Forests in northern regions, like those across Canada, play a major role in storing carbon, regulating water, and responding to climate change. Satellites that measure microwave energy, such as the upcoming NASA/ISRO NISAR mission, are designed to observe these forested landscapes to improve our understanding of soil moisture, frozen ground, wetlands, and carbon cycling. However, interpreting satellite signals in these environments is difficult because the forest canopy, soil, and water all influence what the satellite sees—especially when conditions like freeze/thaw cycles and organic soils are involved.

To improve satellite-based monitoring, we participated in a field campaign called SMAPVEX22-Boreal in Saskatchewan, Canada. There, we collected detailed measurements of vegetation structure, soil moisture, and forest conditions. We also used high-resolution 3D laser scans to describe the shape and structure of trees. These data were used to build computer models that simulate how microwave signals scatter within the forest. We compared these simulations to actual radar observations from the UAVSAR aircraft.

Our results help explain how vegetation affects radar signals and will improve algorithms that estimate soil and water conditions from space. This work directly supports upcoming Earth observation missions and helps us better monitor northern ecosystems in a changing climate.