Crop distribution extraction based on Sentinel data

Remote sensing identification and classification of crops is the use remote for estimating crop planting area timely accurate monitoring growth plant diseases insect pests in advance to make product output estimate key premise study using Sentinel-1 Sentinel-2 satellite, by random forest algorithm, traditional optical wavelengths vegetation index The backward scattering field red edge information radar feature selection classification, including winter wheat summer corn orchard woodland town water bare land set three controls, such as first group contains time characteristics, characteristics second control long, third includes phase analyzed different accuracy. results from confusion matrix show that band after join accuracy improved effectively. Sentinel satellites with a resolution 5–6 days have great potential research.