Forest Height Estimation Approach Combining P-Band and X-Band Interferometric SAR Data

Abstract

Forest height is an essential parameter used to derive important information about forest ecosystems, such as forest above-ground biomass. In this article, a forest height estimation approach combining P-band and X-band interferometric synthetic aperture radar (InSAR) was introduced. The forest height was estimated using the difference in the penetration of long- and short-wavelength radars to the forest. That is, the P-band and X-band InSAR data were used to extract the digital terrain model (DTM) and digital surface model (DSM), respectively. For the DTM, an improved time-frequency (TF) analysis method was used to reduce the effect of forest scatterers on the extraction of a pure understory terrain phase based on P-band InSAR. For the DSM, a novel compensation algorithm based on a multi-layer model (MLM) was proposed to remove the penetration bias of the X-band. Compared to the existing method based on the infinitely deep uniform volumes (IDUV) model, the MLM-based method is more in line with the characteristics of forest structure and the scattering mechanism for X-band InSAR. The airborne P-band repeat-pass InSAR and spaceborne X-band (TanDEM-X) single-pass InSAR data were used to verify the proposed method over the study area in the Saihanba Forest Farm in Hebei, China. The results demonstrated that the improved TF method can achieve high-precision DTM extraction based on P-band InSAR data, and the root mean square error (RMSE) was 0.94 m. The proposed MLM-based compensation method of the DSM achieved a smaller error (RMSE: 1.67 m) compared to the IDUV-based method (RMSE: 3.01 m). Under the same DTM extracted by P-band InSAR, the estimation accuracy of forest height based on the MLM method was 86.58% (RMSE: 1.81 m), which was 8.49% higher than that of the IDUV-based method (RMSE: 2.98 m).