The Innovation Team of Smart Agriculture at the Institute of Agricultural Resources and Regional Planning (IARRP) of the Chinese Academy of Agricultural Sciences (CAAS), has published an overview of agricultural Synthetic Aperture Radar (SAR) quantitative remote sensing. 

The paper comprehensively and systematically reviewed the research progress on SAR inversion of crop parameters, summarized the current research status, identified existing issues and proposed future research directions. The research findings were published in the prestigious journal "IEEE Geoscience and Remote Sensing Magazine," with an Impact Factor of 16.2.

Crop canopy parameters can reflect the growth status and trends of crops and are crucial parameters linking remote sensing features to crop yield. Optical remote sensing is often affected by cloudy and rainy weather conditions, making it challenging to obtain effective remote sensing data sources. Synthetic Aperture Radar (SAR) technology can acquire target object scattering information under various weather conditions, providing data support for the timely acquisition of crop canopy information. The paper systematically reviewed over 30 years of research on the inversion of crop canopy parameters based on SAR remote sensing data, covering more than 100 references.

The research first reviewed key SAR radar characteristics and crop canopy parameters related to existing studies and summarized the factors influencing the accuracy of canopy parameter inversion. It then categorized retrieval models into empirical models, semi-empirical models and mechanistic models, elaborating on the principles, advantages, disadvantages and development trends of each model in detail. Finally, the paper discussed existing research issues and prospects for future development.

The study found that the crop growth process has anthropogenic attributes, making it more complex than the natural vegetation growth process. The microwave scattering information of crops can be accurately simulated by combining radar remote sensing mechanism with agronomic mechanism. In the model construction process, it is necessary to pay attention to the development mechanism model, explore the "real" relationship between microwave and crops, and cooperate with polarization decomposition technology and mechanism model to increase the interpretability of SAR radar features. Actively explore the integration of emerging technologies to expand the application scope of crop canopy parameter inversion models, aiming to further promote the stable development of food production and ensure food security.

The paper's first author was Zhao Rongkun, a doctoral student from the IARRP, while Associate Researcher Wu Shangrong was the corresponding author. The research was supported by the State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, National Key R&D Program, National Natural Science Foundation of China, and the Youth Innovation Program of the Chinese Academy of Agricultural Sciences.

Original article link:

https://ieeexplore.ieee.org/document/10699365