Abstract
Downscaled microwave soil moisture (SM) products with a fine resolution are of great importance for both local and regional studies. However, few studies have explored the merits of multiple downscaled microwave SM products. An evaluation of the different products could help to advance knowledge of the downscaled microwave SM products and help researchers to choose the appropriate downscaled SM products for use in further studies. In this research, five microwave SM products derived from Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E), AMSR2, and Soil Moisture and Ocean Salinity (SMOS) data were downscaled via the back-propagation neural network (BPNN). The BPNN was chosen because it can effectively simulate the nonlinear relationship between SM and the land surface temperature (LST)/vegetation index (VI). The different downscaled SM products were evaluated with in-situ SM data from the central Tibetan Plateau Soil Moisture/Temperature Monitoring Network (SMTMN) during the period from 1 August 2010 to 31 December 2012. Compared with the regression technique, the downscaled correlation coefficient (r) is significantly improved by the BPNN. The downscaled root-mean-square error (RMSE) and bias are comparable for the two techniques. As expected, LST and enhanced VI (EVI) are physically related to SM, and this is the most suitable combination for SM downscaling. Except for the ascending node of SMOS and AMSR2, the downscaled r is closely related to the original RMSE, and a lower original RMSE for the SM product results in a higher downscaled r. The BPNN-downscaled SMOS product in descending node is the closest to the in-situ SM among the different downscaled microwave SM products. The temporal variations and ranges of the microwave SM products are well maintained by the BPNN downscaling. Furthermore, the evaluations against in-situ SM reveal that the overall accuracies of the BPNN-downscaled SM products are very close to the original microwave SM products.
Highlights
Over the past decades, various passive microwave satellites or sensors have been launched to measure soil moisture (SM) globally, with revisit cycles of two to three days, including the AdvancedMicrowave Scanning Radiometer–Earth Observing System (AMSR-E), the Soil Moisture and OceanSalinity (SMOS) mission, the Advanced Microwave Scanning Radiometer-2 (AMSR2), and the SoilRemote Sens. 2017, 9, 402; doi:10.3390/rs9050402 www.mdpi.com/journal/remotesensingRemote Sens. 2017, 9, 402Moisture Active Passive (SMAP) mission
The enhanced VI (EVI) should be chosen for the SM downscaling because the r of the EVI is significantly higher than the r of the other remote sensing indexes (RSIs) at the Moderate Resolution Imaging Spectro-radiometer (MODIS) scale (Table 6)
The evaluation of the multiple downscaled microwave SM products is of vital importance for both regional- and local-scale studies and applications
Summary
Various passive microwave satellites or sensors have been launched to measure soil moisture (SM) globally, with revisit cycles of two to three days, including the AdvancedMicrowave Scanning Radiometer–Earth Observing System (AMSR-E), the Soil Moisture and OceanSalinity (SMOS) mission, the Advanced Microwave Scanning Radiometer-2 (AMSR2), and the SoilRemote Sens. 2017, 9, 402; doi:10.3390/rs9050402 www.mdpi.com/journal/remotesensingRemote Sens. 2017, 9, 402Moisture Active Passive (SMAP) mission. Salinity (SMOS) mission, the Advanced Microwave Scanning Radiometer-2 (AMSR2), and the Soil. Except for the 9-km resolution of the SMAP SM product [1], which is obtained by merging radiometer with radar data, the other instruments are characterized by a coarse spatial resolution (~25-km) [2,3]. The radar instrument of SMAP broke down on 7 July 2015, which resulted in the terminated transmission of satellite-based SM observations at a spatial resolution finer than 10-km. These SM products can be insufficient for local or regional studies due to their coarse spatial resolution, where SM observations at a 1–10-km resolution are commonly required [4]. Different remote sensing data and auxiliary data are used for microwave SM product downscaling, such as optical/thermal infrared (OTI) remote sensing data [4,5,6,7,8,9,10,11,12,13], active microwave data [1,14,15], and topographic, vegetation, and soil data [16]
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