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dc.contributor.authorAli Eweys, Omar
dc.contributor.authorEscorihuela, Maria José
dc.contributor.authorVillar Mir, Josep Ma.
dc.contributor.authorEr-Raki, Salah
dc.contributor.authorAmazirh, Abdelhakim
dc.contributor.authorOlivera, Luis
dc.contributor.authorJarlan, Lionel
dc.contributor.authorKhabb, Saïd
dc.contributor.authorMerlin, Olivier
dc.description.abstractThe 40 km resolution SMOS (Soil Moisture and Ocean Salinity) soil moisture, previously disaggregated at a 1 km resolution using the DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) method based on MODIS optical/thermal data, is further disaggregated to 100 m resolution using Sentinel-1 backscattering coefficient (σ°). For this purpose, three distinct radar-based disaggregation methods are tested by linking the spatio-temporal variability of σ° and soil moisture data at the 1 km and 100 m resolution. The three methods are: (1) the weight method, which estimates soil moisture at 100 m resolution at a certain time as a function of σ° ratio (100 m to 1 km resolution) and the 1 km DISPATCH products of the same time; (2) the regression method which estimates soil moisture as a function of σ° where the regression parameters (e.g., intercept and slope) vary in space and time; and (3) the Cumulative Distribution Function (CDF) method, which estimates 100 m resolution soil moisture from the cumulative probability of 100 m resolution backscatter and the maximum to minimum 1 km resolution (DISPATCH) soil moisture difference. In each case, disaggregation results are evaluated against in situ measurements collected between 1 January 2016 and 11 October 2016 over a bare soil site in central Morocco. The determination coefficient (R2) between 1 km resolution DISPATCH and localized in situ soil moisture is 0.31. The regression and CDF methods have marginal effect on improving the DISPATCH accuracy at the station scale with a R2 between remotely sensed and in situ soil moisture of 0.29 and 0.34, respectively. By contrast, the weight method significantly improves the correlation between remotely sensed and in situ soil moisture with a R2 of 0.52. Likewise, the soil moisture estimates show low root mean square difference with in situ measurements (RMSD = 0.032 m3 m−3).ca_ES
dc.description.sponsorshipThis work is a contribution to the REC project funded by the European Commission Horizon 2020 Programme for Research and Innovation (H2020) in the context of the Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) action under grant agreement no: 645642. In addition, this work has been partially funded by a public grant of Ministerio de Economía y Competitividad (DI-14-06587) and AGAUR-Generalitat de Catalunya (DI-2015-058).ca_ES
dc.relation.isformatofReproducció del document publicat a
dc.relation.ispartofRemote Sensing, 2017, vol. 9, núm. 11, p. 1-20ca_ES
dc.rightscc-by (c) Ali et al., 2017ca_ES
dc.subjectSoilmoisture and ocean salinity satellite (SMOS)ca_ES
dc.titleDisaggregation of SMOS soil moisture to 100m resolution using MODIS optical/thermal and sentinel-1 radar data: evaluation over a bare soil site in moroccoca_ES

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