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.
Highlights
Tropical forests have major impacts on Earth’s ecosystem in terms of carbon storage, regulating water, and weather
tomographic SAR (TomoSAR) analysis was applied for estimation of the forest canopy height and terrain using L-band UAVSAR AfriSAR data collected over Gabon Lopé Park in February 2016
The tomographic Capon profiles at different sections of the forests were validated in a good correlation with small-footprint Lidar (SFL) Lidar data digital terrain model (DTM) and canopy height model (CHM) from the SFL data-set as a reference
Summary
Tropical forests have major impacts on Earth’s ecosystem in terms of carbon storage, regulating water, and weather. Above-ground biomass (AGB) is the most important parameter related directly to the amount of carbon in the global ecosystem cycle [1]. Uncertainty in balancing the global carbon budget arises from a deficiency in AGB density estimation and carbon stocks in tropical forests. NASA, ESA, AGEOS, and DLR have developed united efforts in the implementation of the AfriSAR campaign in the Gabon forests [2]. In this context, the objective of the AfriSAR campaign was to acquire airborne and field data for the development, calibration, and validation of algorithms for the estimation of the vertical structure of tropical forests and the biomass within them. The airborne data provided by the campaign consist of polarimetric synthetic aperture radar (SAR) interferometry (Pol-InSAR), tomographic SAR (TomoSAR) datasets, Lidar full waveforms, and small-footprint Lidar (SFL)
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