Multicriteria Accuracy Assessment of Digital Elevation Models (DEMs) Produced by Airborne P-Band Polarimetric SAR Tomography in Tropical Rainforests

Abstract

The penetration capability of P-band radar waves through dense vegetation, along with the ability of tomography to separate the contributions of different layers in a vertical reflectivity profile, make P-band radar tomography a promising tool for digital terrain modeling in forested areas, specifically in dense tropical forests under which terrain topography remains poorly known. This paper aims to assess the overall quality of a digital terrain model (DTM) produced using tomographic processing of airborne P-band SAR imagery acquired during the TropiSAR campaign in French Guiana. Many quality descriptors are used to evaluate the quality of this DTM. Position and slope accuracies are computed based on a lidar DTM considered as the reference, and the impact of several parameters on these accuracies is studied, namely, slope, slope orientation, off-nadir angle and local incidence angle. The realism of the landforms is also studied according to geomorphological criteria. The results of this multicriteria accuracy assessment show the high potential of P-band SAR tomography in depicting the topography under forests, despite the intrinsic limitations related to the slant range geometry: the absolute elevation error is around 2 m; the slope is overestimated with an error of about 16°, mainly due to a processing artifact for which easy and direct solutions exist. Indeed, this error is equal to about 3° in flat artifact-free areas. These errors vary depending on the acquisition parameters and the local topography. The shapes are globally well preserved. These results are also discussed in the frame of the upcoming BIOMASS mission developed by the European Space Agency (ESA) and expected to be launched in 2024.

Multicriteria Evaluation of the Potential of P-Band Airborne Radar Dems for 3d Characterisation of Hydrography in Tropical Forests

“…However, this error is not homogeneous, and results obtained in area A show that it is a function of the local slope, the surface orientation with regards to the radar viewing direction, and the incidence angle. Indeed, both elevation and slope RMS errors increase as the local slope increases, they are more important on slopes facing away from the radar, and they increase when the incidence angle decreases (El Hage et al, 2022).…”

Global Digital Elevation Model Comparison Criteria: An Evident Need to Consider Their Application

“…On the other hand, it is well known that elevation error and the artifacts present in the GDEMs greatly influence the elevation derivatives (slope, orientation, curvature, etc.) (e.g., [40,66]) in such a way that it is possible to have high elevation accuracy and low shape quality and vice versa [82]. Despite all this, only [40] analyzed pixel-wise error of elevation, slope, and aspect.…”

“…The common situation is the evaluation of the accuracy of DEMs from a single perspective, internal or external accuracy, but not jointly ( [66]). Assessment of external accuracy is the most usual option, although, as El Hage indicates, this perspective is not always the most appropriate.…”

“…Ref. [66] proposes evaluating the quality in a complete way, but they do not establish a quality model only independent measures.…”

A Review of Forest Height Inversion by PolInSAR: Theory, Advances, and Perspectives

“…Representative methods under the multi-baseline condition include the polarimetricsensitive array method and the sum of Kronecker product (SKP) decomposition method. The polarimetric-sensitive array method combines multi-baseline data into an array signal and estimates the wave direction using a polarimetric-sensitive Direction of Arrival (DOA) estimation method [46,47]. The SKP decomposition method is a multi-baseline extension of the scattering decomposition method, which separates the ground phase and canopy phase using matrix rearrangement and singular value decomposition (SVD), obtaining the tree height inversion value [48,49].…”