• 제목/요약/키워드: Landsat TM Image

검색결과 249건 처리시간 0.029초

인공위성 영상자료를 이용한 북한산국립공원 휴식년제도의 효과 분석 (Assessment of the Effectr of Closing Trails in Puk'ansan National Park Based on Satellite Image Analysis)

  • 이혜선;이인성;윤은주
    • 한국환경생태학회지
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    • 제13권2호
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    • pp.153-159
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    • 1999
  • 이 논문은 북한산국립공원에서 1994년부터 실시하고 있는 자연휴식년제도의 효과를 검증하고 추후 휴식년의 적용이 필요한 구간을 파악하기 위하여 인공위성 영상자료를 이용하여 휴식년 적용구간과 그 주변 등산로의 식생활력의 변화를 분석하였다. 이용된 자료는 1988년, 1992년, 1994년, 1996년 9월의 Landsat TM 영상으로, ER Mapper 및 Arc/Info GIS를 이용하여 분석하였고, 식생활력의 측정은 중합차식생지수(NDVI)에 기반한 평균비율(MR)을 이용하였다. 분석결과 휴식년 적용구간의 경우 88년 이후 감소양상을 보이던 식생활력이 휴식년제도가 실시된 94년 이후 뚜렷하게 증가하여 휴식년제도의 실시가 식생활력을 증가시키는 효과가 있었음을 보여주었다. 기타 등산로의 경우는 92년 이후 식생활력이 정체 또는 감소추세를 나타내었으며, 그 중 일부 구간은 식생활력의 저하가 특히 두드러지게 나타나 추후 휴식년제도의 적용이 필요한 구간으로 판단되었다.

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Standardized Agricultural Land Use Classification Scheme at Various Spatial Resolution of Satellite Images

  • Hong Seong Min;Jung In Kyun;Park Geun Ae;Kim Seong Joon
    • 한국농공학회논문집
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    • 제46권7호
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    • pp.15-21
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    • 2004
  • This study is to present a standardized agricultural land use classification scheme at various spatial resolution (from 1 m to 30 m) of satellite images including Landsat TM, KOMPSAT-1 EOC, ASTER VNIR and IKONOS panchromatic (PAN) and multi-spectral (MS) images. The satellite images were interpreted especially for identifying agricultural land use, crop types, agricultural facilities and structures of 18 items. It was found that there is a threshold spatial resolution between 4 m and 6.6 m to identify the full items. Thus it is suggested that IKONOS fusion image (MS enhanced by PAN) is required to produce land use map for agricultural purpose.

원격탐사와 지구정보시스템 (GIS)을 이용한 이천분지의 사면안정평가 (Analysis of Slope Stability by Using Remote Sensing and GIS in Ichon Basin)

  • 원종석;이영훈
    • 자원환경지질
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    • 제30권3호
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    • pp.241-248
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    • 1997
  • In this study, Ichon basin is selected as study area and regional analysis of geological structure are done by using lineament analysis. The factors which affects slope stability, are chosen, and integrated to database using GIS (Geoscientific Information System). Landsat TM band 4, 5 and 7 are choosen and processed by various image enhancement technique to analyse the regional geological lineaments. Spatial distribution of lineament is analysed through lineament density map and study area can be divided the eight structural domains. Considering environmental geological characteristics of study area, rating and weighting of each factors for slope stability analysis are determined and spatial analysis of regional slope stability is examined through overlaying technique of GIS. The result of areal distribution of slope stability shows that the most unstable area is all over Mt. Buksung, Mt. Daepo, Mt. Songrim and Mt. Yankak.

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원격탐사와 GIS를 이용한 대전광역시 토지이용 변화 검출 (Urban Land Use Change Detection over Daejon Metropolitan Area using Bi-temporal Landsat TM image with the Integration of GIS)

  • 안승만;신진민;신동훈;이규석
    • 환경영향평가
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    • 제11권4호
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    • pp.239-246
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    • 2002
  • 지난 몇 십 년 동안 한국에서는 도시의 확장으로 인해 인구 밀집지역에서의 토지이용이 급속하게 변화되었으며, 그 결과 도시의 환경은 악화되었다. 도시화는 도시민에 필요한 녹지의 크기와 수를 감소시킬 뿐만 아니라, 서식처 파괴의 원인이 되며, 적절한 녹지의 배치 또는 배열이 이뤄지지 않을 경우 도시내 생태적 기능의 결핍을 초래한다. 경관변화의 증명과 분석은 토지이용변화의 환경 요소의 인과관계 파악에 중요하다. 원격탐사와 지형정보체계는 토지이용 변화의 경향과 영향을 이해할 수 있어 녹지공간변화 파악에 사용된다. 원격탐사는 동일대상지의 다른 시기에서의 영상자료를 이용해 토지이용의 경년변화를 파악하며 지형정보체계는 이를 저장, 분석에 활용되고 있다. 본 연구는 원격탐사와 지형정보체계를 이용하여, 1989년부터 1998년 동안, 대전광역시의 토지이용 변화를 파악하며 그 원인을 살펴보는데 있다.

선형분광혼합화소분석을 이용한 서부지역 DMZ의 토지피복 변화 탐지 (Land-Cover Change Detection of Western DMZ and Vicinity using Spectral Mixture Analysis of Landsat Imagery)

  • 김상욱
    • 한국지리정보학회지
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    • 제9권1호
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    • pp.158-167
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    • 2006
  • 본 연구는 DMZ 및 민통선지역의 토지피복 변화양상을 생태학적 측면에서 파악해보는데 목적을 두고 있다. 한반도 허리를 가르는 대상형 지역인 DMZ에 대하여 남북간 왕래가 잦은 서부지역에 대하여 토지피복특성을 파악해 보았는데, 비접근지역인 연구지역 특성상 본 연구에서는 위성영상자료를 활용하여 토지피복의 현황 및 변화특성을 파악해 보았다. '80년대 중반(Landsat TM, '87.05.20) 및 2000년대 초반의 영상(Landsat ETM+, '02.06.06)을 활용함으로써 최근 15년 동안 토지피복이 어떻게 변화했는지 파악하였으며, 생태적 가치가 큰 DMZ 지역의 토지피복 분류정확도를 높이기 위하여, 선형분광혼합화소분석(linear spectral mixture analysis : LSMA)을 이용하였다. 이 분석법은 하나의 화소를 단일한 지표물로 가정하여 영상을 처리하는 기존의 기법과 달리, 각 화소의 토지피복의 혼합정도를 세분화 한 후 대상지의 토지피복 특성을 가장 잘 반영하는 순수한 화소값 별로 분할영상(fraction image)을 생성하였는데, 본 연구에서는 식생, 토양, 수문의 3가지 화소에 대한 분할영상을 생성하였다. 분석결과 토지피복 가운데 산림지역의 면적이 가장 많은 감소를 가져왔는데, 남한지역의 경우 산림의 $39.04km^2$가, 북한지역은 $52.37km^2$가 다른 토지피복으로 변화되었다. 농경지의 경우 북한은 농경지 면적의 $56.15km^2$가 나대지로 변화되었는데, 이는 남한에 비하여 농경지 관리가 소홀하여 나대지 상태로 방치되고 있음을 알 수 있다. 공간적인 측면에서 볼 때, 민통선지역의 경우 전반적으로 토지피복의 변화가 나타나고 있으며, DMZ 내부의 경우도 장단반도 주변지역, 파주시 및 북한 판문군지역의 경우 그 변화가 민통선지역과 비슷한 양상을 보이고 있다.

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APPLICATION AND CROSS-VALIDATION OF SPATIAL LOGISTIC MULTIPLE REGRESSION FOR LANDSLIDE SUSCEPTIBILITY ANALYSIS

  • LEE SARO
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.302-305
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    • 2004
  • The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

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CROSS-VALIDATION OF ARTIFICIAL NEURAL NETWORK FOR LANDSLIDE SUSCEPTIBILITY ANALYSIS: A CASE STUDY OF KOREA

  • LEE SARO;LEE MOUNG-JIN;WON JOONG-SUN
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.298-301
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    • 2004
  • The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

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APPLICATION OF LOGISTIC REGRESS10N A MODEL FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AT JANGHUNG, KOREA

  • Saro, Lee;Choi, Jae-Won;Yu, Young-Tae
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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    • pp.64-64
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    • 2003
  • The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.

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Application of a weight-of-evidence model to landslide susceptibility analysis Boeun, Korea

  • Moung-Jin, Lee;Yu, Young-Tae
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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    • pp.65-70
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    • 2003
  • The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$+/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction

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APPLICATION OF LIKELIHOOD RATIO A MODEL FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AT JANGHUNG, KOREA

  • Choi, Jae-Won;Lee, Saro;Yu, Young-Tae
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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    • pp.63-63
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    • 2003
  • The aim of this study is to apply and verify of Bayesian probability model, the likelihood ratio and statistical model, at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the likelihood ratio coefficient were overlaid for landslide susceptibility mapping, Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.

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