Analysis of the Capacity of Radar Time Series Data for Crop Mapping in the Context of the Sahel: Case of Groundnut, Millet and Maize in Senegal

Abstract

Monitoring agricultural areas, using remote sensing, has been a major issue in the Sahel region, due to the small size of farm plot compared to satellite spatial resolution. The main goal is to develop a methodology based on radar data for mapping crops in Senegal. Training plots were used to analyse temporal dynamics of radar signals. The result shows that the possibility to separate agricultural area from other land cover at the beginning of the rainy season. The radar signal of the three crops are confused at the beginning but we note a strong difference at the end of the growing season, where peanut crops signal is marked by a sharp fall. Variance analysis allowed to select images which are able to discriminate these cultures. The Classification And Regression Trees (CART) model used is able to identify peanut plots with more than 82% of accuracy, but confuse maize crop (accuracy less than 70%). This result means the resulting inability to separate the two types of maize crops (one which is sown early and harvested in mid-season, another sown in mid-season and harvested at the end of the season). So, in this area, the use of radar permit to improve crop mapping considering agricultural practice of cereals.