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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #348184

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation

item CHEN, F. - Science Systems And Applications, Inc
item Crow, Wade
item BINDLISH, R. - Goddard Space Flight Center
item COLLIANDER, A. - Jet Propulsion Laboratory
item BURGINS, M.S. - Jet Propulsion Laboratory
item ASANUMA, J. - University Of Tsukuba
item AIDA, K. - University Of Tsukuba

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/3/2018
Publication Date: 9/1/2018
Citation: Chen, F., Crow, W.T., Bindlish, R., Colliander, A., Burgins, M., Asanuma, J., Aida, K. 2018. Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation. Remote Sensing of Environment. 214:1-13.

Interpretive Summary: Accurate measurements of soil moisture are valuable for a wide range of agricultural applications including: irrigation scheduling, crop yield forecasting, drought assessment, and fertilizer application management. In January 2015, NASA launched the Soil Moisture Active/Passive (SMAP) satellite mission with the goal of improving our ability to globally measure soil moisture from space. Given that the mission has now been functioning for nearly three years, an important task is evaluating the quality of SMAP soil moisture retrieval products relative to existing, older satellites. Here, we apply a novel mathematical technique for globally evaluating SMAP soil moisture estimates relative to two other satellite-based soil moisture products. Results demonstrate that, globally speaking, SMAP provides the highest quality soil moisture estimates achieved to date. However, the paper does define a set of regional areas in which SMAP retrievals could be further improved. The results of this analysis are currently being used by SMAP mission developers to reprocess (and further enhance) the quality of SMAP global soil moisture data products.

Technical Abstract: Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally conducted against ground observations acquired at densely-instrumented sites of limited spatial-temporal coverage. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. This study provides a robust cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy over a quasi-global scale. In order to verify these assessments, the validity of TC error assumptions is examined at ground soil moisture monitoring sites using quadruple collocation. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. Overall, SMAP obtains the highest correlation of the three satellite products, although each product shows unique advantages in distinct geographic regions.