Abstract
Several studies have found that the vertical Fourier transform of lidar, interferometric Synthetic Aperture Radar (SAR), and stereo photogrammetric profiles at empirically-determined spatial frequencies enables high-performance forest aboveground biomass (AGB) estimation. Linear combinations of real and imaginary parts of Fourier transforms of Tomographic (multi-baseline) SAR (TomoSAR) profiles, from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne data, generate ~20%-precision estimates of AGB in the Saskatchewan area of Canada. We found that this 20% precision can be improved to ~15%, a factor of 30% improvement in root mean square error (RMSE) if, in addition to using Fourier transforms of the profile itself, we use Fourier transforms of the spatial, vertical derivative of the profile. The formulation of this "derivative"algorithm is the subject of this paper.
| Original language | English |
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| Title of host publication | IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2442-2445 |
| Number of pages | 4 |
| ISBN (Electronic) | 9798350360325 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 - Athens, Greece Duration: Jul 7 2024 → Jul 12 2024 |
Publication series
| Name | International Geoscience and Remote Sensing Symposium (IGARSS) |
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Conference
| Conference | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 |
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| Country/Territory | Greece |
| City | Athens |
| Period | 07/7/24 → 07/12/24 |
Funding
KCC was sponsored in part by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy.
Keywords
- Forest vegetation structure
- lidar remote sensing
- radar remote sensing