• Title/Summary/Keyword: landsat

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Estimating the Heat Island Development Using Landsat TM and AMeDAS Data

  • Harada, Ippei;M.A., Mohammed Aslam;Kondoh, Akihiko
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.450-452
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    • 2003
  • In the present investigation, an estimation of the growth of heat island development of Tokyo metropolis which accounts nearly 100 sq. km of areal spread has been carried out. Band 6 data of LANDSAT TM (Thematic Mapper) data acquired on August 1984 and 1994 have been used for estimating the expansion of the heat island development. Since the vegetation decrease is usually associated with the heat island development, a ratio of green covering has also been assessed using TM data. In order to establish the relationship with the air temperature, AMeDAS(Automated Meteorological Data Acquisition System) data have been correlated.

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Image Map Extraction from Precision Processed Landsat Multispectral Scanner(MSS) and Thematic Mapper(TM)Images

  • Yang, Young-Kyu;Bae, Young-Rae
    • Korean Journal of Remote Sensing
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    • v.2 no.2
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    • pp.107-116
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    • 1986
  • A unique approach to access Landsat satellite imagery has been implemented on IBM PC microcomputer in order to generate image maps to be used as a substitute and/or supplement for a conventional topographic map. This method enables user to automatically: o extract a nominal image map, o geoencode or calibrate as an image map, and o create a multitemporal image file using CCTs containing precision processed Landsat MSS and TM images. These map extraction process includes: o location of map area in the selected CCT, o conversion of map coordinates to image coordinates, o extraction of map area, and o rotation of image to the true North/South and East/Weat direction.

ATC: An Image-based Atmospheric Correction Software in MATLAB and SML

  • Choi, Jae-Won;Won, Joong-Sun;Lee, Sa-Ro
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.417-425
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    • 2008
  • An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.

Regional Geological Mapping by Principal Component Analysis of the Landsat TM Data in a Heavily Vegetated Area (식생이 무성한 지역에서의 Principal Component Analysis 에 의한 Landsat TM 자료의 광역지질도 작성)

  • 朴鍾南;徐延熙
    • Korean Journal of Remote Sensing
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    • v.4 no.1
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    • pp.49-60
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    • 1988
  • Principal Component Analysis (PCA) was applied for regional geological mapping to a multivariate data set of the Landsat TM data in the heavily vegetated and topographically rugged Chungju area. The multivariate data set selection was made by statistical analysis based on the magnitude of regression of squares in multiple regression, and it includes R1/2/R3/4, R2/3, R5/7/R4/3, R1/2, R3/4. R4/3. AND R4/5. As a result of application of PCA, some of later principal components (in this study PC 3 and PC 5) are geologically more significant than earlier major components, PC 1 and PC 2 herein. The earlier two major components which comprise 96% of the total information of the data set, mainly represent reflectance of vegetation and topographic effects, while though the rest represent 3% of the total information which statistically indicates the information unstable, geological significance of PC3 and PC5 in the study implies that application of the technique in more favorable areas should lead to much better results.

Lineaments and Circular/Arc Structure on the Landsat TM Imagery (한반도 Lineament와 Circular/Arc Structure 연구)

  • 강필종;조민조;이봉주
    • Korean Journal of Remote Sensing
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    • v.7 no.2
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    • pp.95-111
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    • 1991
  • The study is to analyze and interpret lineaments and circular/arc structures on the Landsat TM images which cover the Korean peninsula and the attched islands except the Ulneung island. The Landsat TM images which cover the Korean territory are 23 scenes, and band 3 and band 5 were selected for the study from seven bands, because the both vands are sensitive on soil moisture and geological materials. Lineament trend analysis Sinian direction (NNE-SSW), Pyeongan direction(NW-SE), Yodong direction(NE-SW), Korean direction(NNW-SSE) and Danyang direction (WNW-ESE) are predominant lineament trands of Korea. Circular/arc structures can be devided into four categories according to their origin; 1) volcanic activity origin, 2) granite intrusion oringin, 3) structural origin and 4) the others.

Monitoring of Forest Burnt Area using Multi-temporal Landsat TM and ETM+ Data

  • Lee, Seung-Ho;Kim, Cheol-Min;Cho, Hyun-Kook
    • Korean Journal of Remote Sensing
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    • v.20 no.1
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    • pp.13-21
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    • 2004
  • The usefulness of the multi-temporal satellite image to monitoring the vegetation recovery process after forest fire was tested. Using multi-temporal Landsat TM and ETM+data, NDVI and NBR changes over times were analyzed. Both NDVI and NBR values were rapidly decreased after the fire and gradually increased for all forest type and damage class. However, NBR curve showed much clearer tendency of vegetation recovery than NDVI. Both indices yielded the lowest values in severely damaged red pine forest. The results show the vegetation recovery process after forest fire can detect and monitor using multi-temporal Landsat image. NBR was proved to be useful to examine the recovering and development process of the vegetation after fire. In the not damaged forest, however the NDVI shows more potential capability to discriminate the forest types than NBR..

Observation of Ice Gradient in Cheonji, Baekdu Mountain Using Modified U-Net from Landsat -5/-7/-8 Images (Landsat 위성 영상으로부터 Modified U-Net을 이용한 백두산 천지 얼음변화도 관측)

  • Lee, Eu-Ru;Lee, Ha-Seong;Park, Sun-Cheon;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1691-1707
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    • 2022
  • Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

Monitoring of Lake area Change and Drought using Landsat Images and the Artificial Neural Network Method in Lake Soyang, Chuncheon, Korea (Landsat 영상 및 인공 신경망 기법을 활용한 춘천 소양호 면적 및 가뭄 모니터링)

  • Eom, Jinah;Park, Sungjae;Ko, Bokyun;Lee, Chang-Wook
    • Journal of the Korean earth science society
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    • v.41 no.2
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    • pp.129-136
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    • 2020
  • Drought is an environmental disaster typically defined as an unusual deficiency of water supply over an extended period. Satellite remote sensing provides an alternative approach to monitoring drought over large areas. In this study, we monitored drought patterns over about 30 years (1985-2015), using satellite imagery of Lake Soyang, Gangwondo, South Korea. Landsat images were classified using ISODATA, maximum likelihood analysis, and an artificial neural network to derive the lake area. In addition, the relationship between areas of Lake Soyang and the Standardized Precipitation Index (SPI) was analyzed. The results showed that the artificial neural network was a better method for determining the area of the lake. Based on the relationship between the SPI value and changes in area, the R2 value was 0.52. This means that the area of the lake varied depending on SPI value. This study was able to detect and monitor drought conditions in the Lake Soyang area. The results of this study are used in the development of a regional drought monitoring program.

High Resolution Ocean Color Products Estimation in Fjord of Svalbard, Arctic Sea using Landsat-8 OLI (Landsat-8 OLI를 이용한 북극해 스발바드 피요르드의 고해상도 Ocean Color Product 산출)

  • Kim, Sang-Il;Kim, Hyun-Cheol;Hyun, Chang-Uk
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.809-816
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    • 2014
  • Ocean Color products have been used to understand marine ecosystem. In high latitude region, ice melting optically influences the ocean color products. In this study, we assessed optical properties in fjord around Svalbard Arctic sea, and estimated distribution of chlorophyll-a and suspended sediment by using high resolution satellite data, Landsat-8 Operational Land Imager (OLI). To estimate chlorophyll-a and suspended sediment concentrations, various regression models were tested with different band ratio. The regression models were not shown high correlation because of temporal difference between satellite data and in-situ data. However, model-derived distribution of ocean color products from OLI showed a possibility that fjord and coastal areas around Arctic Sea can be monitored with high resolution satellite data. To understand climate change pattern around Arctic Sea, we need to understand ice meting influences on marine ecosystem change. Results of this study will be used to high resolution monitoring of ice melting and its influences on the marine ecosystem change at high latitude. KOPRI (Korea Polar Research Institute) has been operated the Dasan station on Svalbard since 2002, and study was conducted using Arctic station.

An Efficient Method to Estimate Land Surface Temperature Difference (LSTD) Using Landsat Satellite Images (Landsat 위성영상을 이용한 지표온도차 추정기법)

  • Park, Sung-Hwan;Jung, Hyung-Sup;Shin, Han-Sup
    • Korean Journal of Remote Sensing
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    • v.29 no.2
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    • pp.197-207
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    • 2013
  • Difficulties of emissivity determination and atmospheric correction degrade the estimation accuracy of land surface temperature (LST). That is, since the emissivity determination of land surface material and the correction of atmospheric effect are not perfect, it is very difficult to estimate the precise LST from a thermal infrared image such as Landsat TM and ETM+, ASTER, etc. In this study, we propose an efficient method to estimate land surface temperature difference (LSTD) rather than LST from Landsat thermal band images. This method is based on the assumptions that 1) atmospheric effects are same over a image and 2) the emissivity of vegetation region is 0.99. To validate the performance of the proposed method, error sensitive analysis according to error variations of reference land surface temperature and the water vapor is performed. The results show that the estimated LSTD have respectively the errors of ${\pm}0.06K$, ${\pm}0.15K$ and ${\pm}0.30K$ when the water vapor error of ${\pm}0.302g/cm^2$ and the radiance differences of 0.2, 0.5 and $1.0Wm^{-2}sr^{-1}{\mu}m$ are considered. And also the errors of the LSTD estimation are respectively ${\pm}0.037K$, ${\pm}0.089K$, ${\pm}0.168K$ in the reference land surface temperature error of ${\pm}2.41K$. Therefore, the proposed method enables to estimate the LSTD with the accuracy of less than 0.5K.