Towards Estimating Vegetation Water Content in Boreal Forests Using Tower-Based Radar Observations

Estimation of vegetation water content (VWC) in forest ecosystems is essential for understanding and monitoring forest health, transpiration, and responses to environmental changes. Currently there exists no remote sensing method capable of observing VWC changes in forests.

The BorealScat-2 radar tower, constructed in the Svartberget Experimental Forest in northern Sweden, aims to address this challenge by investigating the relationship between radar backscatter and VWC in a boreal forest. The tower provides tomographic radar images at P- (435 MHz), UHF- (600 MHz), and L- (1270 MHz) across all polarization combinations, offering high precision measurements at 30-minute intervals. The high precision is made possible by moving the antenna frame along a 4-m horizontal baseline, followed by incoherent averaging of the tomograms. Complementary in situ measurements, including sap flow sensors, trunk moisture sensors, dendrometers, and an eddy covariance flux tower, enable detailed analysis of water dynamics across the soil-plant-atmosphere continuum within the radar footprint.

Time series results show that P- and UHF-band backscatter covaries (positively correlated) with VWC, with UHF-band backscatter capturing VWC trends over timescales from hours to months. L-band radar observations, however, reveal an unexpected diurnal backscatter pattern, where canopy backscatter increases during periods of decreasing VWC, suggesting a complex interplay of scattering and attenuation effects. This behaviour contrasts with the expectation that an increase in VWC leads to an increase in backscatter. We propose an inversion model, accounting for attenuation effects, for estimating VWC from L-band backscatter.

Results show that the model successfully estimates changes in VWC from canopy backscatter and attenuation measured by the tower over timescales of hours to weeks, demonstrating the possibility of using radar observations for estimating VWC changes in forests. The findings underscore the relevance of tower-based radar observations for refining remote sensing algorithms and for presenting new applications for upcoming L-band synthetic aperture radar missions for global forest monitoring.