Parcel-based summer maize mapping and phenology estimation combined using Sentinel-2 and time series Sentinel-1 data

Abstract

This study aims to map the planting area of summer maize and estimate the spatiotemporal phenology information with parcel-based classification method through integration of Sentinel-1/2 data in Jiaozuo located in North China Plain. For the maize mapping, the combination of Sentinel-1/2 data with the parcel-based method has the highest classification accuracy, suggesting that the integration of Sentinel-1/2 data with parcel-based method has great potential for regional maize mapping. For the estimation of maize phenology, the dynamic threshold method is used to extract the tasseling and milk ripening date through the time series σ0VH. In order to reduce the influence of precipitation or irrigation on SAR data, a Local Minimum Value Composite (LMVC) method is proposed to filter the original time series SAR data. The systematic phenology estimation method mainly includes LMVC, S-G filtering, Fourier curve fitting and dynamic threshold points extracting. Compared with the actual phenology date by field investigation, the errors of estimated tasseling and milk ripening date are 4.3 days and 5.5 days respectively, indicating that the time series σ0VH derived from the SAR data has great potential in spatiotemporal phenology estimation of field maize. Finally, the scattering mechanism of the maize field to C-band microwave in different growth periods was analyzed. It was also found that the phenology of maize was delayed in the coal mining subsidence areas and the areas with insufficient field management.