Land cover classification and height extraction experiments using Chinese airborne X-band PolInSAR system in China

Abstract

In this paper, we describe our land cover classification and height extraction experiments with high-resolution X-band polarimetric interferometric synthetic aperture radar (PolInSAR) data acquired by Chinese airborne PolInSAR system over Linshui in southern China. The experimental area contains plenty of natural and artificial objects. We present two polarimetric synthetic aperture radar (PolSAR) classification schemes for different land cover types. An Oriented-Object classification scheme based on hierarchical segmentation is employed to the regular land cover classification experiment. The Entropy-PSD unsupervised classification method based on pixel is employed to the low backscattering targets classification experiment. Fully taking advantage of the characteristics of the multi-baseline data set, a dual-baseline polarimetric interferometry method is applied to the PolInSAR experiment of height extraction. Our PolSAR and PolInSAR experiment results demonstrate that high-resolution X-band PolInSAR imagery acquired by Chinese airborne SAR system have great application potential for land classification and height extraction.

Integration of Sentinel-1 and Sentinel-2 Data for Land Cover Mapping Using W-Net

“…In order to overcome this drawback, recent works [13][14][15][16] proposed the use of Synthetic Aperture Radar (SAR) imaging sensors, able to acquire even in presence of clouds. In literature, the polarimetric SAR (PolSAR) [17,18], the polarimetric SAR interferometry (PolInSAR) [19], and the Multi-chromatic analysis PolInSAR (MCA-PolInSAR) [20] methods have been used to extrapolate information about the physical proprieties of targets. Furthermore, the bottleneck of using single sensor is an inherent trade-off between spatial and temporal resolution.…”