This study explored the suitability of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectrometer (MODIS) obtained for six sugar management zones, over nine years (2002-2010), to forecast sugarcane yield on an annual and zonal base. To take into account the characteristics of the sugarcane crop management (15-month cycle for a ratoon, accompanied with continuous harvest in Western Kenya), the temporal series of NDVI was normalized through an original weighting method that considered the growth period of the sugarcane crop (wNDVI), and correlated it with historical yield datasets. Results when using wNDVI were consistent with historical yield and significant at P-value = 0.001, while results when using traditional annual NDVI integrated over the calendar year were not significant. This correlation between yield and wNDVI is mainly drawn by the spatial dimension of the data set (R 2 = 0.53, when all years are aggregated together), rather than by the temporal dimension of the data set (R 2 = 0.1, when all zones are aggregated). A test on 2012 yield estimation with this model realized a RMSE less than 5 t· ha −1 . Despite progress in the methodology through the weighted
['Betty Mulianga', 'Agnès Bégué', 'Margareth Simoes', 'Pierre Todoroff']
Forecasting Regional Sugarcane Yield Based on Time Integral and Spatial Aggregation of MODIS NDVI