Abstract
In this paper, we consider a new method for forest canopy height estimation using TanDEM-X single-pass radar interferometry. We exploit available information from sample-based, space-borne LiDAR systems, such as the Global Ecosystem Dynamics Investigation (GEDI) sensor, which offers high-resolution vertical profiling of forest canopies. To respond to this, we have developed a new extended Fourier-Legendre series approach for fusing high-resolution (but sparsely spatially sampled) GEDI LiDAR waveforms with TanDEM-X radar interferometric data to improve wide-area and wall-to-wall estimation of forest canopy height. Our key methodological development is a fusion of the standard uniform assumption for the vertical structure function (the SINC function) with LiDAR vertical profiles using a Fourier-Legendre approach, which produces a convergent series of approximations of the LiDAR profiles matched to the interferometric baseline. Our results showed that in our test site, the Petawawa Research Forest, the SINC function is more accurate in areas with shorter canopy heights (<~27 m). In taller forests, the SINC approach underestimates forest canopy height, whereas the Legendre approach avails upon simulated GEDI forest structural vertical profiles to overcome SINC underestimation issues. Overall, the SINC + Legendre approach improved canopy height estimates (RMSE = 1.29 m) compared to the SINC approach (RMSE = 4.1 m).
Highlights
Whether using LiDAR or radar tomography, is the question of how much vertical profile resolution is required for good height estimation from TanDEMX? In this paper, we address this issue by proposing a novel Legendre series approach [9,10,11]
85%the of forest stands in the Petawawa Research Forest (PRF) are clasto-wall map ofbecause canopymore height from
We developed and assessed a novel combined SINC + Legendre approach for fusing high-resolution but sparsely spatially sampled Global Ecosystem Dynamics Investigation (GEDI) LiDAR waveforms with singleand passassessed radar interferometry to improve radar forest
Summary
There is currently great interest in the capacity to improve wide-area forest canopy height estimates derived from TanDEM-X single-pass radar interferometry by focusing on forest height inversion modeling and by integrating data from the Global. Ecosystem Dynamics Investigation (GEDI) full waveform LiDAR or radar tomography to estimate vertical forest profile functions [1,2,3,4,5]. Standard profile estimation functions, such as assuming a uniform vertical profile (the SINC approximation [6,7]) or exponential (as in the Random-Volume-Over-Ground (RVOG) model [8]) are often assumed to be inaccurate for complex forest environments with heterogeneous vertical structures. Whereas LiDAR provides the greatest vertical resolution, it has important differences from the radar in terms of viewing geometry [4], leading in particular to the strong influence of ground returns in open and lower biomass forests, while direct radar tomography has limitations in vertical resolution [5], but better mimics the sensing geometry of radar interferometers and so potentially provides a better balanced profile at the wavelength of the interferometer
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