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Clewley, D, Whitcomb, JB, Akbar, R, Silva, AR, Berg, A, Adams, JR, Caldwell, T, Entekhabi, D and Moghaddam, M 2017 A Method for Upscaling In Situ Soil Moisture Measurements to Satellite Footprint Scale Using Random Forests. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (6). 2663-2673. https://doi.org/10.1109/JSTARS.2017.2690220
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clewley_et_al_upscaling_soil_moisture_2017_pre_print.pdf Available under License All Rights Reserved. Download (13MB) | Preview |
Abstract/Summary
Geophysical products generated from remotely sensed data require validation to evaluate their accuracy. Typically in situ measurements are used for validation, as is the case for satellite-derived soil moisture products. However, a large disparity in scales often exists between in situ measurements (covering meters to 10 s of meters) and satellite footprints (often hundreds of meters to several kilometers), making direct comparison difficult. Before using in situ measurements for validation, they must be “upscaled” to provide the mean soil moisture within the satellite footprint. There are a number of existing upscaling methods previously applied to soil moisture measurements, but many place strict requirements on the number and spatial distribution of soil moisture sensors difficult to achieve with permanent/semipermanent ground networks necessary for long-term validation efforts. A new method for upscaling is presented here, using Random Forests to fit a model between in situ measurements and a number of landscape parameters and variables impacting the spatial and temporal distributions of soil moisture. The method is specifically intended for validation of the NASA soil moisture active passive (SMAP) products at 36-, 9-, and 3-km scales. The method was applied to in situ data from the SoilSCAPE network in California, validated with data from the SMAPVEX12 campaign in Manitoba, Canada with additional verification from the TxSON network in Texas. For the SMAPVEX12 site, the proposed method was compared to extensive field measurements and was able to predict mean soil moisture over a large area more accurately than other upscaling approaches.
| Item Type: | Publication - Article |
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| Additional Information. Not used in RCUK Gateway to Research.: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Divisions: | Plymouth Marine Laboratory > Science Areas > Earth Observation Science and Applications |
| Depositing User: | Kim Hockley |
| Date made live: | 19 Feb 2019 14:32 |
| Last Modified: | 25 Apr 2020 09:59 |
| URI: | https://plymsea.ac.uk/id/eprint/8130 |
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