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|Title:||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 Raid; DALI Mustapha; HAFANI Miriam; HAYTHEM Ismael; HOOKER JOSEPH DOMINIC; LAHLOU Mouanis; LOPEZ LOZANO RAUL; MAHYOU Hamid; MONCEF Ben Moussa; SGHAIER Nabil; WAFA Talhaoui; LEO Olivier|
|Citation:||IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING vol. 54 no. 2 p. 795-804|
|Publisher:||IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC|
|Type:||Articles in periodicals and books|
|Abstract:||After 15 years, the SPOT-VEGETATION (VGT) programme reached the end of its life in May 2014 and was replaced by the 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 to 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.|
|JRC Directorate:||Sustainable Resources|
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