method. This study is used to the high-resolution(6.6m) Electro-Optical Camera(EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1(KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer(MODIS) image data(36 bands).

An Assessment of a Random Forest Classifier for a Crop Classification Using Airborne Hyperspectral Imagery

  • Jeon, Woohyun;Kim, Yongil
    • Korean Journal of Remote Sensing
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    • v.34 no.1
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    • pp.141-150
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    • 2018
  • Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

Land Suitability Classification for Rational Land Use Planning in County(Gun) Area( I ) - Methodological Considemtion of Land Suitability Classification - (군단위지역 토지이용계획의 합리적 책정을 위한 토지적성구분( I ) - 토지적성구분의 방법론적 고찰 -)

  • Hwang, Han-Cheol;Choe, Su-Myeong;Han, Gyeong-Su
    • Journal of Korean Society of Rural Planning
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    • v.1 no.1
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    • pp.65-74
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    • 1995
  • As a initial methodological approach to rational land use planning in the county-level area, three types of land suitability classification techniques were examined from the viewpoint of their practical applicability through the case study of Seungju-gun area, Chonnam-province, Korea : major factors' criteria(method I ), principal component analysis( I ), and local monitoring( R( ). Each method has its strong and weak points as shown in Tab.-5. Therefore, when its practical application, there seem to be wide-range methodological selectivities from exclusive use of the best one to intermethodological combination of related ones In the beginning stage, intermethodological combination of all three types were tried to formulate the best solution possible. However, because of reliability problem of method R accrued from non- uniformity of evaluators'quality, only two methods( 1 , E ) were combined into a new evaluation method The applied results of the new combined method to case study area are shown in Fig.-2, 3 and 4.

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Simplification of Tunnel Support System in Karst (석회암 공동발달지역의 터널지보패턴개발에 대한 연구)

  • 김상환;허종석;전덕찬
    • Proceedings of the Korean Geotechical Society Conference
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    • pp.281-288
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    • 2003
  • In karst formation area, the tunnel support system is an important factor for the tunnel safety during operation. This paper presents the simplified tunnel support systems to be adopt in karst formation. For the tunnel planned in the project area, karst features and the expected scenarios in the tunnel area were developed based on the results of the geological and geotechnical assessment. In order to provide specific supporting system and construction details for a wide range of possible karst features, the generalized typical support systems are developed according to the classification of karst features. In addition, the initial support systems and construction sequence for each karst feature are also presented in this paper.

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Frequency Forecasting Model for Next Wireless Multimedia Services (멀티미디어 이동통신서비스를 위한 주파수 수요예측 모형)

  • Jang, Hee-Seon;Han, Sung-Su;Yeo, Jae-Hyun;Choi, Sung-Ho
    • IE interfaces
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    • v.18 no.3
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    • pp.333-342
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    • 2005
  • In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group and its applications are presented.

Forecasting Methodology of the Radio Spectrum Demand (무선자원 서비스 수요예측 방안)

  • Kim Jeom-Gu;Jang Hee-Seon;shin Hyun-Cheul
    • The Journal of Information Technology
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    • v.5 no.4
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    • pp.173-183
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    • 2002
  • In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group.

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A Study on Forest Land Classification Using Multivariate Statistical Methods : A Case Study at Mt. Kwanak (다변수통계방법을 이용한 산지분류에 관한 연구)

  • 정순오
    • Journal of the Korean Institute of Landscape Architecture
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    • v.13 no.1
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    • pp.43-66
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    • 1985
  • Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.

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