Dr. Nuno Carvalhais Profile

Dr. Nuno Carvalhais

at Max-Planck-Institut für Biogeochemie

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Proceedings Article | 9 October 2018 Presentation + Paper

Potential of UAV GNSS-R for forest biomass mapping

Laura Dente, Leila Guerriero, Nuno Carvalhais, Pedro Silva, Paula Soares, Paolo Ferrazzoli, Nazzareno Pierdicca

Proceedings Volume 10788, 1078809 (2018) https://doi.org/10.1117/12.2327130

KEYWORDS: Reflectivity, Receivers, Vegetation, Unmanned aerial vehicles, Neural networks, Antennas, Satellite navigation systems, Electromagnetic simulation

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A combined Position-Reflectometry Galileo receiver on board a low cost unmanned aerial platform (UAV) was developed in the framework of the Combined Positioning-Reflectometry Galileo Code Receiver for Forest Management project (COREGAL) with the main aims of evaluating the accurate positioning in areas where no GNSS ground infrastructures are available and of investigating the forest biomass mapping.

In this context, the Soil and Vegetation Reflection Simulator (SAVERS) was employed to simulate GNSS-R data in order to analyze the GNSS-R sensitivity to biomass, to create a Look Up Table (LUT) of GNSS-R reflectivity and to carry out a biomass retrieval test.

SAVERS simulated the mean power of the reflected GNSS-R signals by applying the integral bistatic equation taking into account the scattering contributions from soil and vegetation. It was shown that the GNSS-R sensitivity to forest biomass can be enhanced by filtering out the incoherent component of the signal, i.e. by using a long coherent integration time. A LUT was created by running SAVERS for a realistic range of the input parameters. Moreover, a GNSS-R synthetic dataset was generated for the case of a cork oak open forest in Portugal and a retrieval test was carried out. A neural network with two hidden layers was trained on the LUT and the forest biomass was estimated from the synthetic data. The biomass mean retrieval error was approximately 10 t/ha.

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