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Evaluation of Agreement Between Space Remote Sensing SPOT-VEGETATION fAPAR Time Series.

Authors :
Meroni, Michele
Atzberger, Clement
Vancutsem, Christelle
Gobron, Nadine
Baret, Frédéric
Lacaze, Roselyne
Eerens, Herman
Leo, Olivier
Source :
IEEE Transactions on Geoscience & Remote Sensing. Apr2013 Part 1, Vol. 51 Issue 4, p1951-1962. 12p.
Publication Year :
2013

Abstract

Satellite-derived time series of the fraction of absorbed photosynthetically active radiation (fAPAR) are widely used to monitor vegetation dynamics and to detect vegetation anomalies. Several global data sets are available for this purpose. They are produced using different algorithms and/or satellite sensors. This paper compares and analyzes three multitemporal fAPAR data sets derived from SPOT-VEGETATION instrument by explicitly distinguishing between spatial and temporal agreement. The first two data sets are currently used by the Joint Research Centre—Monitoring Agricultural ResourceS Unit (JRC-MARS) for operational yield forecasting and food security assessments. The third time series (named GEOV1) is from a new processing algorithm developed within the European FP7 Geoland2 project. The comparative analysis was conducted for the years 2003 and 2004 over three 10^\circ \times 10^\circ regions with different eco-climatic characteristics (Niger, Brazil, and France). Our study revealed that GEOV1 fAPAR estimates were systematically higher than those of JRC-MARS. The spatial analysis showed moderate to high agreement between data sets with specific seasonality in the three study regions. The temporal agreement showed spatial (and land cover-related) variability spanning from very low to almost perfect. Large differences were observed in regions and periods with large cloud occurrence where GEOV1 provides more reliable and smooth temporal profiles due to improved cloud screening and longer compositing periods. Other sources of disagreement between data sets were identified in differences in the fAPAR retrieval algorithm definitions. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01962892
Volume :
51
Issue :
4
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
95451802
Full Text :
https://doi.org/10.1109/TGRS.2012.2212447