Proposal for A Global Soil Moisture Monitoring System Using GNSS-IR and Optical Remote Sensing

Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) extracts information about the surrounding environment of a ground-based GNSS antenna by analyzing the differences between direct signals and reflected multipath signals. In recent years, the use of GNSS-IR has become increasingly prevalent, driven by the growing demand for environmental monitoring. One of the most critical parameters for monitoring the environment is soil moisture due to its role in the water-heat transfer and energy exchange between the soil and the atmosphere, influencing the hydrological cycle. Soil moisture has been estimated via GNSS-IR using the GNSS multipath signal phase, which is determined by using observed Signal-to-Noise Ratio (SNR) values, because of a strong link between the multipath signal phase and the soil moisture. However, although there are thousands of continuously operating GNSS stations worldwide, most are used for navigation, and their potential to be used in GNSS-IR is yet to be fully explored both as standalone stations and as part of a broader global network.

The International GNSS Service (IGS) network is one of the most expansive global GNSS networks.  While the IGS stations vary in installation and surroundings, they collectively provide global coverage and continuously accessible and reliable data. We evaluated each station against criteria such as minimum antenna height and relevant surrounding topography. We found that several IGS stations can be utilized to estimate soil moisture, as approximately 33% are suitable for GNSS-IR. Each station's coverage can reach hundreds of square meters depending on the GNSS antenna height. Next, we use discrete soil moisture estimates based on optical remote sensing multispectral data, such as Sentinel-2 data, to fit a model that continuously estimates soil moisture using the suitable IGS stations' GNSS multipath signal SNR data. These discrete estimates can estimate volumetric soil moisture with a precision of around 0.02 [m^3/m^3] for a pixel's area of around [10 x 10] [m]. When combined with GNSS-IR data, they enable continuous soil moisture estimation with a comparable precision for the same area.

This approach enables establishing a global, continuous soil moisture monitoring system that leverages the continuous observations of GNSS-IR and the extensive coverage of the IGS network. Unlike optical remote sensing satellites, which are constrained by a 3–5-day revisit time, this system provides consistent, weather-independent measurements. By combining the continuous monitoring capabilities of GNSS-IR with the discrete, in-situ-independent soil moisture estimates from optical remote sensing, the system holds promise for global and continuous soil moisture monitoring with decent precision.

In this study, we present the initial results of a global soil moisture monitoring system utilizing data from several IGS stations located across various regions worldwide. Over a limited timeframe, we provide daily and sub-daily soil moisture estimates, demonstrating the system's potential for continuous and reliable environmental monitoring.