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Science China Earth Sciences

, Volume 56, Issue 1, pp 1–12 | Cite as

An improved Landsat Image Mosaic of Antarctica

  • FengMing Hui
  • Xiao Cheng
  • Yan Liu
  • YanMei Zhang
  • YuFang Ye
  • XianWei Wang
  • Zhan Li
  • Kun Wang
  • ZhiFei Zhan
  • JianHong Guo
  • HuaBing Huang
  • XiuHong Li
  • ZiQi Guo
  • Peng Gong
Research Paper

Abstract

A revised Landsat Image Mosaic of Antarctica (LIMA) is presented, using the 1073 multi-band scenes of the original Land-sat-7 ETM+ LIMA image collection available at the United States Geological Survey (USGS: http://lima.usgs.gov/). Three improvements have been applied during the data processing: (1) DN saturation is adjusted by adopting a linear regression, which has a lower root mean square error than the ratio regression used by LIMA; (2) solar elevation angle is calculated using pixel-level latitude/longitude and the acquisition time and date of the central pixel of the scene, improving slightly upon the bilinear interpolation of the solar elevation angles of scene corners applied in LIMA; and (3) two additional image bands, Band 5 and Band 7, are sharpened using the panchromatic band (Band 8) and a Gram-Schmidt Spectral Sharpening algorithm to more easily distinguish snow, cloud and exposed rocks. The final planetary reflectance product is stored in 16-bit bands to preserve the full radiometric content of the scenes. A comparative statistical analysis among 12 sample regions indicates that the new mosaic has enhanced visual qualities, information entropy, and information content for land cover classification relative to LIMA.

Keywords

Landsat Antarctica ice sheet mosaic remote sensing 

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Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • FengMing Hui
    • 1
    • 2
  • Xiao Cheng
    • 1
    • 2
  • Yan Liu
    • 1
    • 2
  • YanMei Zhang
    • 3
  • YuFang Ye
    • 4
  • XianWei Wang
    • 1
  • Zhan Li
    • 5
  • Kun Wang
    • 1
    • 2
  • ZhiFei Zhan
    • 1
    • 2
  • JianHong Guo
    • 1
  • HuaBing Huang
    • 1
  • XiuHong Li
    • 1
    • 2
  • ZiQi Guo
    • 1
  • Peng Gong
    • 1
  1. 1.State Key Laboratory of Remote Sensing ScienceJointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of SciencesBeijingChina
  2. 2.College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina
  3. 3.Institute of Earthquake ScienceChina Earthquake AdministrationBeijingChina
  4. 4.Institute of Environmental PhysicsUniversity of BremenBremenGermany
  5. 5.Department of Geography & EnvironmentBoston UniversityBostonUSA

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