The spectral characteristics of different autumn crops are known from years of experience using remote sensing to monitor crop planting areas. A combined map of crop spatial distribution in Henan Province in 2019 was made using multi-source remote sensing and different classification methods, based on topographic and geomorphic characteristics and crop planting structures. The classification crops include corn, peanuts, rice and soybeans, and the multi-source images include Sentinel-2, Landsat 8-OLI, GF6 WFV with different spatial resolutions. The accuracy of the classification results was verified using ground samples and survey data.

The planting structure of autumn crops is complicated, including single crops of corn and rice, as well as mixed crops of corn, peanuts and soybeans. In the study area, corn was planted over the largest area, followed by peanuts. The overall accuracy and Kappa coefficient of the combined map were 86.13% and 0.83, respectively, which met the basic requirements for monitoring crops at provincial scale.

The paper addresses the optimization of remote sensing data sources, classification methods, ground surveys and precision verification approaches. In this study, the technical ability to monitor crops using remote sensing of planting structures was tested in a large-scale business application. It offers technical support for using remote sensing to produce a combined map at large scale.