Abstract
Our study aims to provide a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR to assess the ability for TomoSAR to monitor and estimate the tropical forest structure parameters for enhanced forest management and to support biomass missions. The comparison relies on the unique UAVSAR Jet propulsion Laboratory (JPL)/NASA L-band data, P-band data acquired by ONERA airborne system (SETHI), Small Footprint LiDAR (SFL), and NASA Land, Vegetation and Ice Sensor (LVIS) LiDAR datasets acquired in 2015 and 2016 in the frame of the AfriSAR campaign. Prior to multi-baseline data processing, a phase residual correction methodology based on phase calibration via phase center double localization has been implemented to improve the phase measurements and compensate for the phase perturbations, and disturbances originated from uncertainties in allocating flight trajectories. First, the vertical structure was estimated from L- and P-band corrected Tomography SAR data measurements, then compared with the canopy height model from SFL data. After that, the SAR and LiDAR three-dimensional (3D) datasets are compared and discussed at a qualitative basis at the region of interest. The L- and P-band’s performance for canopy penetration was assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration were compared with their ability to derive forest vertical structure. Finally, the vertical structure extracted from the 3D radar reflectivity from L- and P-band are compared with SFL data, resulting in a root mean square error of 3.02 m and 3.68 m, where the coefficient of determination shows a value of 0.95 and 0.93 for P- and L-band, respectively. The results demonstrate that TomoSAR holds promise for a scientific basis in forest management activities.
Highlights
Tropical Forests play a vital role in the global carbon cycle, and subsequently within the global climate [1]
The limitation of L-band Tomography Synthetic Aperture Radar (TomoSAR) imaging in dense forests using TropiSAR data acquired over Paracou is illustrated; we report the results of forest structure characterization over Gabon Lopé National Park by means of tomography imaging using AfriSAR L- and P-band TomoSAR Single Look Complex (SLC) data
A phase residual correction methodology based on phase calibration via phase center double localization was implemented
Summary
Tropical Forests play a vital role in the global carbon cycle, and subsequently within the global climate [1]. There’s a crucial demand to develop a new technology to help in surveying and revealing the dynamics of tropical forests. Forest structure information is essential for developing a precise forest biomass estimators. The latter is needed to observe better and evaluate forest ecosystems’ contribution in the overall carbon cycle [3,4,5]. Forest structure observation has been implemented by inventory plots at local scales. Inventory measurements provide correct estimates of a variety of single trees and stand parameters. These measurements are time demanding and they are performed at smaller scales. Remote sensing techniques have the potential to overcome this limitation and make an enormous contribution in qualitative and quantitative observation of three-dimensional forest structure [7,8,9,10]
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