350 rub
Journal Achievements of Modern Radioelectronics №7 for 2022 г.
Article in number:
Assessment of forest profile and biomass using the Earth polarimetric and tomographic remote sensing systems
Type of article: overview article
DOI: https://doi.org/10.18127/j20700784-202207-01
UDC: 528.8
Authors:

A.S. Petrov

Lavochkin Association (Khimki, Moscow region, Russia)

Abstract:

Knowledge of the forest structure and its changes is important for modeling the forest ecosystem, for example, for reliable estimation of biomass or for estimating carbon fluxes associated with the functional purpose of the forest. In recent years, two powerful polarimetric interferometry and tomography technologies have been developed (Pol-In-SAR and TomoSAR) using SAR systems for remote sensing, which make it possible to isolate information about natural and artificial objects by calculating the vertical power distribution of backscattering or 3-dimensional reflection.

In the Russian literature, the methods of implementing these new technologies are insufficiently covered. The purpose of the work is a brief overview of the methods used to assess the wave scattering profile from forests, restore the volume of surface biomass of forests and detect forest fires using synthetic aperture radars (SAR) operating in polarimetric interferometer modes.

The review describes the initial practical results of restoring the forest profile using tomographic SR. The formulation of the problem of modeling the backscattering profile is formulated, the main methods of its solution are indicated and references are given to the literature in which the problem is covered in greater detail. The allometric methods of estimating the surface biomass of the forest by its tomographic profile obtained as a result of processing the RSA signal are considered. Approaches to the construction of electrodynamic models of volumetric wave reflection from the forest and the earth's surface are described. Finally, the issues of identifying forest fires and burnt areas with the help of Pol-In-SAR and TomoSAR are touched upon.

The short list of literary sources given in the review can only be considered as initially introducing the reader to this new, interesting and complex subject, the serious development of which will actually require familiarization with many hundreds of publications.

Pages: 5-19
For citation

Petrov A.S. Assessment of forest profile and biomass using the Earth polarimetric and tomographic remote sensing systems. Achievements of modern radioelectronics. 2022. V. 76. № 7. P. 5–19. DOI: https://doi.org/ 10.18127/j20700784-202207-01 [in Russian]

References
  1. Research Results and Projects Status Report 2011 – 2017. Technical Report, October 2018. Microwaves and Radar Institute. https://www.researchgate.net/ publication/330384080.
  2. Massonnet D., Souyris J.-C. Imaging with synthetic aperture radar. EPFL Press. 2008.
  3. Cherniakov M. Bistatic radar: emerging technology. Part 4 by Krieger G. and Moreira A., Spaceborne Interferometric and Multistatic SAR Systems / John Wiley & Sons. 2008. P. 95–158.
  4. Petrov A.S., Nazarov A.E., Demin D.S. Otsenka tochnosti trekhmernogo otobrazheniya elementov rel'efa zemnoy poverkhnosti kosmicheskimi sistemami distantsionnogo zondirovaniya Zemli. Uspekhi sovremennoy radioelektroniki. 2022. T. 76. № 2. S. 5–15. DOI: https://doi.org/10.18127/j20700784-202202-01. [in Russian]
  5. Reigber A., Moreira A. First demonstration of airborne SAR tomography using multibaseline L-band data. IEEE Trans. Geosci. Remote Sens. 2000. V. 38. № 5. P. 2142–2152.
  6. Nannini M., Scheiber R., Moreira A. Estimation of the Minimum Number of Tracks for SAR Tomography. IEEE Transactions On Geoscience And Remote Sensing. 2009. V. 47. № 2. P. 531–543.
  7. Cazcarra-Bes V., Pardini M., Tello M., Papathanassiou K.P. Comparison of tomographic SAR reflectivity reconstruction algorithms for forest applications at L-band. IEEE Trans. Geosci. Remote Sens. 2020. V. 58. № 1. Р. 147–164.
  8. Korobkov M.A., Petrov A.S. Metody i algoritmy pelenga istochnikov radioizlucheniya. Elektromagnitnye volny i elektronnye sistemy. 2015. № 4. S. 3–32. [in Russian]
  9. Caicoya A.T., Pardini M., Hajnsek I., Papathanassiou K. Forest Above-Ground Biomass Estimation From Vertical Reflectivity Profiles at L-Band. IEEE Geoscience And Remote Sensing Letters. 2015. V. 12. № 12. Р. 2379–2383.
  10. Yu H., Zhang Z. The Performance of Relative Height Metrics for Estimation of Forest Above-Ground Biomass Using L- and X-Bands TomoSAR Data. IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, V. 14. 2021. Р. 1857–1871.
  11. Lasaponara R., Tucci B. Identification of Burned Areas and Severity Using SAR Sentinel-1. IEEE Geoscience And Remote Sensing Letters. 2019. V. 16. № 6. Р. 917–921.
Date of receipt: 30.05.2022
Approved after review: 16.06.2022
Accepted for publication: 30.06.2022