The Application of Compact Polarization Decomposition in the Construction of a Dual-Polarization Radar Index and the Effect Evaluation of Rape Extraction

The rape planting plots are fragmented and have the same temporal variation characteristics as other land types, the rape planting area is cloudy and rainy, and the optical remote sensing images are limited, all make it difficult to extract the rape planting areas. Aiming at the above-mentioned problems, this study used microwave remote sensing data combined with the compact polarimetric technique to construct a dual-polarization radar index to classify rape planting areas and analyzed the influence of time series combinations on the extraction accuracy of rape in South China. First, based on
m-χ
compact polarimetric decomposition, a dual-polarization radar vegetation index (RVI) was constructed. Then, based on Sentinel-1 data, the dynamic time warping (DTW) threshold classification method was used to extract rape planting areas in six counties in the main rape-producing areas in the middle and lower reaches of the Yangtze River, China. Finally, a random forest algorithm was used to analyze and screen the optimal time series combination of the extracted regional rape planting areas. Among the 94 rape samples obtained in the field, 74 samples were accurately classified as rape, and the overall accuracy was 78.72%. Six ground samples were used to verify the accuracy of the rape planting area extraction results, and the F-1 score was 81.00%. The above-mentioned results indicated that the rape planting area extraction approach based on the RVI
_m-χ
and DTW threshold classification methods yields high accuracy in regional rape planting area extraction from dual-polarization SAR data, and RVI
_m-χ
is characterized by certain regional scalability and stability.