The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations
Open accessAbstract
Abstract Comprehensive assessments on the reliability of remotely sensed soil moisture products are undeniably essential for their advancement and application. With the establishment of extensive dense networks across the globe, mismatches between satellite footprints and ground single-point observations can be feasibly relieved. In this study, five remotely sensed soil moisture products, namely, the Soil Moisture Active Passive (SMAP), two Soil Moisture and Ocean Salinity (SMOS) products, the Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2) and the European Space Agency (ESA) Climate Change Initiative (CCI), were systematically investigated by utilizing in-situ soil moisture observations from global dense and sparse networks. Distinguished from previous studies, several perturbing factors comprising the surface temperature, vegetation optical depth (VOD), surface roughness and spatial heterogeneity were taken into account in this investigation. Furthermore, products' skills under various climate regions were also evaluated. Through the results, the SMAP product captures temporal trends of ground soil moisture, exhibiting an averaged R of 0.729, whereas for overall accuracy, ESA CCI outperformed other products with a slightly smaller ubRMSE of 0.041 m3 m−3 and a bias of −0.005 m3 m−3. This complementarity between SMAP and ESA CCI was further demonstrated under different climate conditions and can afford the reference of their integration for a more reliable global soil moisture product. Though some underestimations still exist, the newly developed SMOS- INRA-CESBIO (SMOS-IC) was illustrated to gain considerable upgrades with regard to R and ubRMSE compared to SMOS-L3 product, especially in dense VOD conditions achieving the highest R compared to other products. Generally, the underestimations of the European Centre for Medium-Range-Weather Forecasts (ECMWF) surface temperature used for SMOS under moderate or high VOD, heterogeneity, and most surface roughness conditions were consistent with the underestimations of the soil moisture product and provide the directions of product promotions. As for LPRM surface temperature, the worse skills can partially explain the unsatisfactory performances for LPRM soil moisture products. In spite of relatively acceptable skills of SMAP and SMOS-IC soil moisture products concerning R under moderate or dense VOD, small surface roughness, low heterogeneity conditions and temperate and cold climate types, advances in soil moisture products under high or even slightly low VOD, high roughness or topography complexity and heterogeneity, as well as in tropical or desert regions, remain challenging. It is expected that these findings can contribute to algorithm refinements, product enhancements (e.g., fusion and disaggregation) and hydrometeorological usages.
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Cites
SIMPSON, E. H. (1949) · Nature · doi:10.1038/163688a0 · Cited by 14,164
Updated world map of the Köppen-Geiger climate classification
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Updated world map of the Köppen-Geiger climate classification
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Investigating soil moisture–climate interactions in a changing climate: A review
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., & Teuling, A. J. (2010) · Earth-Science Reviews · doi:10.1016/j.earscirev.2010.02.004 · Cited by 5,638
The Soil Moisture Active Passive (SMAP) Mission
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., et al. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2043918 · Cited by 3,754
The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle
Kerr, Y. H., Waldteufel, P., Wigneron, J.-P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.-J., Font, J., Reul, N., Gruhier, C., et al. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2043032 · Cited by 1,988
Soil moisture retrieval from AMSR-E
Njoku, E. G., Jackson, T. J., Lakshmi, V., Chan, T. K., & Nghiem, S. V. (2003) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2002.808243 · Cited by 1,522
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Cited by
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn, S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., et al. (2021) · Hydrology and Earth System Sciences · doi:10.5194/hess-25-17-2021 · Cited by 380
Kang, Y., Bassiouni, M., Gaber, M., Lu, X., & Keenan, T. F. (2025) · Earth System Science Data · doi:10.5194/essd-17-3009-2025 · Cited by 22
Metadata
- Authors
- Ma, H., Zeng, J., Chen, N., Zhang, X., Cosh, M. H., & Wang, W.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 231
- Pages
- 111215
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2955045786
- Cited by
- 389
- References
- 46
- FWCI
- 17.52
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Ma, H., Zeng, J., Chen, N., Zhang, X., Cosh, M. H., & Wang, W. (2019). Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2019.111215
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