• Title/Summary/Keyword: Landsat/TM

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Identifying Urban Heat Island Effects due to Urban Land Use Change

  • Shin Dong-hoon;Lee Kyoo-seock
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.22-24
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    • 2004
  • The land use has changed rapidly since 1960s in accordance with urbanization in Seoul Metropolitan Region. As a result, the urban microclimate has undergone changes as well. This study aims to recognize trend of the urban heat island change which is caused by land use change during urbanization in large city. Thermal data of Landsat TM images in 1987 and 1999 were for land surface temperature change detection in the study.

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An Iterative Approach to Contextual Classification of Remote Sensing Images (공간적 상관성의 반복적 결합을 이용한 원격탐사 화상 분류)

  • 박노욱;지광훈
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.9-14
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    • 2003
  • 본 연구에서는 원격탐사 화상의 분류를 목적으로 분광정보와 공간적 상관성의 반복적 결합방법을 제안하였다. 퍼지이론을 기반으로 공간적 상관성을 분류 과정에 적용하기 위하여 초기단계에서 정의된 소속 함수에 대해서 주변영역에 대한 필터링을 적용하였고, 특정 수렴 조건을 만족하는 단계까지 반복적 결합을 수행하였다. Landsat TM 화상에 적용한 결과, 향상된 분류정확도와 분광정보만으로 분류가 애매한 화소의 공간적 분포 양상을 확인할 수 있었다.

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Using ASTER TIR imagery to identify Heat Islands: A case study of New Jersey (ASTER 열적외선 이미지를 이용한 열섬 현상 탐지: 뉴저지를 사례로)

  • Park, Gwang yong;David W. Gwynn;David A. Robinson
    • Proceedings of the KGS Conference
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    • 2004.05a
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    • pp.56-56
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    • 2004
  • The ability to detect urban heat islands in satellite imagery is a function of spatial, spectral, and temporal resolutions. Imagery from the satellite-mounted Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor acquired since December 1999 allows us to view the Earth at a higher spectral resolution in the thermal infrared (TIR) portion of the electromagnetic spectrum than most other satellite systems (e.g., AVHRR, Landsat TM). (omitted)

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SCS Curve Number Estimations from the Satellite Image (위성영상을 이용한 유출곡선번호의 추정)

  • 박희성;박승우
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.519-524
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    • 1999
  • In order to assess the estimtions of CN for a small agricultural watershed using the satellite image, TM image from Landsat-5 was classsified by MLC. CN for each pixels in the image was estimaed using the results. For the estimation enhancing , it was tried that each land use area in a pixel was estimated by the mixel assumption and the averaged CN by weight areas. Those resutls were applied for the actual hydrologic analyses were highly concerned with the observed runoff discharge and more enhanced on the mixel assumption.

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Land Cover Classification and SCS Runoff Estimation using Remotely Sensed Imaged (위성영상을 이용한 토지피복 분류 및 SCS 유출량 산정)

  • 이윤아;함종화;장석길;김성준
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.544-549
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    • 1999
  • The objective of this study is to identify the applicability of land cover image classified by remotely sensed data ; Landsat TM merged by SPOT for hydrological applications such as SCS runoff estimation . By comparing the calssified land cover image with the statistical data, it was proved that hey are agreed well with little errors. As a simple application , SCS runoff estimation was tested by varying rainfall intensity and AMC with Soilmap classfied by hydrologica soil map.

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The Generation of SPOT True Color Image Using Neural Network Algorithm

  • Chen, Chi-Farn;Huang, Chih-Yung
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.940-942
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    • 2003
  • In an attempt to enhance the visual effect of SPOT image, this study develops a neural network algorithm to transform SPOT false color into simulated true color. The method has been tested using Landsat TM and SPOT images. The qualitative and quantitative comparisons indicate that the striking similarity can be found between the true and simulated true images in terms of the visual looks and the statistical analysis.

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Unsupervised segmentation of Multi -Source Remotely Sensed images using Binary Decision Trees and Canonical Transform

  • Mohammad, Rahmati;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.23.4-23
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    • 2001
  • This paper proposes a new approach to unsupervised classification of remotely sensed images. Fusion of optic images (Landsat TM) and radar data (SAR) has beer used to increase the accuracy of classification. Number of clusters is estimated using generalized Dunns measure. Performance of the proposed method is best observed comparing the classified images with classified aerial images.

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Dispersion Pattern of CoolingWater of Kori Atomic Power Station Using Thermal Infrared Data (열적외선 자료에 의한 고리 원자력발전소의 냉각수 확산에 대한 연구)

  • 姜必鍾;智光薰
    • Korean Journal of Remote Sensing
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    • v.3 no.2
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    • pp.81-87
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    • 1987
  • The study was to analysis the dispersion of the cooling water of Kori atomic power station using thermal infrared data. The dispersion pattern of the cooling water analysis clearly on the LANDSAT TM band 6. It was changed due to tidal current, that is, the cooling water disperses north-eastern direction during the low tide and southweatern direction during the high tide. The relative temperature distribution was mapped through the density slicing method on the images.

Forest Fire Damage Analysis Using Satellite Images (위성영상을 이용한 산불재해 분석)

  • Kang, Joon-Mook;Zhang, Chuan;Park, Joon-Kyu;Kim, Min-Gyu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.21-28
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    • 2010
  • Forest fire is one of the main factor disturbing the environment of forest, and it influences greatly the structure and function on forest. The process of vegetation recovery could be decided according to the extent of the damage. It is required a lot of man powers and budgets to understand born severity and process of vegetation rehabilitation at the damaged area after large-fire. However, the analysis of born severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. In this study, the space sensors have been used to map area burned, assess characteristics of active fires. For classifying fire damaged area and analyzing severity of Cheongyang-Yesan fire in 2002, in this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ to compute the evaluate large-scale patterns of burn severity, use the digital stock map to calculate the damaged condition about the forest fires damaged regions and use the NDVI to monitoring the situation of the revegetation.