*3.2. Methods*

Firstly, a map of common spectral indices in RCF modeling was prepared based on the Landsat 8 and Sentinel 1 VV and VH spectral bands. Then, these maps were masked to areas with NDVI < 0.3 to limit analysis to areas without significant green vegetative ground cover [16] and was also masked to agricultural crop fields using the AAFC map. Then, the efficiency of each of these indicators in modeling the RCF was evaluated for each agricultural product. Secondly, the efficiency of different algorithms, including RFR, SVM, ANN and PLSR in modeling RCF, was evaluated and they were compared with each other. Furthermore, different algorithms' results were combined based on the modeling error in order to increase the accuracy of receipt modeling. This strategy used the fusion capability at the decision level to improve the accuracy of RCF modeling.
