Huanting Huang improves accuracy of remote sensing

Huang won the Best Student Paper Award at the IEEE International Conference on Computational Electromagnetics for her work developing better electromagnetic models that calculate microwave interactions with tree and vegetation cover.

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Huanting Huang

Remote sensing is a key tool for monitoring environmental conditions. In remote sensing, satellites or high-flying aircraft measure the reflected and emitted radiation from a target geographical area to learn about the physical properties of that area. While remote sensing is used to monitor many different environmental properties, Huanting Huang, a PhD student in electrical and computer engineering, focuses on the remote sensing of soil moisture and vegetation.

Her most recent research, published in the paper, “Full Wave Simulations of Vegetation/Trees Using 3D Vector Cylindrical Wave Expansions In Foldy-Lax Multiple Scattering Equations,” won first prize for best student paper at the IEEE International Conference on Computational Electromagnetics 2019 held in Shanghai. The paper focuses on Huang’s work building better electromagnetic models to improve the accuracy of remote sensing.

Assessing soil moisture is important for drought monitoring, flood prediction, crop yield forecast, irrigation planning, and other environmental purposes. When attempting to measure soil moisture, trees and other vegetation often get in the way. As electromagnetic waves reflect off the soil on their way to a satellite, they bounce between water-filled leaves and limbs of plants and trees. This obscures the signal from the soil and alters the final reading of soil moisture. To account for the scattering and absorption of waves due to vegetation, researchers create models of plants and how they interact with radar waves to remove the interference from the soil moisture signal. However, many of these models are flawed.

For instance, current models rely on the assumption that tree branches and leaves are uniformly distributed and trees are spaced far apart. This leads to inaccurate results and flawed data. To address this, Huang built a better model that more realistically simulates the vegetation.

Huang’s method uses full wave simulations of the vegetation or trees. She breaks down the trees into smaller parts and encloses them within cylindrical shapes. The scattering properties of each single object can be determined by a computational technique called the T matrix approach, with 3D vector cylindrical wave expansions. The T matrix of each single object can be extracted from the off-the-shelf software or computer code, such as HFSS, FEKO, Infinite Cylinder Approximation (ICA) and Body of Revolution (BOR). The T matrices are then substituted into the Foldy-Lax multiple scattering equations.

Huang’s new model, which takes into account all the interactions among single objects, has been shown to be accurate and predicts much larger microwave transmission through forest than the previous models. A much larger transmission means the microwaves can better penetrate the vegetation and forest canopy, which improves the accuracy of soil moisture readings.

Huang’s previous method involved using spherical/spheroidal shapes instead of cylinders, but she’s found that cylinders are a better fit for tree trunks, trees and plants.

“It’s hard to enclose the whole tree in a sphere/spheroid, because the tree is so large, and the matrix with high order of spherical/spheroidal wave expansions becomes unstable,” she says. “By changing to a cylinder, we can enclose the tree trunks much more compactly, and it’s simpler and more stable.”

Huang’s research is a part of the NASA’s SMAP (Soil Moisture Active and Passive) mission. She received her undergraduate degree from the City University of Hong Kong, and she is advised by Prof. Leung Tsang.

Read more about Huang’s research, which won the IEEE Antennas and Propagation Society Ulrich L. Rohde Innovative Conference Paper Award on Computational Techniques in Electromagnetics last year