• DocumentCode
    3086156
  • Title

    Using NASA´S Long Term Data Record version 3 for the monitoring of land surface vegetation

  • Author

    Sobrino, Jose A. ; Julien, Yves ; Mattar, Cristian ; Oltra-Carrio, Rosa ; Jimenez-Munoz, Juan C. ; Soria, Gustavo ; Franch, Belen ; Hidalgo, V.

  • Author_Institution
    Imaging & Process. Lab., Univ. of Valencia, Valencia, Spain
  • fYear
    2011
  • fDate
    12-14 July 2011
  • Firstpage
    253
  • Lastpage
    256
  • Abstract
    Numerous datasets have been made available for the observation of our planet from space. The aim of this work is the observation of changes in vegetation, through the use of a recent remote sensing dataset, NASA´s Long Term Data Record (LTDR). Several authors have pointed out that vegetation monitoring benefits of the simultaneous use of Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST). Therefore, this work presents the procedure developed to monitor vegetation with the LTDR dataset, using both NDVI and LST parameters. This procedure includes data preprocessing (estimation of NDVI and LST, orbital drift correction, atmospherically contaminated data reconstruction), and analysis (Mann-Kendall statistical framework).
  • Keywords
    data analysis; land surface temperature; vegetation mapping; Mann-Kendall statistical framework; NASA long term data record; NOAA-AVHRR; atmospherically contaminated data reconstruction; data analysis; data preprocessing method; land surface temperature; land surface vegetation monitoring; normalized difference vegetation index; remote sensing dataset; vegetation change observation; Clouds; Land surface; Land surface temperature; Monitoring; Remote sensing; Time series analysis; Vegetation mapping; LTDR; Land Surface Temperature; NDVI; NOAA-AVHRR; time series; vegetation monitoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Analysis of Multi-temporal Remote Sensing Images (Multi-Temp), 2011 6th International Workshop on the
  • Conference_Location
    Trento
  • Print_ISBN
    978-1-4577-1202-9
  • Type

    conf

  • DOI
    10.1109/Multi-Temp.2011.6005096
  • Filename
    6005096