  Early warning systems for food security rely on timely and accurate
estimations of crop production. Several approaches have been developed to get
early estimations of area and yield, the two components of crop production. The
most common methods, based on Earth observation data, are image classification
for crop area and correlation with vegetation index for crop yield. Regardless
of the approach used, early estimators of cropland area, crop area or crop
yield should have an accuracy providing lower production error than existing
historical crop statistics. The objective of this study is to develop a
methodological framework to define the accuracy requirements for early
estimators of cropland area, crop area and crop yield in Senegal. These
requirements are made according to (i) the inter-annual variability and the
trend of historical data, (ii) the calendar of official statistics data
collection, and (iii) the time at which early estimations of cropland area,
crop area and crop yield can theoretically be available. This framework is
applied to the seven main crops in Senegal using 20 years of crop production
data. Results show that the inter-annual variability of crop yield is the main
factor limiting the accuracy of pre-harvest production forecast. Estimators of
cropland area can be used to improve production prediction of groundnuts,
millet and rice, the three main crops in Senegal stressing the value of
cropland mapping for food security. While applied to Senegal, this study could
easily be reproduced in any country where reliable agricultural statistics are
available.
