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
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