Joint Soil and Above-Ground Biomass Characterization Using Radars

TL;DR

This paper presents a novel UAS-based radar method for joint estimation of soil moisture, biomass moisture, and height, overcoming calibration challenges and achieving high accuracy in simulations and experiments.

Contribution

It introduces a calibration-free algorithm leveraging UAS radar measurements to simultaneously estimate soil and biomass properties, improving accuracy over existing methods.

Findings

Soil moisture estimated with less than 1% median absolute error

Vegetation height estimated with 11.1cm median absolute error

Method effective in practical scenarios with varying biomass moistures and heights

Abstract

Soil moisture sensing through biomass or vegetation canopy has challenged researchers, even those who use SAR sensors with penetration capabilities. This is mainly due to the imposed extra time and phase offsets on Radio Frequency (RF) signals as they travel through the canopy. These offsets depend on the vegetation canopy moisture and height, both of which are typically unknown in agricultural and forest fields. In this paper, we leverage the mobility of an unmanned aerial system (UAS) to collect spatially-diverse radar measurements, enabling the joint estimation of soil moisture, above-ground biomass moisture, and biomass height, all without assuming any calibration steps. We leverage the changes in time-of-flight (ToF) and angle-of-arrival (AoA) measurements of reflected radar signals as the UAS flies above a reflector buried under the soil. We demonstrate the effectiveness of our algorithm by simulating its performance under realistic measurement noises as well as conducting lab experiments with different types of above-ground biomass. Our simulation results conclude that our algorithm is capable of estimating volumetric soil moisture to less than 1% median absolute error (MAE), vegetation height to 11.1cm MAE, and vegetation relative permittivity to 0.32 MAE. Our experimental results demonstrate the effectiveness of the proposed method in practical scenarios for varying biomass moistures and heights.