In the face of climate change and escalating water scarcity, precision agriculture is becoming an increasingly vital tool for farmers and agricultural managers. A new systematic review, published in *Science of Remote Sensing*, sheds light on how remote-sensing technologies are revolutionizing soil moisture estimation—a critical factor for agricultural sustainability and water-resource management. Led by Ana C. Teixeira of the University of Trás-os-Montes e Alto Douro and the Institute for Systems and Computer Engineering, Technology and Science in Portugal, the study synthesizes recent advancements and emerging trends in this rapidly evolving field.
Soil moisture is a cornerstone of agricultural productivity, influencing everything from crop yields to irrigation efficiency. Traditional methods of measuring soil moisture are often labor-intensive and limited in scope, making them impractical for large-scale farming operations. Remote-sensing technologies, however, offer a transformative solution by enabling large-scale, high-resolution, and continuous monitoring. The review analyzed 64 studies published between 2016 and 2024, focusing on agricultural applications of remote-sensing data for soil moisture estimation.
The study reveals that satellite observations dominate the literature, accounting for 73% of the reviewed studies. Unmanned aerial vehicles (UAVs), though less common, are increasingly being used for high-resolution, site-specific assessments. “Multi-sensor fusion, combining optical, thermal, and microwave data, is a growing strategy to overcome the limitations of individual sensors,” Teixeira explains. This approach leverages the strengths of different sensors, such as the weather-independent measurements of active Synthetic Aperture Radar (SAR) systems and the spectral indices provided by optical and thermal sensors.
Learning-based methods, which include machine and deep learning, are the most frequently used approach in the reviewed studies, appearing in 54% of the research. These methods excel at modeling complex relationships between soil moisture and remote-sensing variables, offering promising avenues for improving accuracy and scalability. However, the review also highlights significant challenges, including vegetation interference, surface roughness, and limited in-situ calibration data. To address these issues, researchers are exploring strategies such as longer-wavelength SAR (L- and P-bands), multi-sensor fusion, downscaling, and the integration of auxiliary datasets like soil texture, elevation, and meteorology.
The commercial implications of this research are substantial. Accurate, scalable, and operational soil-moisture monitoring can significantly enhance precision agriculture, enabling farmers to optimize irrigation, reduce water waste, and improve crop yields. As climate change intensifies water scarcity, these technologies will become even more critical for sustainable agricultural practices. “By synthesizing recent advances and emerging trends, this review provides practical guidance for accurate, scalable, and operational soil-moisture monitoring in precision agriculture and environmental management,” Teixeira notes.
The findings of this systematic review not only underscore the potential of remote-sensing technologies but also point to future developments in the field. As these technologies continue to evolve, they are likely to play an increasingly central role in shaping the future of agriculture, helping farmers adapt to the challenges of a changing climate and resource constraints. With further research and innovation, the integration of remote-sensing data into agricultural practices could unlock new levels of efficiency and sustainability, benefiting both farmers and the environment.
The study, led by Ana C. Teixeira of the Engineering Department at the University of Trás-os-Montes e Alto Douro and the Institute for Systems and Computer Engineering, Technology and Science in Portugal, was published in *Science of Remote Sensing*.