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Evaluating NDVI Data Continuity Between SPOT-VEGETATION and PROBA-V Missions for Operational Yield Forecasting in North African Countries
Author(s) -
Michele Meroni,
Dominique Fasbender,
Riad Balaghi,
Mustapha Dali,
Myriam Haffani,
Ismael Haythem,
Josh Hooker,
Mouanis Lahlou,
Raul Lopez-Lozano,
Hamid Mahyou,
Moncef Ben Moussa,
Nabil Sghaier,
Talhaoui Wafa,
Olivier Leo
Publication year - 2015
Publication title -
ieee transactions on geoscience and remote sensing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.141
H-Index - 254
eISSN - 1558-0644
pISSN - 0196-2892
DOI - 10.1109/tgrs.2015.2466438
Subject(s) - geoscience , signal processing and analysis
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.

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