L-Band UAVSAR Tomographic Imaging in Dense Forests: Gabon Forests

Abstract

Developing and enhancing strategies to characterize actual forests structure is a timely challenge, particularly for tropical forests. P-band synthetic aperture radar (SAR) tomography (TomoSAR) has previously been demonstrated as a powerful tool for characterizing the 3-D vertical structure of tropical forests, and its capability and potential to retrieve tropical forest structure has been discussed and assessed. On the other hand, the abilities of L-band TomoSAR are still in the early stages of development. Here, we aim to provide a better understanding of L-band TomoSAR capabilities for retrieving the 3-D structure of tropical forests and estimating the top height in dense forests. We carried out tomographic analysis using L-band UAVSAR data from the AfriSAR campaign conducted over Gabon Lopé Park in February 2016. First, it was found that L-band TomoSAR was able to penetrate into and through the canopy down to the ground, and thus the canopy and ground layers were detected correctly. The resulting TomoSAR vertical profiles were validated with a digital terrain model and canopy height model extracted from small-footprint Lidar (SFL) data. Second, there was a strong correlation between the L-band Capon beam forming profile in HH and HV polarizations with Land Vegetation Ice Sensor (LVIS) Level 1B waveform Lidar over different kinds of forest in Gabon Lopé National Park. Finally, forest top height from the L-band data was estimated and validated with SFL data, resulting in a root mean square error of 3 m and coefficient of determination of 0.92. The results demonstrate that L-band TomoSAR is capable of characterizing 3-D structure of tropical forests.

Monitoring Tropical Forest Structure Using SAR Tomography at L- and P-Band

“…Utilizing the Capon beamforming power estimator, we can recover the 3D backscatter profile from the multi-layer SLC and demonstrate the vertical backscatter distribution function. To do this, we applied the method proposed in [39] and we estimated the forest top height H from L-and P-band data:…”

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

“…Equation (3) can be actually regarded as a problem of spectral estimation. To date, a lot of spectral estimation approaches have been proposed to implement tomographic focusing, which can be categorized into three groups: (1) non-parametric spectral estimation [6,13,14];…”

“…Tomographic synthetic aperture radar (TomoSAR) [6][7][8][9], and especially the long-wavelength SAR systems, can penetrate the forest canopy to the ground and record the backscattering information from the forest vertical structure [10], which provides us with the possibility of underlying topographic mapping [11,12]. TomoSAR is an extension of the traditional two-dimensional (2D) imaging to three-dimensional (3D) imaging by collecting several images at different heights [13]. In other words, TomoSAR can be used to obtain the scattering echo along the elevation by the computed tomography for each resolution cell [14].…”

Potential of P-Band SAR Tomography in Forest Type Classification

“…TomoSAR exploits the key feature of microwaves to penetrate into vegetation, providing the possibility to see features that are hidden to optical and hyperspectral systems. In contrast to optical and hyperspectral imaging, TomoSAR measurements provide significantly higher sensitivity to the vertical arrangement of forest elements due to the ability to penetrate through the vegetation layer and interact with forest structure components at different heights [16,19,20]. Although LiDAR systems can measure precise vertical forest structure, TomoSAR has the advantage of a higher penetration ability through clouds/vegetation and wide-swath imaging capacities that can provide information at a large scale at high temporal and spatial resolutions [10][11][12].…”