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Evaluating NDVI Data Continuity Between SPOT-VEGETATION and PROBA-V Missions for Operational Yield Forecasting in North African Countries.

Authors :
Meroni, Michele
Fasbender, Dominique
Balaghi, Riad
Dali, Mustapha
Haffani, Myriam
Haythem, Ismael
Hooker, Josh
Lahlou, Mouanis
Lopez-Lozano, Raul
Mahyou, Hamid
Ben Moussa, Moncef
Sghaier, Nabil
Wafa, Talhaoui
Leo, Olivier
Source :
IEEE Transactions on Geoscience & Remote Sensing; Feb2016, Vol. 54 Issue 2, p795-804, 10p
Publication Year :
2016

Abstract

After 15 years, the Système Pour l'Observation de la Terre (SPOT)-VEGETATION (VGT) program reached the end of its life in May 2014 and was replaced by the Project for On-Board Autonomy-Vegetation (PROBA-V) mission. Exploiting the period of overlap between instruments, this study compares the normalized difference vegetation index (NDVI) of two instruments from the point of view of the user interested in operational crop monitoring. The comparison is performed for Morocco, Algeria, and Tunisia, where NDVI is used to derive anomaly maps, temporal profiles, and cereal yield forecasts. A relevant scatter due to unexplained unsystematic variability exists between anomaly values. A mismatch between anomaly classes is observed for 20%–30% of the crop area. However, when the NDVI is averaged over cropland and administrative units to derive temporal profiles, the two data sources show a high agreement. Results for yield estimation comparison indicate an overall high agreement, and both the (null) hypotheses that the model predictions and the root mean square error (RMSE) in yield estimation are not different, when using PROBA-V instead of SPOT-VGT, cannot be rejected in all cases for Morocco and Algeria. On the contrary, in Tunisia, where RMSE is lower using PROBA-V, the hypothesis of no difference in RMSE is rejected. These findings therefore indicate that yield estimation performances are not affected (Morocco and Algeria) or improved (Tunisia) by the source transition. Finally, despite the same nominal spatial resolution, the different spatial quality of the sensors was found to have an effect on yield estimation in areas characterized by sharp transitions between cropland and desert. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01962892
Volume :
54
Issue :
2
Database :
Complementary Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
112538314
Full Text :
https://doi.org/10.1109/TGRS.2015.2466438