Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8866561 | Remote Sensing of Environment | 2018 | 14 Pages |
Abstract
The NASA Soil Moisture Active Passive (SMAP) mission was launched on January 31st, 2015. The spacecraft was to provide high-resolution (3â¯km and 9â¯km) global soil moisture estimates at regular intervals by combining for the first time L-band radiometer and radar observations. On July 7th, 2015, a component of the SMAP radar failed and the radar ceased operation. However, before this occurred the mission was able to collect and process ~2.5â¯months of the SMAP high-resolution active-passive soil moisture data (L2SMAP) that coincided with the Northern Hemisphere's vegetation green-up and crop growth season. In this study, we evaluate the SMAP high-resolution soil moisture product derived from several alternative algorithms against in situ data from core calibration and validation sites (CVS), and sparse networks. The baseline algorithm had the best comparison statistics against the CVS and sparse networks. The overall unbiased root-mean-square-difference is close to the 0.04â¯m3/m3 the SMAP mission requirement. A 3â¯km spatial resolution soil moisture product was also examined. This product had an unbiased root-mean-square-difference of ~0.053â¯m3/m3. The SMAP L2SMAP product for ~2.5â¯months is now validated for use in geophysical applications and research and available to the public through the NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC). The L2SMAP product is packaged with the geo-coordinates, acquisition times, and all requisite ancillary information. Although limited in duration, SMAP has clearly demonstrated the potential of using a combined L-band radar-radiometer for proving high spatial resolution and accurate global soil moisture.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Computers in Earth Sciences
Authors
Narendra N. Das, Dara Entekhabi, R. Scott Dunbar, Andreas Colliander, Fan Chen, Wade Crow, Thomas J. Jackson, Aaron Berg, David D. Bosch, Todd Caldwell, Michael H. Cosh, Chandra H. Collins, Ernesto Lopez-Baeza, Mahta Moghaddam, Tracy Rowlandson,