UAVSAR Tomography for Vertical Profile Generation of Tropical Forest of Mondah National Park, Gabon

• Main Authors: Udit Asopa, Shashi Kumar
• Format: Article
• Language: English
• Published: American Geophysical Union (AGU) 2020-10-01
• Series: Earth and Space Science
• Subjects: SAR tomography; PolTomSAR; Capon; vertical profile; forest height; UAVSAR
• Online Access: https://doi.org/10.1029/2020EA001230

Abstract Polarimetric synthetic‐aperture radar (SAR) remote sensing has been widely used for structural and biophysical parameters retrieval of forest vegetation. It has been found that the combination of polarimetric properties and interferometric characteristics of SAR remote sensing provides the capacity to retrieve forest height. The prime objective of this research was to investigate the potential of Polarimetric Synthetic Aperture Radar Tomography (PolTomSAR) for the forested and river region of Mondah National Park, Gabon. SAR tomography is an improved method for acquiring the height of geographical features. UAVSAR L‐band fully polarimetric multibaseline data have been used in this research (1.275 GHz). SAR data and ground data over the area have been collected in the year 2016. With the superresolution‐based Capon algorithm, multiple scatterers located at a different vertical position in the same azimuth range cell has been resolved and reconstructed. This work provides a framework for Capon‐based tomographic processing of multibaseline UAVSAR data for vertical profile retrieval of forest vegetation. The height profile of the forest patch having sparse, as well as dense vegetation, were retrieved. The vertical profile for a single azimuthal bin was obtained in range direction. The tomographic profile obtained was cross‐checked with the field‐measured forest height for the 16 locations in Mondah National Park, Gabon. To check the accuracy of the applied method, the statistical method of R2 and root‐mean‐square error (RMSE) is employed. The obtained RMSE of the result is 4.21 m and R2 is 0.92. The obtained results were concluded to find the potential of the Capon algorithm for the tomographic reconstruction of UAVSAR data.