Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15

Authors: COLLIANDER, A. - Jet Propulsion Laboratory; FISHER, J. - Jet Propulsion Laboratory; HALVERSON, G. - Jet Propulsion Laboratory; MERLIN, O. - University Of Toulouse; MISRA, S. - Jet Propulsion Laboratory; BINDLISH, R. - Goddard Space Flight Center; Jackson, Thomas; YEUH, S. - Jet Propulsion Laboratory

Submitted to: Geoscience and Remote Sensing Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/11/2017
Publication Date: 11/1/2017
Citation: Colliander, A., Fisher, J., Halverson, G., Merlin, O., Misra, S., Bindlish, R., Jackson, T.J., Yeuh, S. 2017. Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15. Geoscience and Remote Sensing Letters. 14:2107-2111.

Interpretive Summary: A downscaling analysis of the Soil Moisture Active Passive (SMAP) coarse resolution radiometer-based soil moisture (SM) product using Moderate Resolution Imaging Spectroradiometer (MODIS) data was conducted for a semiarid rangeland site to provide higher spatial resolution information. The approach uses land surface temperature and normalized difference vegetation index (NDVI) to construct soil evaporative efficiency to downscale the SMAP soil moisture. The algorithm was applied over one pixel in the SMAP Validation Experiment 2015 domain and the downscaled soil moisture was compared with airborne based high resolution soil moisture. The combination of the small-scale variability of soil moisture, soil evaporation controlling the surface temperature, and availability of the airborne high-resolution SM measurements offered a unique opportunity to test this algorithm. The results showed that the algorithm demonstrated reasonable skill in resolving higher resolution soil moisture features within the coarse scale pixel. The analysis of the approach benefited from the features of the study domain; that the surface temperature is controlled by soil evaporation, the topographical variation within the pixel area is relatively moderate, and the vegetation density is relatively low over most parts of the pixel. The results show 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.

Technical Abstract: The SMAP (Soil Moisture Active Passive) mission provides global surface soil moisture 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 soil moisture product. In this paper the SMAP radiometer-based soil moisture product was downscaled to 1 km using MODIS (Moderate Resolution Imaging Spectroradiometer) data, and validated against airborne data from the PALS (Passive Active L-band System) instrument. The downscaling approach uses MODIS land surface temperature and normalized difference vegetation index (NDVI) to construct soil evaporative efficiency, which is used to downscale the SMAP soil moisture. 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 dataset for testing soil moisture downscaling algorithms. The results showed that the approach had reasonable skill (root mean square difference of 0.053 m3/m3 for 1-km resolution and 0.037 m3/m3 for 3-km resolution) in resolving high resolution soil moisture 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 soil moisture product with an accuracy suitable for many applications.