• DocumentCode
    792278
  • Title

    Selection of IRS-P6 LISS-4 MO mode band for producing band-sharpened multispectral imagery

  • Author

    Kumar, A. Senthil ; Kumar, A. S Kiran ; Navalgund, R.R.

  • Author_Institution
    Nat. Remote Sensing, Agency Dept. of Space Balanagar, Hyderabad, India
  • Volume
    3
  • Issue
    1
  • fYear
    2006
  • Firstpage
    32
  • Lastpage
    35
  • Abstract
    The recently launched IRS-P6 satellite has a unique capability of acquiring simultaneously multispectral data at three different spatial resolutions from three independent optical sensors (LISS-4, LISS-3 and AWIFS). Of these, the LISS-4 sensor can be operated in two modes: (i) multispectral (MX) mode covering a swath of 23 km and (ii) monochromatic (MO) mode covering a 70-km swath, both at a spatial resolution of 5 m. One of the important uses of the LISS-4 MO data is in realizing a 5 m band-sharpened multispectral image by merging it with the low-resolution LISS-3 MS image. Operationally anyone of the three LISS-4 bands can be chosen for the MO mode data acquisition. The performance of each band for producing band-sharpened MS images is evaluated, and the choice of the band based on the spatial and spectral characteristics of the merged data is suggested. The LISS-4 Red-band is found to be optimal. It provides band-sharpened imagery with spatial and spectral qualities very similar to the LISS-4 MX data products.
  • Keywords
    principal component analysis; remote sensing; AWIFS; IRS-P6 LISS-4 MO mode band; IRS-P6 satellite; LISS-3; PCA; band sharpening; band-sharpened multispectral imagery; monochromatic mode; multispectral data acquisition; multispectral mode; optical sensors; principal component analysis; Data acquisition; Image quality; Merging; Multispectral imaging; Optical sensors; Principal component analysis; Quality assessment; Remote sensing; Satellites; Spatial resolution; Band sharpening; multispectral imagery; principal component analysis (PCA); quality assessment;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2005.855618
  • Filename
    1576684