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Abstract
Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) provides a new opportunity for land observation. This study is the first to compare and evaluate the performance of the only two spaceborne GNSS-R satellite missions whose data are publicly available, i.e., the UK’s TechdemoSat-1 (TDS-1) and the US’s Cyclone Global Navigation Satellite System (CYGNSS), for sensitivity analysis with SMAP SM on a daily basis and soil moisture (SM) estimates on a monthly basis over Mainland China. For daily sensitivity analysis, the two data were matched up and compared for the period (i.e., May 2017 through April 2018) when they coexisted (R = 0.561 vs. R = 0.613). For monthly SM estimates, a back-propagation artificial neural network (BP-ANN) was used to construct a model using data from more than two years. The model was subsequently used to derive long-term and continuous SM maps over Mainland China. The results showed that TDS-1 and CYGNSS agree and correlate very well with the SMAP SM in Mainland China (R = 0.676, MAE = 0.052 m3m−3, and ubRMSE = 0.060 m3m−3 for TDS-1; R = 0.798, MAE = 0.040 m3m−3, and ubRMSE = 0.062 m3m−3 for CYGNSS). The retrieved results were further validated using monthly in situ SM data from dense sites across Mainland China. It was found that the SM derived from the TDS-1/CYGNSS also correlated well with in situ SM (R = 0.687, MAE = 0.066 m3m−3, and ubRMSE = 0.056 m3m−3 for TDS-1; R = 0.724, MAE = 0.052 m3m−3, and ubRMSE = 0.053 m3m−3 for CYGNSS). The results in this study suggested that TDS-1/CYGNSS and the upcoming spaceborne GNSS-R mission could be new and powerful data sources to produce SM data set at a large scale and with relatively high precision.
Highlights
Global Navigation Satellite System Reflectometry (GNSS-R) is a technique that exploits the capability of GNSS satellites to act as a bistatic-radar with the GNSS satellites as its transmitters and the receiver capable of processing scattered signals from the Earth’s surface [1,2]
The results of TDS-1 and Cyclone Global Navigation Satellite System (CYGNSS) were analyzed for sensitivity analysis on a daily basis and soil moisture (SM) estimation on a monthly basis, respectively
Since the TDS-1 data are distributed discretely and the daily Moderate-Resolution Imaging Spectroradiometer (MODIS) NDVI data set is severely affected by cloud and fog, surface reflectivity (SR) and Pr,eff are used as a proxy to compare with the soil moisture active and passive (SMAP) SM dataset
Summary
Global Navigation Satellite System Reflectometry (GNSS-R) is a technique that exploits the capability of GNSS satellites to act as a bistatic-radar with the GNSS satellites as its transmitters and the receiver capable of processing scattered signals from the Earth’s surface [1,2]. The first spaceborne GNSS-R was launched on the UK-Disaster Monitoring Constellation (UK-DMC) satellite in September 2003, which proved that spaceborne GNSS-R signals can reliably measure environmental parameters for ocean and land surface [3,4]. The TechdemoSat-1 (TDS-1), the experimental GNSS-R satellite, launched in July 2014, has demonstrated the strong sensitivity of the GNSS-R signal to various ocean and land parameters [5,6,7,8,9]. The Cyclone Global Navigation Satellite System (CYGNSS) mission, launched into space in December 2016, contains eight microsatellites with the same payload as the TDS-1. The CYGNSS was designed to measure ocean winds in the tropics, while reflections observed from the satellites were proved sensitive to land parameters [10,11,12,13]. Compared to TDS-1 (10–35 days) [14], the CYGNSS microsatellites randomly receive GNSS-R signals with revisiting times of approximately 2.8~7 h per day [12,15]
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