An Analysis of a Commercial GNSS-R Soil Moisture Dataset

Abstract

An analysis of a Level-2 (L2) soil moisture record extending from 1 May 2021 to 1 January 2024 derived from Spire, Inc.’s Global Navigation Satellite System Reflectometry (GNSS-R) observatories is presented. The product's sensitivity to large scale soil moisture variability is demonstrated using an example of a 2022 flood in Pakistan. Product consistency among the constellation's multiple satellites is also investigated; no clear evidence of intersatellite biases is observed. Further comparisons are performed with soil moisture datasets from the Soil Moisture Active Passive (SMAP) and Cyclone Global Navigation Satellite System (CYGNSS) missions, from the European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5), and from in situ International Soil Moisture Network (ISMN) sites. Although an overall product correlation with SMAP soil moisture of approximately 85$\%$ is determined, per-pixel correlations vary significantly and per-pixel root-mean-square errors (RMSE) can range from 0.02 to 0.09 (cm$^{3}$/cm$^{3}$) depending on land class. The importance of applying the product's quality flags is also demonstrated. The influence of other calibration effects and inland water body contamination on these results is also discussed.

Keywords

• Bistatic radar systems
• CubeSats
• global navigation satellite systems reflectometry (GNSS-R)
• rough surface scattering
• SmallSats
• soil moisture