Evaluation of P-Band SAR Tomography for Mapping Tropical Forest Vertical Backscatter and Tree Height

Abstract

Low-frequency tomographic synthetic aperture radar (TomoSAR) techniques provide an opportunity for quantifying the dynamics of dense tropical forest vertical structures. Here, we compare the performance of different TomoSAR processing, Back-projection (BP), Capon beamforming (CB), and MUltiple SIgnal Classification (MUSIC), and compensation techniques for estimating forest height (FH) and forest vertical profile from the backscattered echoes. The study also examines how polarimetric measurements in linear, compact, hybrid, and dual circular modes influence parameter estimation. The tomographic analysis was carried out using P-band data acquired over the Paracou study site in French Guiana, and the quantitative evaluation was performed using LiDAR-based canopy height measurements taken during the 2009 TropiSAR campaign. Our results show that the relative root mean squared error (RMSE) of height was less than 10%, with negligible systematic errors across the range, with Capon and MUSIC performing better for height estimates. Radiometric compensation, such as slope correction, does not improve tree height estimation. Further, we compare and analyze the impact of the compensation approach on forest vertical profiles and tomographic metrics and the integrated backscattered power. It is observed that radiometric compensation increases the backscatter values of the vertical profile with a slight shift in local maxima of the canopy layer for both the Capon and the MUSIC estimators. Our results suggest that applying the proper processing and compensation techniques on P-band TomoSAR observations from space will allow the monitoring of forest vertical structure and biomass dynamics.

Improving Forest Canopy Height Estimation Using a Semi-Empirical Approach to Overcome TomoSAR Phase Errors

“…Multibaseline TomoSAR provides multiple observations of the same object acquired during multiple flights by airborne or satellite platforms. Multiple antennas of different heights form a synthetic aperture in the normal direction, thus providing elevation information [16,23,[29][30][31] (Figure 2).…”

“…Multibaseline TomoSAR provides multiple observations of the same object acquired during multiple flights by airborne or satellite platforms. Multiple antennas of different heights form a synthetic aperture in the normal direction, thus providing elevation information [16,23,[29][30][31] (Figure 2). If the radar wavelength is sufficiently long to penetrate the canopy layer [32], multiple SAR acquisitions in the same area with slightly different views allow the forest reflectance to be quantified in three dimensions.…”

“…The Capon spectral estimator is a conventional nonparametric method in TomoSAR analysis that can be used to obtain an infinite vertical profile of the vegetation without any a priori knowledge of the data's statistical properties [16,21,30,33,34]. The method is an improved algorithm version of the conventional beamforming method based on the minimum variance criterion, which filters the signal of each array element through the optimal weighting vector to suppress noise interference and enhance the signal.…”

High-Resolution L-Band TomoSAR Imaging on Forest Canopies with UAV Swarm to Detect Dielectric Constant Anomaly

“…The morphology of a forest, including canopy height, vertical structure and spatial distribution, provides useful information for ecological protection [1], biomass estimation [2], the monitoring of biodiversity [1] and the global carbon cycle [3]. More incidences of forest fires in recent years may be correlated to the trend of global warming [4].…”

Underlying Topography Inversion Using TomoSAR Based on Non-Local Means for an L-Band Airborne Dataset

“…Accordingly, the tomographic 3D imaging of forests is processed using the CM [19,20]. For example, the frequently used tomographic methods such as beamforming [6], adaptive beamforming (Capon) [8], and the multiple signal classification (MUSIC) [9] algorithm all obtain tomograms on the basis of CMs [21,22]. Therefore, the estimation accuracy of the CM directly determines the performance of tomographic focusing.…”