Colliander A., Fisher J. B., Halverson G., Merlin Olivier, Misra S., Bindlish R., Jackson T. J., Yueh S. (2017). Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15. IEEE Geoscience and Remote Sensing Letters, 14 (11), p. 2107-2111. ISSN 1545-598X.
Titre du document
Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15
Colliander A., Fisher J. B., Halverson G., Merlin Olivier, Misra S., Bindlish R., Jackson T. J., Yueh S.
Source
IEEE Geoscience and Remote Sensing Letters, 2017,
14 (11), p. 2107-2111 ISSN 1545-598X
The Soil Moisture Active Passive (SMAP) mission provides a global surface soil moisture (SM) product at 36-km resolution from its L-band radiometer. While the coarse resolution is satisfactory to many applications, there are also a lot of applications which would benefit from a higher resolution SM product. The SMAP radiometer-based SM product was downscaled to 1 km using Moderate Resolution Imaging Spectroradiometer (MODIS) data and validated against airborne data from the Passive Active L-band System instrument. The downscaling approach uses MODIS land surface temperature and normalized difference vegetation index to construct soil evaporative efficiency, which is used to downscale the SMAP SM. The algorithm was applied to one SMAP pixel during the SMAP Validation Experiment 2015 (SMAPVEX15) in a semiarid study area for validation of the approach. SMAPVEX15 offers a unique data set for testing SM downscaling algorithms. The results indicated reasonable skill (root-mean-square difference of 0.053 m(3)/m(3) for 1-km resolution and 0.037 m(3)/m(3) for 3-km resolution) in resolving high-resolution SM features within the coarse-scale pixel. The success benefits from the fact that the surface temperature in this region is controlled by soil evaporation, the topographical variation within the chosen pixel area is relatively moderate, and the vegetation density is relatively low over most parts of the pixel. The analysis showed that the combination of the SMAP and MODIS data under these conditions can result in a high-resolution SM product with an accuracy suitable for many applications.
Plan de classement
Pédologie [068]
;
Bioclimatologie [072]
;
Etudes, transformation, conservation du milieu naturel [082]
;
Télédétection [126]
