Novel Harmonic-Based Scheme for Mapping Rice-Crop Intensity at a Large Scale Using Time-Series Sentinel-1 and ERA5-Land Datasets

Rice-crop intensity is the annual number of rice growth cycles in a field. Monitoring the intensity on a large scale is vital in evaluating grain production and its ecological impact. Synthetic aperture radar (SAR) has an all-weather imaging capability. However, the existing SAR-based rice-crop intensity mapping methods mostly focus on small regions due to the diversity of rice backscatter patterns, the inefficiency of the time-series feature extraction, and the unavailability of rice phenological information on a large scale. In this study, a harmonic-based method is proposed to identify the essential backscatter periodicities. It also suppresses short-term disturbance in time-series Sentinel-1 SAR data without setting filtering windows or assuming profile shapes. The method detects backscatter troughs, eliminating the requirement for point-by-point traversal mathematical operations. Annual temperature profiles are derived from time-series ERA5-Land data to identify troughs related to rice growth cycles under various agro-climatic conditions. Then, the single (135 537 km2), double (19 036 km2), and triple (259 km2) rice-crop intensities covering the entire Southern China in 2020 are mapped in a 10-m resolution, without relying on region-specific prior phenological information. The method achieves an overall accuracy of 82.26% and can potentially support the continental or global mapping task.