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

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.

[1]  S. Nilsson,et al.  Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000 , 2010 .

[2]  L. Ji,et al.  An Agreement Coefficient for Image Comparison , 2006 .

[3]  W. Dierckx,et al.  PROBA-V mission for global vegetation monitoring: standard products and image quality , 2014 .

[4]  Stefan Adriaensen,et al.  The PROBA-V mission: image processing and calibration , 2014 .

[5]  Jin Chen,et al.  A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter , 2004 .

[6]  R. Wilcox Comparing the variances of two independent groups. , 2002, The British journal of mathematical and statistical psychology.

[7]  B. Holben Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[8]  Steffen Fritz,et al.  Harmonizing and Combining Existing Land Cover/Land Use Datasets for Cropland Area Monitoring at the African Continental Scale , 2012, Remote. Sens..

[9]  Clement Atzberger,et al.  Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs , 2013, Remote. Sens..

[10]  Herman Eerens,et al.  Image time series processing for agriculture monitoring , 2014, Environ. Model. Softw..

[11]  Clement Atzberger,et al.  Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection , 2013, Remote. Sens..

[12]  Wouter Dierckx,et al.  Proba-V Belgian Mission Satellite Global Products for Vegetation Monitoring , 2013 .

[13]  John L. Dwyer,et al.  Agreement evaluation of AVHRR and MODIS 16‐day composite NDVI data sets , 2008 .

[14]  Michele Meroni,et al.  Remote Sensing Based Yield Estimation in a Stochastic Framework - Case Study of Durum Wheat in Tunisia , 2013, Remote. Sens..

[15]  J. A. Schell,et al.  Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor] , 1973 .

[16]  C. Vignolles,et al.  A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study on Spain , 2001 .

[17]  Michele Meroni,et al.  Evaluation of Agreement Between Space Remote Sensing SPOT-VEGETATION fAPAR Time Series , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Bicheron Patrice,et al.  GlobCover - Products Description and Validation Report , 2008 .