• Title/Summary/Keyword: Landsat 7 image

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Particulate Distribution Map of Tidal Flat using Unsupervised Classification of Multi-Temporary Satellite Data (다중시기 위성영상의 무감독분류에 의한 갯벌의 입자 분포도)

  • 정종철
    • Korean Journal of Remote Sensing
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    • v.18 no.2
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    • pp.71-79
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    • 2002
  • This research presents particulate distribution map of tidal flats of Hampyung bay using reflectance which extracted from satellite data and field survey data during same periods. The spectrum of particulate composition obtained from Landsat TM data was analysed and 7 scenes of satellite image were classified with ISODATA and K-MEANS methods. The results of unsupervised classification were estimated with in-situ data. The classification accuracy of ISODATA and K-MAMS methods were 84.3% and 85.7%. For validation of classified results of multi-temporal satellite images, TM image of May 1999(reference data), which was classified with field survey data was compared with classified results of multi-temporary satellite data.

Fire Severity Mapping Using a Single Post-Fire Landsat 7 ETM+ Imagery (단일 시기의 Landsat 7 ETM+ 영상을 이용한 산불피해지도 작성)

  • 원강영;임정호
    • Korean Journal of Remote Sensing
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    • v.17 no.1
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    • pp.85-97
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    • 2001
  • The KT(Kauth-Thomas) and IHS(Intensity-Hue-Saturation) transformation techniques were introduced and compared to investigate fire-scarred areas with single post-fire Landsat 7 ETM+ image. This study consists of two parts. First, using only geometrically corrected imagery, it was examined whether or not the different level of fire-damaged areas could be detected by simple slicing method within the image enhanced by the IHS transform. As a result, since the spectral distribution of each class on each IHS component was overlaid, the simple slicing method did not seem appropriate for the delineation of the areas of the different level of fire severity. Second, the image rectified by both radiometrically and topographically was enhanced by the KT transformation and the IHS transformation, respectively. Then, the images were classified by the maximum likelihood method. The cross-validation was performed for the compensation of relatively small set of ground truth data. The results showed that KT transformation produced better accuracy than IHS transformation. In addition, the KT feature spaces and the spectral distribution of IHS components were analyzed on the graph. This study has shown that, as for the detection of the different level of fire severity, the KT transformation reflects the ground physical conditions better than the IHS transformation.

Extraction of Soil Wetness Information and Application to Distribution-Type Rainfall-Runoff Model Utilizing Satellite Image Data and GIS (위성영상자료와 GIS를 활용한 토양함수정보 추출 및 분포형 강우-유출 모형 적용)

  • Lee, Jin-Duk;Lee, Jung-Sik;Hur, Chan-Hoe;Kim, Suk-Dong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.3
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    • pp.23-32
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    • 2011
  • This research uses a distributed model, Vflo which can devide subwater shed into square grids and interpret diverse topographic elements which are obtained through GIS processing. To use the distributed model, soil wetness information was extracted through Tasseled Cap transformation from LANDSAT 7 $ETM^+$ satellite data and then they were applied to each cell of the test area, unlike previous studies in which have applied average soil condition of river basin uniformly regardless of space-difference in subwater shed. As a resut of the research, it was ascertained the spatial change of soil wetness is suited to the distributed model in a subwater shed. In addition, we derived out a relation between soil wetness of image collection time and 10 days-preceded rainfall and improved the feasibility of weights obtained by the relation equation.

Monitoring Spatiotemporal Changes of Tidal Flats in Go-Gunsan Islands by Environmental Factors using Satellite Images (위성영상을 활용한 환경 요인에 따른 고군산 군도 간석지의 시공간적 변화 탐지)

  • Lee, Hong-Ro;Lee, Jae-Bong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.8 no.3
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    • pp.34-43
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    • 2005
  • We will catch the spatio-temporal changes that analyse the unknown topography of Go-Gunsan Islands using Landsat TM satellite images into an unsupervised ISODATA classification and a supervised nearest likelihood classification. Each sedimental topography has the different characteristics according to building the Saemangeum embarkment. We will deal with the distribution of sedimental shapes using ERDAS Imagine 8. 6. The result that classifies specifically topographic properties of our research area be considered to get use of establishing the reclaiming program and predicating the reclaimed sedimental topography. The research area can be classified into tidal flats and sea level using band 4 among 7 bands of Landsat TM. Also band 5 can be used to classify the special unknown shapes of tidal flats. We will clarify the efficiency that spatio-temporal sedimental changes can be extracted through processing satellite images. Therefore, the spatio-temporal unknown topography change monitoring using satellite images is expected to be very useful to clarify whether the tidal flat is generated or not in the Go-Gunsan Islands at the outer side of the embarkment after constructing completely the Saemangeum tidal embarkment.

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Study on an algorithm for atmospheric correction of Landsat TM imagery using MODTRAN simulation

  • Oh, Sung-Nam;Yu, Sung-Yeol;Lee, Hyun-Kyung;Kim, Yong-Sup;Park, Kyung-Won
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.103-109
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    • 1998
  • A technique on atmospheric correction algorithm for a single band (0.76-0.90 $\mu$m) reflective of Landsat TM imagery has been developed using a radiation transfer model simulation. It proceeds in two steps: First, calculation of the surface reflectance of each pixel based on precomputed planetary albedo functions for actual atmospheres(e. g. radiosonde) and two kinds of atmospheric visibility states. Second, approximate correction of the adjacency pixel effect by taking into account the average reflectance in an 7 $\times$ 7 pixel neighbourhood and using appropriate land cover classification in reflectance. The correction functions are provided by MODTRAN model.

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Application of satellite image data to management plan of large-scale irrigation projects

  • Torii, Kiyoshi;Yaota, Kiyoyuki;Hata, Takeshi;Abdelhadi, A.W.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1233-1235
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    • 2003
  • We are studying large-scale irrigation projects of 100,000 ha to 1,000,000 ha in the world with emphasis on their historical courses of development, geographical conditions, water managements, planting conditions and landuse changes. Recent advancement in GIS/remote sensing techniques has enabled us to proceed studies in this field in more details. Here, we describe the results of analysis on distribution of irrigation canals, three-dimensional shape of the irrigation area and planting conditions of agricultural products investigated last year in Gezira irrigation project, Sudan, using Landsat 7 ETM data and DEM supplied by USGS.

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An Analysis of the Landuse Classification Accuracy Using PCA Merged Images from IRS-1C PAN Data and Landsat TM Data (IRS-1C PAN 데이터와 Landsat TM 데이터의 PCA 중합화상을 이용한 토지이용 분류 정확도 분석)

  • Ahn, Ki-Won;Lee, Hyo-Sung;Seo, Doo-Chun;Shin, Sok-Hyo
    • Journal of Korean Society for Geospatial Information Science
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    • v.7 no.1 s.13
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    • pp.87-95
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    • 1999
  • The min object of this study was to prove the effectiveness of PCA(principal component analysis) merged images produced by PCA method using high resolution IRS-1C PAN data and multispectral Landsat TM data A sample data which has ten classes was generated for evaluation of the overall classification accuracy. In result, merged sample image which TM13457 bands with IRS-1C PAN data by PCA method showed best result (95.1%). Especially, the largest improve (6.2%) in classification accuracy was resulted when IRS-1C PAN data was merged with TM123457 or TM13457 images. In addition, landuse classification accuracy of the PCA merged images was improved (5.16%) than original color composite images of Landsat TM data.

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Introduction of Integrated Management of Satellite Imagery Information

  • Chae, Gee-Ju;Yoon, Geun-Won;Hwang, Tae-Hyun;Park, Jong-Hyun
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.197-201
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    • 2002
  • The high prices of satellite images prevent researchers from studying remote sensing and most non-professional people doesn't have the simple and easy solutions for the manipulation of satellite images. "Integrated Management of Satellite Imagery Information" project which will be promoted by ETRI (Electronics and Telecommunications Research Institute) will provide the solutions for the above mentioned problems. We will introduce the archiving center in this study. This includes the data construction, storage, management and distribution. We first review the background for this archiving center and introduce the interior and foreign institutes which archive and distribute satellite images. We review our H/W system and S/W system briefly. Finally, the further service of our project will be suggested. Since we will distribute the satellite images (Landsat, SPOT, JERS, Corona, Kompast-1) and will receive Landsat7 ETM+ in 2003 you, this will help the professional work dealing with the satellite image and attract the non-professional people for simple and easy manipulation solutions of satellite image.

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Landsat TM Image Compression Using Classified Bidirectional Prediction and KLT (영역별 양방향 예측과 KLT를 이용한 인공위성 화상데이터 압축)

  • Kim Seung-Jin;Kim Tae-Su;Park Kyung-Nam;Kim Young-Choon;Lee Kuhn-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.1
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    • pp.1-7
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    • 2005
  • We propose an effective Landsat TM image compression method using the classified bidirectional prediction (CBP), the classified KLT and the SPIHT. The SPIHT is used to exploit the spatial redundancy of feature bands selected in the visible range and the infrared range separately. Regions of the prediction bands are classified into three classes in the wavelet domain, and then the CBP is performed to exploit the spectral redundancy. Residual bands that consist of difference values between the original band and the predicted band are decorrelated by the spectral KLT Finally, the three dimensional (3-D) SPIHT is used to encode the decorrelated coefficients. Experiment results show that the proposed method reconstructs higher quality Landsat TM image than conventional methods at the same bit rate.