Crop Field Edge Detection based on Time-Varying Polarimetric Characteristics with Time-Series Sentinel-1 SAR Data

Crop field edge is the key characteristic of agricultural crop management. Edge detection with dual-polarization SAR time series have been widely studied, with the data advantages of sensitivity to crop growth. Existing methods rarely consider time-varying dynamic polarimetric characteristics, making it difficult to detect complete crop field edges. Based on this, this proposes a joint edge strength, which combines two kinds of polarimetric distances with a novel spatial-temporal homogeneity measure. This measure applies spatial- and temporal-varying contexts to pre-identify edge and homogenous area, and adaptatively allocate various distances in one pixel. There are 14 Sentinel-1 SAR time series images are utilized to evaluate the proposed method. By the comparison of the visual differences, our method has lower missing rate and lower false alarm rate than conventional methods.