• 제목/요약/키워드: land-use classification

검색결과 363건 처리시간 0.024초

LANDSAT TM과 JERS-1 OPS 영상을 이용한 도시지역의 토지이용 변화 검출 (Detecting Land Use Changes in an Urban Area using LANDSAT TM and JERS-1 OPS Imagery)

  • 이진덕;연상호;유재엽;김성길
    • 한국지리정보학회지
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    • 제2권1호
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    • pp.73-83
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    • 1999
  • 위성영상으로부터 주기적으로 얻어지는 토지이용 및 토지피복 정보는 지표환경이 급변하는 도시지역의 변화를 검출하는데 효과적으로 활용될 수 있다. 또한 이들 정보는 도시정보시스템에서 공간데이터베이스 구축을 위한 베이스맵으로서, 그리고 바람직한 도시계획 및 개발방향을 위한 의사결정자료로서 활용될 수 있을 것이다. 본 연구에서는 구미시를 사례지로 하여 1991년과 1997년에 수집된 Landsat TM과 JERS-1 OPS 영상데이터로부터 토지이용에 대한 무감독 및 감독분류를 각각 행하고 토지이용 변화를 검출하였다.

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An Application of Canonical Correlation Analysis Technique to Land Cover Classification of LANDSAT Images

  • Lee, Jong-Hun;Park, Min-Ho;Kim, Yong-Il
    • ETRI Journal
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    • 제21권4호
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    • pp.41-51
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    • 1999
  • This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

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군단위지역 토지이용계획의 합리적 책정을 위한 토지적성구분(II) - 토지이용적성의 종합화 방안 - (Land Suitability Classification for Rational Land Use Planning in County(Gun) Area(II) Determination of the land Use Suitability to Integrate the Classified Values -)

  • 황한철;최수명;한경수
    • 농촌계획
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    • 제2권1호
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    • pp.31-38
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    • 1996
  • As a rational decision-making process of county-level area development, this study designed 3-step framework : function-giving(areal analysis) on unit planning area by decision matrix of land suitability, check of typical characteristics of each function area and formulation of its future development strategies. Two alternatives were suggested as the areal analysis method, of which one is equal ordering / valuing technique of checking indices for land suitability classfication and the other preferential weighting technique. And then, under the algorithm specially defined in this study, land suitability maps(Fig.2,3) of the case study area (Seungju-county area, Chonnam-province, Korea) were drawn from the areal analysis results. By use of land suitability classification results, unique characteristics of typical function areas were defined (on 7 types of alternative 1 , 8 types of II ) and their future development strategies were formulated in the case study area, According to the categorization criteria in this study, all the villages of the case area were classfied as a suitable type of function areas illustrated in this study.

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지리정보시스템(GIS)을 이용한 경산시의 토지잠재력 분석 (A Land Capability Analysis in Kyungsan, Korea Using Geographic Information System)

  • 오정학;정성관
    • 한국조경학회지
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    • 제26권3호
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    • pp.34-44
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    • 1998
  • The purpose of this study is to provide the basic data for land use in the future, which result from analyzing land use, obtained after studying on the natural environment by Geographic Information System and Remote Sensing. The results of this study are as follows : ·According to the classification of land-cover, agricultural land use is relatively prominent except for overall natural covering. According to the average value of Green Vegetation Index class, the average value of GVI is 3.0, and 45% of the regions have relatively good condition of floral state. ·With a view to natural environment, the survey shows that the altitude of 90% of the total areas is below 400m, and most of them are flattened or moderately-inclined area. Therefore, this region has a good condition to be used for development. · The area for the first class in preservation degree of natural scenery of Namcheon-Myun is 2.3% of the total areas. According to the results about unstable areas on all sides, unstable districs are distributed in so small-scale units that they will be safe from some damages drawn by developing activity. But we have to consider every aspects for the future development of them. In this study, the natural environment-variables are regarded firstly, and effective designation of the land with natural environment is researched too. However, to establish more practical developing plan, ecological and human variables should be regarded.

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고해상도 위성영상과 수치지형도를 이용한 지목 불부합의 정도 측정 (Land Category Non-coincidence Measurements Using High Resolution Satellite Images and Digital Topographic Maps)

  • 홍성언;이동헌;박수홍
    • Spatial Information Research
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    • 제12권1호
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    • pp.43-56
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    • 2004
  • 필지는 지번, 지목, 경계, 면적이라는 기본적인 구성요소를 가지고 있다. 그 가운데 토지의 가치는 대부분 지목에 의해 결정된다. 많은 수익이나 산출이 기대되는 용도로 토지를 이용하려는 경향에 따라 토지이용 전환이 많이 이루어지고 있다. 결국, 이것은 토지의 불법 형질변경, 난개발 등의 원인이 되고 있고, 지목 불부합의 발생을 가중시키고 있다. 그러나 이에 대한 대처나 정리는 상대적으로 미흡한 편이다. 본 연구에서는 고해상도 위성영상과 수치지형도를 이용하여 지목을 기반으로 한 필지별 토지이용/토지피복을 분류할 수 있는 방법을 제안하였다. 이렇게 분류된 필지별 토지이용/토지피복도와 편집지적도상의 지목을 비교·분석하여 지목 불부합 정도를 통계적으로 측정하였다. 그 결과 연구지역의 불부합 정도에 대한 통계적인 해석이 가능하여, 향후 지적 불부합지를 정량적으로 자동 해석할 수 있는 가능성을 제시할 수 있었다.

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Crop Field Extraction Method using NDVI and Texture from Landsat TM Images

  • Shibasaki, Ryosuke;Suzaki, Junichi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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    • pp.159-162
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    • 1998
  • Land cover and land use classification on a huge scale, e.g. national or continental scale, has become more and more important because environmental researches need land cover: And land use data on such scales. We developed a crop field extraction method, which is one of the steps in our land cover classification system for a huge area. Firstly, a crop field model is defined to characterize "crop field" in terms of NDVI value and textual information Textual information is represented by the density of straight lines which are extracted by wavelet transform. Secondly, candidates of NDVI threshold value are determined by "scale-space filtering" method. The most appropriate threshold value among the candidates is determined by evaluating the line density of the area extracted by the threshold value. Finally, the crop field is extracted by applying level slicing to Landsat TM image with the threshold value determined above. The experiment demonstrates that the extracted area by this method coincides very well with the one extracted by visual interpretation.

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일본 장야현 송천촌(長野縣 松川村)의 농촌토지이용조정제도 (A Case Study on the Rural Zoning System of Local Government in Japan)

  • 윤원근
    • 농촌지도와개발
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    • 제13권2호
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    • pp.341-355
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    • 2006
  • The purpose of this study is to introduce the case of advancement of rural zoning system in a local government of Japan. The Matzgawa county, one of the local governments in Japan, sets up a new zoning system which advanced in using rural resources. In order to develop and revitalize rural region, it is necessary to use all kinds of rural resources, including agricultural as well as non-agricultural resources comprehensively. Also, the classification of agricultural land use should be reformed. The zoning on rural land should be changed to include not only agricultural use but also non-agricultural use, so as to manage comprehensively agricultural land use and its conversions. Furthermore, the land use regulation should be applied to each zone of the agricultural land.

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최신토지피복자료를 이용한 대구시의 열환경 수치모의 (Application of the Latest Land Use Data for Numerical Simulation of Urban Thermal Environment in the Daegu)

  • 이현주;이귀옥;원경미;이화운
    • 한국대기환경학회지
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    • 제25권3호
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    • pp.196-210
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    • 2009
  • The land surface precesses is very important to predict urban meteorological conditions. Thus, the latest land use data set to reflect the rapid progress in urbanization was applied to simulate urban thermal environment in Daegu. Because use of the U.S geological Survey (USGS) 25-category data, currently in the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), does not accurately described the heterogeneity of urban surface, we replaced the land use data in USGS with the latest land-use data of the Korea Ministry of Environment over Daegu. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 5 classes to account for heterogeneity of urban land cover. The new land cover classification (MC-LULC) improved the capability of MM5 to simulate the daytime part of the diurnal temperature cycle in the urban area. The 'MC-LULC' simulation produced the observed temperature field reasonably well, including spatial characteristics. The warm cores in western Daegu is characterized by an industrial area.

A Neuro-Fuzzy Model Approach for the Land Cover Classification

  • Han, Jong-Gyu;Chi, Kwang-Hoon;Suh, Jae-Young
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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    • pp.122-127
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    • 1998
  • This paper presents the neuro-fuzzy classifier derived from the generic model of a 3-layer fuzzy perceptron and developed the classification software based on the neuro-fuzzl model. Also, a comparison of the neuro-fuzzy and maximum-likelihood classifiers is presented in this paper. The Airborne Multispectral Scanner(AMS) imagery of Tae-Duk Science Complex Town were used for this comparison. The neuro-fuzzy classifier was more considerably accurate in the mixed composition area like "bare soil" , "dried grass" and "coniferous tree", however, the "cement road" and "asphalt road" classified more correctly with the maximum-likelihood classifier than the neuro-fuzzy classifier. Thus, the neuro-fuzzy model can be used to classify the mixed composition area like the natural environment of korea peninsula. From this research we conclude that the neuro-fuzzy classifier was superior in suppression of mixed pixel classification errors, and more robust to training site heterogeneity and the use of class labels for land use that are mixtures of land cover signatures.

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Analysis of land use change for advancing national greenhouse gas inventory using land cover map: focus on Sejong City

  • Park, Seong-Jin;Lee, Chul-Woo;Kim, Seong-Heon;Oh, Taek-Keun
    • 농업과학연구
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    • 제47권4호
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    • pp.933-940
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    • 2020
  • Land-use change matrix data is important for calculating the LULUCF (land use, land use change and forestry) sector of the national greenhouse gas inventory. In this study, land cover changes in 2004 and 2019 were compared using the Wall-to-Wall technique with a land cover map of Sejong City from the Ministry of Environment. Sejong City was classified into six land use classes according to the Intergovernmental Panel on Climate Change (IPCC) guidelines: Forest land, crop land, grassland, wetland, settlement and other land. The coordinate system of the land cover maps of 2004 and 2019 were harmonized and the land use was reclassified. The results indicate that during the 15 years from 2004 to 2019 forestlands and croplands decreased from 50.4% (234.2 ㎢) and 34.6% (161.0 ㎢) to 43.4% (201.7 ㎢) and 20.7% (96.2 ㎢), respectively, while Settlement and Other land area increased significantly from 8.9% (41.1 ㎢) and 1.4% (6.9 ㎢) to 35.6% (119.0 ㎢) and 6.5% (30.3 ㎢). 79.㎢ of cropland area (96.2 ㎢) in 2019 was maintained as cropland, and 8.8 ㎢, 1.7 ㎢, 0.5 ㎢, 5.4 ㎢, and 0.4 ㎢ were converted from forestland, grassland, wetland, and settlement, respectively. This research, however, is subject to several limitations. The uncertainty of the land use change matrix when using the wall-to-wall technique depends on the accuracy of the utilized land cover map. Also, the land cover maps have different resolutions and different classification criteria for each production period. Despite these limitations, creating a land use change matrix using the Wall-to-Wall technique with a Land cover map has great advantages of saving time and money.