1. A Rule Transference Algorithm for Obtaining High-Resolution Soil Moisture Surface in Arid and Semi-Arid Regions
- Author
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Lewis, Michael G., Fisher, Andmorgan, Smith, Clint, Qu, John J., and Houser, Paul
- Subjects
Remote sensing ,Soil moisture ,Hydrology ,Microwave devices ,Arid regions ,Machine learning ,Algorithms ,Algorithm ,Geography - Abstract
Soil moisture is vital to understanding many natural systems such as hydrology, climate and weather, erosion, and biology. Current remote sensing provides soil moisture data with a resolution on the scale of tens of kilometers, due to the current constraints of microwave antennae technology. In this study, we present a machine-learning technique based on rule transference that allows us to use a low-resolution but high-accuracy product, obtained through multiple proxies, to produce a high-resolution model of Earth's soil moisture. The low-resolution, high-accuracy microwave product is utilized as a dependent variable in rule-building only. This algorithm is simple, utilizes public data, and overcomes many local issues inherent in other techniques, such as topographic, biographic, temporal, and climatic variations. The final result demonstrates close parity with high-resolution airborne L-band radiometric data. Keywords: Downscaling, soil moisture, random forests, Introduction Soil moisture is a measure of the hydrological component within a finite amount of soil. The variability of soil moisture is highly dependent on the soil properties (Cosby et [...]
- Published
- 2020