The interaction between radio waves and vegetation has been extensively studied for efficient wireless network planning. Both empirical and analytical models have been developed for this purpose. However, radio transmission within a wireless sensor network could be used for sensing the medium in the signal path in addition to data transmission within the network. Prior work suggested that radio waves interact strongly with water contained in vegetation. The dependence of radio waves on water is through its dielectric constant. In this thesis, the relationship between RF loss and water content in vegetation in the path of a radio communications link was modelled to study the feasibility of monitoring plant health using wireless communication networks.

A model to calculate the RF loss through packed vegetation with different moisture content was developed. This model only considers the dielectric constant of the vegetation and does not include the air component of the tree canopy. The model was further extended to calculate RF loss through tree canopies. Both the models were verified against experimental measurements acquired using Eucalyptus leaves and trees. The results show that there is a positive non-linear relationship between RF loss in dB and water content expressed as effective water path (EWP) in mm. Vegetation thickness is also a factor in RF loss, however the contribution was minor compared to water content of vegetation. This work has quantified the relationship between RF loss and water within vegetation. It may lead to wireless sensor networks being repurposed to monitor, over periods of many years, changes in plant water status.

Detection of plant water status is important for monitoring plant physiology. Previous studies showed that radio waves are attenuated when passing through vegetation such as trees, and models (both empirical and analytical) were developed. However, for models to be more broadly applicable across a broad range of vegetation types and constructs, basic electrical properties of the vegetation need to be characterised. In our previous work, a model was developed to calculate the RF loss through vegetation with varying water content. In this paper, the model was extended to calculate RF loss through tree canopies with or without an air gap. When the model was compared with the actual RF loss acquired using Eucalyptus blakelyi trees (with and without leaves), there was a systematic offset equivalent to a residual moisture content of 13% that was attributed to bound water. When the model was adjusted for the additional water content, the effective water path (EWP) was found to explain 72% of the variance in the measured RF loss.

Assessing plant water status is important for monitoring plant physiology. Previous studies showed that radio waves are attenuated when passing through vegetation such as trees. The degree of radio frequency (RF) loss has previously been measured for various tree types but the relationship between water content and RF loss has not been quantified. In this study, the amount of water inside leaves was expressed as an effective water path (EWP), the thickness of a hypothetical sheet of 100% water with the same mass. A 2.4331 GHz radio wave was transmitted through a wooden frame covered on both sides with 5 mm clear acrylic sheets and filled with Eucalyptus laevopinea leaves. The RF loss through the leaves was measured for different stages of drying. The results showed that there is a nonlinear relationship between effective water path (EWP) in mm and RF loss in dB. It can be concluded that 2.4 GHz frequency radio waves can be used to predict the water content inside eucalyptus leaves (0 < EWP < 14 mm; RMSE ± 0.87 mm) and demonstrates the potential to measure the water content of whole trees.

Previous studies have investigated the attenuation of 2.4 GHz radio waves and vegetation, and generated a model to predict RF loss in response to the effective water path (EWP) of both packed leaves and whole tree canopies. Owing to the absence of phase information in the radio signal strength (RSS) it is not possible to directly invert the model to elicit EWP. This paper builds upon previous work and proposes a two-point iteration methodology to predict actual gravimetric water content (M_g) of single tree canopies from RF loss. An investigation for sample tree canopies (including two trees in series) demonstrated M_g explained 72% of the variance in measured RF loss.