• DocumentCode
    144232
  • Title

    Calculating vegetation index based on the universal pattern decomposition method (VIUPD) using Landsat 8

  • Author

    Xiaojun She ; Lifu Zhang ; Ali Baig, Muhammad Hasan ; Yao Li

  • Author_Institution
    Inst. of Remote Sensing & Digital Earth, Beijing, China
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    4734
  • Lastpage
    4737
  • Abstract
    This study introduced the vegetation index based on the universal pattern decomposition method (VIUPD) and then applied on a new sensor - Landsat 8 Operational Land Imager (OLI). VIUPD is a valuable sensor-independent spectral analysis method. Each pixel is described as the linear mixture of standard spectral patterns for water, vegetation, soil and supplementary patterns included when necessary. In the present paper, processing procedure about the data acquisition, radiometric calibration and atmospheric correction have been elaborated. The normalized reflectance (P) of four standard samples resampled to OLI has been listed. For validation of the results, Normalized Difference Vegetation Index (NDVI) and VIUPD have been calculated for comparison. The results showed that VIUPD is more sensitive to the vegetation amount change even in the high vegetation coverage, while the NDVI is more rapidly saturated in high vegetation cover area. In addition, VIUPD is more sensitive to the soil background than NDVI.
  • Keywords
    remote sensing; vegetation; LANDSAT 8 Operational Land Imager; VIUPD; atmospheric correction; data acquisition; normalized difference vegetation index; radiometric calibration; sensor-independent spectral analysis method; soil background; standard spectral patterns; universal pattern decomposition method; vegetation cover area; vegetation index; Earth; Indexes; Reflectivity; Remote sensing; Satellites; Standards; Vegetation mapping; Landsat; Operational Land Imager; UPDM; VIUPD; sensor independent;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6947551
  • Filename
    6947551