Multitemporal polarimetric SAR crop classification method based on tensor representation

XU Lu; ZHANG Hong; WANG Chao; WU Fan; ZHANG Bo; TANG Yixian

doi:10.7523/j.ucas.2024.003

Journal of University of Chinese Academy of Sciences >

2025 , Vol. 42 >Issue 5: 686 - 699

DOI: https://doi.org/10.7523/j.ucas.2024.003

Research Articles

Multitemporal polarimetric SAR crop classification method based on tensor representation

XU Lu ,
ZHANG Hong ,
WANG Chao ,
WU Fan ,
ZHANG Bo ,
TANG Yixian

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1. CAS Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
2. The International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2023-11-07

Revised date: 2024-01-17

Online published: 2024-01-25

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Abstract

Multitemporal polarimetric synthetic aperture radar (SAR) provides abundant polarimetric scattering information, which is of great value to the long-term monitoring of various crop lands. To make full use of the time correlation and polarimetric information of multitemporal polarimetric SAR, this paper proposed a multitemporal polarimetric SAR crop classification method, which is based on the complete polarimetric covariance matrix. The method can maintain the complex matrix structure of covariance matrix and realize the independent representation of time dimension in tensor space, so that it can be applied to both full- and compact-polarimetric SAR. The method adopted the object-level classification strategy. Firstly, the superpixel segmentation of multitemporal SAR data was achieved by the simple linear iterative clustering (SLIC) method. Then, the covariance matrices of multitemporal SAR were expressed as tensors, and the multilinear principal component analysis (MPCA) method was used to reduce the feature dimension. Finally, the crop classification is achieved by decision tree. In this research, four multitemporal RADARSAT-2 Fine Quad SAR images covered Wuqing District，Tianjin, were used for the crop classification experiments. Compared with methods proposed in other references, the method proposed in this paper achieved the highest overall classification accuracy. Besides, the proposed method was applied to the π/4 mode and the CTLR mode compact-polarimetric SAR to discuss the capability of different kinds of polarimetric SAR in crop classification. Compared with the full-polarimetric SAR, the compact-polarimetric SAR could achieve comparable classification accuracies, but the full-polarimetric SAR performed better at the classes with small sample size, such as rice and lotus.

Key words： synthetic aperture radar (SAR); full polarimetric (FP); compact polarimetric (CP); crop classification; tensor; multilinear principal component analysis (MPCA)

Cite this article

XU Lu , ZHANG Hong , WANG Chao , WU Fan , ZHANG Bo , TANG Yixian . Multitemporal polarimetric SAR crop classification method based on tensor representation[J]. Journal of University of Chinese Academy of Sciences, 2025 , 42(5) : 686 -699 . DOI: 10.7523/j.ucas.2024.003

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