Evaluation of Fengyun-3C Soil Moisture Products Using In-Situ Data from the Chinese Automatic Soil Moisture Observation Stations: A Case Study in Henan Province, China

Abstract

Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications, especially crop monitoring and disaster warning. Evaluating the dependability of satellite-derived soil moisture products on a large scale is crucial. In this study, we assessed the level 2 (L2) SM product from the Chinese Fengyun-3C (FY-3C) radiometer against in-situ measurements collected from the Chinese Automatic Soil Moisture Observation Stations (CASMOS) during a one-year period from 1 January 2016 to 31 December 2016 across Henan in China. In contrast, we also investigated the skill of the Advanced Microwave Scanning Radiometer 2 (AMSR2) and Soil Moisture Active/Passive (SMAP) SM products simultaneously. Four statistical parameters were used to evaluate these products’ reliability: mean difference, root-mean-square error (RMSE), unbiased RMSE (ubRMSE), and the correlation coefficient. Our assessment results revealed that the FY-3C L2 SM product generally showed a poor correlation with the in-situ SM data from CASMOS on both temporal and spatial scales. The AMSR2 L3 SM product of JAXA (Japan Aerospace Exploration Agency) algorithm had a similar level of skill as FY-3C in the study area. The SMAP L3 SM product outperformed the FY-3C temporally but showed lower performance in capturing the SM spatial variation. A time-series analysis indicated that the correlations and estimated error varied systematically through the growing periods of the key crops in our study area. FY-3C L2 SM data tended to overestimate soil moisture during May, August, and September when the crops reached maximum vegetation density and tended to underestimate the soil moisture content during the rest of the year. The comparison between the statistical parameters and the ground vegetation water content (VWC) further showed that the FY-3C SM product performed much better under a low VWC condition (<0.3 kg/m2) than a high VWC condition (>0.3 kg/m2), and the performance generally decreased with increased VWC. To improve the accuracy of the FY-3C SM product, an improved algorithm that can better characterize the variations of the ground VWC should be applied in the future.

Using FengYun-3C VSM Data and Multivariate Models to Estimate Land Surface Soil Moisture

“…The MWRI onboard FY-3 includes vertical and horizontal polarization modes (V/H) in the 10.65-GHz, 18.7-GHz, 23.8-GHz, 36.5-GHz, and 89.0-GHz frequency bands [29]. The characteristics, such as the bandwidth, sensitivity, calibration accuracy, scanning mode, and instantaneous field of view (IFOV), are shown in Table 1 [23]. Among all of the frequency bands, the channels in the 10.65 GHz band are capable of penetrating clouds and rain and are mainly used to obtain global surface sea temperature (SST), wind speed, SM content, and other geophysical parameters under all weather conditions.…”

“…FY-3C VSM products are retrieved from the L1 brightness temperature (BT) data collected by MWRI using a new inversion technique, i.e., the Q p model, which was built using advanced integral equation (AIE) model simulations of microwave emissions [14]. Compared with the single channel SM retrieval algorithm, both the vertical and horizontal polarizations of the X-band (10.65 GHz) were applied in the Q p model to decrease the effects of roughness and vegetation coverage [23]. Also, the pixels covered with snow, frozen soil, and coastal waters were removed from the FY-3C VSM retrievals.…”

“…The NDVI products derived from MODIS are the most mature and widely used source for monitoring vegetation status and estimating soil water contents at the regional scale as supplemental data in many previous studies [20,23]. Here, 14 tiles (h08v04, h08v05, h08v06, h09v04, h09v05, h09v06, h10v04, h10v05, h10v06, h11v04, h11v05, h12v04, h12v05, and h13v04) of monthly MODIS NDVI products (MOD13A3, v006) from the Terra satellite from January 2019 to October 2019 were downloaded from the NASA website (https://ladsweb.modaps.eosdis.nasa.gov/).…”

“…Among these soil moisture products, the FY-3/MWRI SM (FY-3 VSM) is an official SM product released by the National Satellite Meteorological Center (NSMC) of China and has been widely used to record the soil moisture content in the top layer with a spatial resolution of 25 km [18,23]. The FY-3 VSM products are retrieved from observations via the MWRI onboard FY-3 series satellites, including FY-3A, FY-3B, FY-3C, and FY-3D.…”

“…Generally, the FY-3C VSM product is considered to have a better quality than FY-3A and FY-3B, and longer available time series data than FY-3D. Zhu et al [23] assessed the performance of FY-3C VSM over cropland in Henan Province, China, during 2016, and the results indicated that the SM variation patterns of the FY-3C VSM retrievals were in good agreement with the measured SM. However, the FY-3C VSM tended to overestimate or underestimate the SM during the year.…”