Abstract
The radiometric terrain correction (RTC) is an essential processing step for supervised classification applications of polarimetric synthetic aperture radar (PolSAR) over mountainous areas. However, the current angular variation effect (AVE) correction methods of three-step RTC processing are difficult to apply to PolSAR supervised classification because of the problem of interdependence between AVE correction and classification. To address this issue, based on the three-step semi-empirical RTC approach, we propose an improved AVE correction method suitable for the supervised classification of PolSAR. We make full use of the prior knowledge required for supervised classification and RTC processing, that is, samples and elevation data, to calculate the parameters of AVE correction by constructing a weight coefficient matrix. GaoFen-3 QPSI (C-band, quad-polarization) data were used to verify the proposed method. Experimental results showed that the proposed method is available and effective for PolSAR supervised classification. The new method can effectively remove the AVE effect in the PolSAR image, and the overall accuracy of PolSAR supervised classification can be improved about 9% compared to that without AVE correction. For the fine classification of forest types, the AVE correction can improve the classification accuracy by about 20%.
Highlights
Due to the characteristics of the side-looking of synthetic aperture radar (SAR) imaging system, SAR images present obvious topographical effects in mountainous areas, which is a great resistance to the application of SAR data
By making full use of the prior knowledge available in the supervised classification and radiometric terrain correction (RTC) process (i.e., digital elevation model (DEM) data), we developed an improved version of the three-step RTC approach for supervised classification of polarimetric SAR (PolSAR)
We proposed an improved three-step semi-empirical radiometric terrain correction approach
Summary
Due to the characteristics of the side-looking of synthetic aperture radar (SAR) imaging system, SAR images present obvious topographical effects in mountainous areas, which is a great resistance to the application of SAR data. Radiometric terrain correction (RTC) is an indispensable processing step in the application of SAR in mountainous areas [1]. For polarimetric SAR (PolSAR), the influence of terrain undulations mainly includes three aspects, namely the polarization orientation angle (POA), the effective scattering area (ESA), and the angular variation effect (AVE) [2,3,4,5]. Two or three steps of RTC are usually required to remove the influence of terrain in the PolSAR data [6,7,8]. The ESA correction corresponds to the influence of terrain on the scattering area of each pixel of the SAR image. On the front slope, one pixel corresponds to more ground area (i.e., ESA) than it would on the back slope
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.