Enhancing remotely sensed soil moisture estimations using in situ ancillary information
SPIE Newsroom DOI: 10.1117/2.1201301.004710 – URL: http://spie.org/x92147.xml – 2013
Abstract: Developing algorithms used to generate soil moisture maps of agricultural, bare soils from synthetic aperture radar systems benefits from including ancillary information within a Bayesian retrieval scheme. Soil moisture is a key variable related to crop development and yield. Too much or too little moisture can each have devastating effects: persistently dry soil causes plants to wilt and diminishes their ability to transpire and grow. By contrast, excess moisture results in poor seed germination, inadequate nutrient uptake, and soil compaction. Consequently, the early assessment of soil moisture reserves, and monitoring moisture changes, is particularly important prior to—and throughout—the seeding season.
In response to this demand for information, a systematic effort has been made to develop maps of soil moisture over agricultural areas. Orbiting microwave synthetic aperture radar (SAR) systems offer the opportunity to monitor moisture content at different scales and under almost any weather condition. SAR systems leverage the known sensitivity that the backscattered signal (which originated in the sensor and was scattered by the target) exhibits to soil parameters, including soil moisture and soil roughness.1 However, the relationship between the backscattered signal and soil parameters is not straightforward, and consequently no operational SAR-derived soil moisture maps are yet available.
The major obstacles to developing such maps include the difficulty in modeling the scattering processes that relate backscattering to soil properties (moisture and roughness),2 the speckle noise,3 and the difficulty in measuring soil roughness in the field. The former two mainly relate to the SAR imaging system, whereas the latter relates to soil heterogeneity.4, 5 Moreover, several combinations of surface parameters can usually produce the same SAR observation. As a consequence, the retrieval of soil parameters remains challenging, and soil-moisture maps derived from remotely sensed SAR data remain fairly inaccurate.