Classical algorithms used for traveltime tomography are not necessarily well suited for handling very large seismic data sets or for taking advantage of current supercomputers. The classical approach of first-arrival traveltime tomography was revisited with the proposal of a simple gradient-based approach that avoids ray tracing and estimation of the Fréchet derivative matrix. The key point becomes the derivation of the gradient of the misfit function obtained by the adjointstate technique. The adjoint-state method is very attractive from a numerical point of view because the associated cost is equivalent to the solution of the forward-modeling problem, whatever the size of the input data and the number of unknown velocity parameters. An application on a 2D synthetic data set demonstrated the ability of the algorithm to image near-surface velocities with strong vertical and lateral variations and revealed the potential of the method.
The next European Space Agency (ESA) Earth Explorer mission BIOMASS will acquire Synthetic Aperture Radar (SAR) data to help characterizing carbon fluxes in densely vegetated areas. The ESA-sponsored AfriSAR campaign was designed to collect data from African tropical forests in order to support the future BIOMASS mission. It was conducted in two parts over the tropical forests of Gabon, by ONERA in July 2015 and by DLR in Febuary 2016. This paper addresses the potential of tomographic SAR for retrieving vegetation parameters from the multibaseline P-band airborne data acquired by ONERA over the forest of La Lopé. It is shown that a correction of phase disturbances (phase screens) is necessary before tomographic analysis. Under the hypothesis of phase screens resulting only from inaccurancies in the platform motion, a correction procedure based on recent works from Tebaldini et al. is detailed and applied. The tomographic profiles after correction are shown to present good correspondances with the available LIDAR data.
The determination of the correct velocity structure of the near surface is a crucial step in seismic data processing and depth imaging. Generally, first-arrival traveltime tomography based on refraction data or diving waves is used to assess a velocity model of the subsurface that best explains the data. Such first-arrival traveltime tomography algorithms are very attractive for land data processing because early events in the seismic records are very often dominated by noise, and reflected events are very difficult or even impossible to identify. On the other hand, first arrivals can generally be identified quite clearly and are very often the only data available to reconstruct the near-surface velocity structure.
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