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2025
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| Online Access: | https://doi.org/10.5281/zenodo.17159901 |
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| _version_ | 1866902092628623360 |
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| author | Petropoulos, George P. Detsikas, Spyridon E. Anagnostopoulos, Vasilis Lekka, Christina |
| author_facet | Petropoulos, George P. Detsikas, Spyridon E. Anagnostopoulos, Vasilis Lekka, Christina |
| contents | <p>Herein we present RegreSSM, a software tool that enables the downscaling of SMAP L3 Surface Soil Moisture (SSM) operational product from 36 kilometers to 1 km by the fusion of optical and thermal data retrieved from Sentinel-3 platform. The downscaling method is based on the well-established properties of the Ts/VI feature space. The tool has been developed in python programming language as a stand-alone application and can be executed in any operational system (OS). The application offers automated and reproduceable workflows for processing of SMAP L3 SSM products and Sentinel-3 dataset. The tool’s practical application is demonstrated over the Iberian Peninsula, where validation of the SMAP L3 product performed for all calendar year 2022 using in-situ observations from the REMEDHUS operational network stations. Results showed a satisfactory retrieval of SSM with a small average bias of 0.01 m<sup>3</sup>/m<sup>3</sup>, a MAE of 0.06 m<sup>3</sup>/m<sup>3</sup> and a RMSD of 0.07 m<sup>3</sup>/m<sup>3</sup>, confirming the ability of the proposed downscaling framework and of RegreSSM to retrieve SSM at the 1km spatial resolution. Results obtained herein were also comparable to the validation metrics reported for operational RS-based SSM products, with typically reported uncertainty of 0.04 m<sup>3</sup>/m<sup>3</sup>. The availability of RegreSSM to the SSM users’ community consists an important step towards the <a>standardization of downscaling procedures as well as bridging the spatial gap of existing operational SM products to the requirements of the fine-scale applications. </a> . It also contributes towards advancing the deployment of geo-processing tools utilizing the synergies between state-of-the-art methods and RS data available today from the most sophisticated satellites in orbit.</p> <div> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17159901 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
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| spellingShingle | RegreSSM: A novel software tool for downscaling the SMAP L3 soil moisture operational product utilizing the Ts - VI feature space and Sentinel-3 data Petropoulos, George P. Detsikas, Spyridon E. Anagnostopoulos, Vasilis Lekka, Christina <p>Herein we present RegreSSM, a software tool that enables the downscaling of SMAP L3 Surface Soil Moisture (SSM) operational product from 36 kilometers to 1 km by the fusion of optical and thermal data retrieved from Sentinel-3 platform. The downscaling method is based on the well-established properties of the Ts/VI feature space. The tool has been developed in python programming language as a stand-alone application and can be executed in any operational system (OS). The application offers automated and reproduceable workflows for processing of SMAP L3 SSM products and Sentinel-3 dataset. The tool’s practical application is demonstrated over the Iberian Peninsula, where validation of the SMAP L3 product performed for all calendar year 2022 using in-situ observations from the REMEDHUS operational network stations. Results showed a satisfactory retrieval of SSM with a small average bias of 0.01 m<sup>3</sup>/m<sup>3</sup>, a MAE of 0.06 m<sup>3</sup>/m<sup>3</sup> and a RMSD of 0.07 m<sup>3</sup>/m<sup>3</sup>, confirming the ability of the proposed downscaling framework and of RegreSSM to retrieve SSM at the 1km spatial resolution. Results obtained herein were also comparable to the validation metrics reported for operational RS-based SSM products, with typically reported uncertainty of 0.04 m<sup>3</sup>/m<sup>3</sup>. The availability of RegreSSM to the SSM users’ community consists an important step towards the <a>standardization of downscaling procedures as well as bridging the spatial gap of existing operational SM products to the requirements of the fine-scale applications. </a> . It also contributes towards advancing the deployment of geo-processing tools utilizing the synergies between state-of-the-art methods and RS data available today from the most sophisticated satellites in orbit.</p> <div> </div> |
| title | RegreSSM: A novel software tool for downscaling the SMAP L3 soil moisture operational product utilizing the Ts - VI feature space and Sentinel-3 data |
| url | https://doi.org/10.5281/zenodo.17159901 |