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Open AccessArticle

Stepwise Disaggregation of SMAP Soil Moisture at 100 m Resolution Using Landsat-7/8 Data and a Varying Intermediate Resolution

1
Centre d’Etudes Spatiales de la BIOsphère (CESBIO, Université de Toulouse (CNES/CNRS/INRA,IRD/UPS), 31013 Toulouse, France
2
Faculty of Sciences and Techniques, Cadi Ayyad University, Marrakech 40000, Morocco
3
Center for Remote Sensing Application (CRSA), University Mohammed VI Polytechnic (UM6P), Benguerir 43150, Morocco
4
isardSAT S.L, Parc Tecnologic Barcelona Activa, 08042 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1863; https://doi.org/10.3390/rs11161863
Received: 25 June 2019 / Revised: 29 July 2019 / Accepted: 4 August 2019 / Published: 9 August 2019
(This article belongs to the Special Issue Remote Sensing of Regional Soil Moisture)
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Abstract

Global soil moisture (SM) products are currently available from passive microwave sensors at typically 40 km spatial resolution. Although recent efforts have been made to produce 1 km resolution data from the disaggregation of coarse scale observations, the targeted resolution of available SM data is still far from the requirements of fine-scale hydrological and agricultural studies. To fill the gap, a new disaggregation scheme of Soil Moisture Active and Passive (SMAP) data is proposed at 100 m resolution by using the disaggregation based on physical and theoretical scale change (DISPATCH) algorithm. The main objectives of this paper is (i) to implement DISPATCH algorithm at 100 m resolution using SMAP SM and Landsat land surface temperature and vegetation index data and (ii) to investigate the usefulness of an intermediate spatial resolution (ISR) between the SMAP 36 km resolution and the targeted 100 m resolution. The sequential disaggregation approach from 36 km to ISR (ranging from 1 km to 30 km) and from ISR to 100 m resolution is evaluated over 22 irrigated field crops in central Morocco using in-situ SM measurements collected from January to May 2016. The lowest root mean square difference (RMSD) between the 100 m resolution disaggregated and in-situ SM is obtained when the ISR is around 10 km. Therefore, the two-step disaggregation is more efficient than the direct disaggregation from SMAP to 100 m resolution. Moreover, we propose a moving average window algorithm to increase the accuracy in the 100 m resolution SM as well as to reduce the low-resolution boxy artifacts on disaggregated images. The correlation coefficient between 100 m resolution disaggregated and in situ SM ranges between 0.5–0.9 for four out of the six extensive sampling dates. This methodology relies solely on remote sensing data and can be easily implemented to monitor SM at a high spatial resolution over irrigated regions. View Full-Text
Keywords: disaggregation; soil moisture; DISPATCH; Intermediate spatial resolution; SMAP disaggregation; soil moisture; DISPATCH; Intermediate spatial resolution; SMAP
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Ojha, N.; Merlin, O.; Molero, B.; Suere, C.; Olivera-Guerra, L.; Ait Hssaine, B.; Amazirh, A.; Al Bitar, A.; Escorihuela, M.J.; Er-Raki, S. Stepwise Disaggregation of SMAP Soil Moisture at 100 m Resolution Using Landsat-7/8 Data and a Varying Intermediate Resolution. Remote Sens. 2019, 11, 1863.

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