• Title, Summary, Keyword: Landsat

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Conjugation of Landsat Data for Analysis of the Land Surface Properties in Capital Area (수도권 지표특성 분석을 위한 Landsat 자료의 활용)

  • Jee, Joon-Bum;Choi, Young-Jean
    • Journal of the Korean earth science society
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    • v.35 no.1
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    • pp.54-68
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    • 2014
  • In order to analyze the land surface properties in Seoul and its surrounding metropolitan area, several indices and land surface temperature were calculated by the Landsat satellites (e.g., Landsat 5, Landsat 7, and Landsat 8). The Landsat data came from only in the fall season with Landsat 5 on October 21, 1985, Landsat 7 on September 29, 2003, and Landsat 8 on September 16, 2013. The land surface properties used are the indices that represented Soil Adjusted Vegetation Index (SAVI), Modified Normalized Difference Wetness Index (MNDWI), Normalized Difference Wetness Index (NDWI), Tasseled cap Brightness, Tasseled cap Greenness, Tasseled cap Wetness Index, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) and the land surface temperature of the area in and around Seoul. Most indices distinguish very well between urban, rural, mountain, building, river and road. In particular, most of the urbanization is represented in the new city (e.g., Ilsan) around Seoul. According to NDVI, NDBI and land surface temperature, urban expansion is displayed in the surrounding area of Seoul. The land surface temperature and surface elevation have a strong relationship with the distribution and structure of the vegetation/built-up indices such as NDVI and NDBI. While the NDVI is positively correlated with the land surface temperature and is also negatively correlated with the surface elevation, the NDBI have just the opposite correlations, respectively. The NDVI and NDBI index is closely associated with the characteristics of the metropolitan area. Landsat 8 and Landsat 5 have very strong correlations (more than -0.6) but Landsat 7 has a weak one (lower than -0.5).

Analysis of Land Surface Temperature from MODIS and Landsat Satellites using by AWS Temperature in Capital Area (수도권 AWS 기온을 이용한 MODIS, Landsat 위성의 지표면 온도 분석)

  • Jee, Joon-Bum;Lee, Kyu-Tae;Choi, Young-Jean
    • Korean Journal of Remote Sensing
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    • v.30 no.2
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    • pp.315-329
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    • 2014
  • In order to analyze the Land Surface Temperature (LST) in metropolitan area including Seoul, Landsat and MODIS land surface temperature, Automatic Weather Station (AWS) temperature, digital elevation model and landuse are used. Analysis method among the Landsat and MODIS LST and AWS temperature is basic statistics using by correlation coefficient, root-mean-square error and linear regression etc. Statistics of Landsat and MODIS LST are a correlation coefficient of 0.32 and Root Mean Squared Error (RMSE) of 4.61 K, respectively. And statistics of Landsat and MODIS LST and AWS temperature have the correlations of 0.83 and 0.96 and the RMSE of 3.28 K and 2.25 K, respectively. Landsat and MODIS LST have relatively high correlation with AWS temperature, and the slope of the linear regression function have 0.45 (Landsat) and 1.02 (MODIS), respectively. Especially, Landsat 5 has lower correlation about 0.5 or less in entire station, but Landsat 8 have a higher correlation of 0.5 or more despite of lower match point than other satellites. Landsat 7 have highly correlation of more than 0.8 in the center of Seoul. Correlation between satellite LSTs and AWS temperature with landuse (urban and rural) have 0.8 or higher. Landsat LST have correlation of 0.84 and RMSE of more than 3.1 K, while MODIS LST have correlation of more than 0.96 and RMSE of 2.6 K. Consequently, the difference between the LSTs by two satellites have due to the difference in the optical observation and detection the radiation generated by the difference in the area resolution.

The Comparison of Thermal Infrared Satellite Observation for Plume Assessment of Thermal Discharge (온배수 확산 평가를 위한 열적외선 위성관측 비교)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
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    • v.24 no.4
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    • pp.367-374
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    • 2015
  • To examine the effect of thermal discharge from nuclear power plants, Sea Surface Temperature (SST) is one of the most important variables measured by satellite remote sensing. However, the study was not much comparison of field data and satellite SST from operational Landsat 8 Thermal Infrared Sensor(TIRS) and Landsat 7 ETM+. The Landsat 8 TIRS have 2 spilt Thermal Infrared channels but ETM+ uses one channel for extracting of SST. In spite of that this research carried out that Landsat 7 ETM+ have more profitable for correction of SST than Landsat 8 TIRS. The used 15 Landsat 7 and 8 Thermal Infrared data of path/row 114-36 were processed by SST algorithm of ENVI and IDL. The in-situ SST data from KHOA(Korea Hydrographic and Oceanographic Administration) compared with satellite SST and the accuracy of extracted SST were assessed by each field sites in-situ point data with time series satellite SST.

Method of Integrating Landsat-5 and Landsat-7 Data to Retrieve Sea Surface Temperature in Coastal Waters on the Basis of Local Empirical Algorithm

  • Xing, Qianguo;Chen, Chu-Qun;Shi, Ping
    • Ocean Science Journal
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    • v.41 no.2
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    • pp.97-104
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    • 2006
  • A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band's radiance ($L_{{\lambda},L7/ETM+}$) to that of Landsat-5 TM TIR ($L_{{\lambda},L5/TM+})$ as: $L_{{\lambda},L5/TM}=0.9699{\times}L_{{\lambda},L7/ETM+}+0.1074\;(R^2=1)$. In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.

Automated Image Receiving and Processing System for Landsat 7

  • Park, Sung-Og;Kim, Moon-Gyu;Kim, Tae-Jung;Ji-Hyeon, Shin;Choi, Myung-jin;Park, Jeong-Hyun
    • Proceedings of the KSRS Conference
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    • pp.573-577
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    • 2002
  • The Landsat Program is the longest running enterprise for acquisition of imagery of the Earth from space. The first Landsat satellite was launched in 1972 and the most recent, Landsat 7, was launched on April 15, 1999. The Landsat satellites have acquired millions of images. The Landsat 7 receiving station is installed at more than 25 sites and will be installed in Korea. This paper will address the work being carried out for the development of image receiving and processing system for the Landsat 7 image data, which will be used at ground station of Landsat 7 in Korea.

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Processing and Analysis of LANDSAT MSS Data for Extraction of Coastal Flow Patterns - around Incheon Bay - (연안수리현상 파악을 위한 LANDSAT MSS Data의 처리와 해석 -인천해역을 중심으로-)

  • 안철호;안기원;안호준
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.4 no.2
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    • pp.59-75
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    • 1986
  • The purpose of this study is to determine the most effective image analysis technique for extraction of coastal flow patterns from LANDSAT MSS data. Choosing the coastal area of Incheon, LANDSAT MSS data of oceanic area, which has generally low values of CCT data in comparison with the adjacent land was used On the basis of the above preparation, the most effective image analysis procedure of LANDSAT MSS data for the case of extraction of coastal flow patterns has been obtained through contrast stretching, color composite, and compression of bi-band image data.

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Landsat 8-based High Resolution Surface Broadband Albedo Retrieval (Landsat 8 위성 기반 고해상도 지표면 광대역 알베도 산출)

  • Lee, Darae;Seo, Minji;Lee, Kyeong-sang;Choi, Sungwon;sung, Noh-hun;Kim, Honghee;Jin, Donghyun;Kwon, Chaeyoung;Huh, Morang;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.741-746
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    • 2016
  • Albedo is one of the climate variables that modulate absorption of solar energy, and its retrieval is important process for climate change study. High spatial resolution and long-term consistent periods are important considerations in order to efficiently use the retrieved albedo data. This study retrieved surface broadband albedo based on Landsat 8 as high resolution which is consistent with Landsat 7. First of all, we analyzed consistency of Landsat 7 channel and Landsat 8 channel. As a result, correlation coefficient(R) on all channels is average 0.96. Based on this analysis, we used multiple linear regression model using Landsat 7 albedo, which is being used in many studies, and Landsat 8 reflectance channel data. The regression coefficients of each channel calculated by regression analysis were used to derive a formula for converting the Landsat 8 reflectance channel data to broadband albedo. After Landsat 8 albedo calculated using the derived formula is compared with Landsat 7 albedo data, we confirmed consistency of two satellite using Root Mean Square Error (RMSE), R-square ($R^2$) and bias. As a result, $R^2$ is 0.89 and RMSE is 0.003 between Landsat 7 albedo and Landsat 8 albedo.

ATMOSPHERIC CORRECTION OF LANDSAT SEA SURFACE TEMPERATURE BY USING TERRA MODIS

  • Kim, Jun-Soo;Han, Hyang-Sun;Lee, Hoon-Yol
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.864-867
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    • 2006
  • Thermal infrared images of Landsat-5 TM and Landsat-7 ETM+ sensors have been unrivalled sources of high resolution thermal remote sensing (60m for ETM+, 120m for TM) for more than two decades. Atmospheric effect that degrades the accuracy of Sea Surface Temperature (SST) measurement significantly, however, can not be corrected as the sensors have only one thermal channel. Recently, MODIS sensor onboard Terra satellite is equipped with dual-thermal channels (31 and 32) of which the difference of at-satellite brightness temperature can provide atmospheric correction with 1km resolution. In this study we corrected the atmospheric effect of Landsat SST by using MODIS data obtained almost simultaneously. As a case study, we produced the Landsat SST near the eastern and western coast of Korea. Then we have obtained Terra/MODIS image of the same area taken approximately 30 minutes later. Atmospheric correction term was calculated by the difference between the MODIS SST (Level 2) and the SST calculated from a single channel (31 of Level 1B). This term with 1km resolution was used for Landsat SST atmospheric correction. Comparison of in situ SST measurements and the corrected Landsat SSTs has shown a significant improvement in $R^2$ from 0.6229 to 0.7779. It is shown that the combination of the high resolution Landsat SST and the Terra/MODIS atmospheric correction can be a routine data production scheme for the thermal remote sensing of ocean.

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Hydrosphere Change Detection of the Basin using Multi-temporal Landsat Satellite Imagery (다시기 Landsat영상을 이용한 유역의 수계 변화 탐지)

  • Kang, Joon-Mook;Park, Joon-Kyu;Um, Dae-Yong;Lee, Yong-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.3
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    • pp.31-39
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    • 2007
  • In this study, the hydrosphere change of the Daecheong dam basin was detected qualitatively and quantitatively using Landsat satellite images until recentness since the construction of Daecheong dam. The hydrosphere change of the basin was analyzed by applying supervised classification about Landsat satellite images which were classified according to the hydrosphere, vegetation, road and etc. for four distinct years which are 1981, 1987, 1993, and 2002 year. Landsat satellite images of each year were achieved overlay analysis with extracting only the hydrosphere, and though these results, the hydrosphere change of the Daecheong dam basin was monitored efficiently.

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SLC-off Image Correlation and Usability Evaluation by Gapfill Function (Gapfill 함수에 의한 SLC off 영상 보정 및 활용성 평가)

  • Park, Joon-Kyu;Kim, Min-Gyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.8
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    • pp.3692-3697
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    • 2012
  • Landsat 7 ETM+ sensor is getting imageries in the SLC-off state since May 31, 2003 due to mechanical defect of SLC(Scan Line Corrector). Therefore additional correction works are required to use these imageries. In this study, Landsat 7 SLC-off imageries were corrected using Gapfill function and compared with Landsat 5 around the same time. Most of pixels in omitted areas due to SLC-off by producing SLC-off imageries and imageries without visual incompatibility could be achieved as there were not unnatural noises. Also, the corrected imageries were performed land cover classification which was compared with the classification result using reference image. To do this, it could be suggested the possibility of SLC-off imagery. Landsat 7 SLC-off corrected imageries will improve the difficult conditions to detect changes of large areas and be used to detect changes of large areas and classify imageries as well as to recover imagery loss arising regionally such as small scale cloud, etc.