Evaluation and Analysis of AMSR2 and FY3B Soil Moisture Products by an In Situ Network in Cropland on Pixel Scale in the Northeast of China

Abstract

An in situ soil moisture observation network at pixel scale is constructed in cropland in the northeast of China for accurate regional soil moisture evaluations of satellite products. The soil moisture products are based on the Japan Aerospace Exploration Agency (JAXA) algorithm and the Land Parameter Retrieval Model (LPRM) from the Advanced Microwave Scanning Radiometer 2 (AMSR2), and the products from the FengYun-3B (FY3B) satellite are evaluated using synchronous in situ data collected by the EC-5 sensors at the surface in a typical cropland in the northeast of China during the crop-growing season from May to September 2017. The results show that the JAXA product provides an underestimation with a bias (b) of -0.094 cm3/cm3, and the LPRM soil moisture product generates an overestimation with a b of 0.156 cm3/cm3. However the LPRM product shows a better correlation with the in situ data, especially in the early experimental period when the correlation coefficient is 0.654, which means only the JAXA product in the early stage, with an unbiased root mean square error (ubRMSE) of 0.049 cm3/cm3 and a b of -0.043 cm3/cm3, reaches the goal accuracy (±0.05 cm3/cm3). The FY3B has consistently obtained microwave brightness temperature data, but its soil moisture product data in the study area is seriously missing during most of the experimental period. However, it recovers in the later period and is closer to the in situ data than the JAXA and LPRM products. The three products show totally different trends with vegetation cover, soil temperature, and actual soil moisture itself in different time periods. The LPRM product is more sensitive and correlated with the in situ data, and is less susceptible to interferences. The JAXA is numerically closer to the in situ data, but the results are still affected by temperature. Both will decrease in accuracy as the actual soil moisture increases. The FY3B seems to perform better at the end of the whole period after data recovery.

Evaluation of the AMSR2 L2 soil moisture product of JAXA on the Mongolian Plateau over seven years (2012–2018)

“…Although AMSR2 has been underestimating soil moisture because of the non-optimal measurement depth of in situ soil moisture, the AMSR2 L2 soil moisture product has been shown to have high quality, and it has proven useful for large-scale monitoring of surface soil moisture in grassland areas. For improved measurement of soil moisture, evaluations will be required using adequate datasets of in situ soil moisture measurements at an effective measurement depth, from other validation sites with different surface conditions [36], and using other soil moisture products such as the LPRM [17,18].…”

“…Although, as shown in 2.3, the AMSR2 algorithm eliminates the effects by the frequency difference, the values of brightness temperature and the normalized difference vegetation index (NDVI) themselves are affected directly by surface soil temperature and vegetation development, respectively. Thus, the effects of soil temperature and vegetation [18,33,34] should be considered possible causes of the underestimation. Figure 8 shows the relationship between the area-averaged in situ soil temperature at 3-cm depth at the time of AMSR2 soil moisture measurement and the AMSR2 soil moisture during periods of no rainfall in 2013 (wet year) and 2015 (dry year).…”

“…Unit of RMSE and Bias: m 3 remarkable decrease or increase in AMSR2 soil moisture with the increase in soil temperature within the range of 0-40 °C at 3-cm depth. Although these two factors are not correlated, Fu et al [18] highlighted the potential effect of soil temperature based on analysis of the surface soil temperature. The same results were obtained in other years.…”

“…However, as the values are relatively smaller and vary within a smaller range in comparison with those of AMSR2, it appears that SMOS is able to measure soil moisture more effectively than AMSR2, which measures soil moisture at a shallower depth. Fu et al [18] attempted to validate AMSR2 soil moisture measurements using in situ soil moisture at the depth of 2.5 cm in a crop field. Their results produced a value of negative bias (− 0.094 m 3 /m 3 ) slightly larger than determined in this study (Table 3).…”

“…The results of that study showed that the averaged value of the root mean square deviation for both 10and 25-km products was 0.05 m 3 /m 3 . Subsequently, other studies have conducted validation of the AMSR2 soil moisture products in many sites in Asia, Europe, Australia and the USA [12][13][14][15][16][17][18]. These studies showed that AMSR2 has certain characteristics such as negative bias and variation of the RMSE that have not been discussed fully.…”