Integration of active and passive microwave signatures for characterization of soil properties.

摘要

Soil water is one of the key factors governing water and energy fluxes at the land surface. Microwave remote sensing at C- and L-bands provides soil moisture estimates, due to its high sensitivity to water content changes in the soil. The performances of the soil moisture estimates from retrieval and assimilation algorithms using microwave observations rely on realistic estimates of microwave signatures, backscattering (sigma0) or brightness temperature (TB) from microwave backscattering or emission models. This dissertation explores the impacts of soil moisture distribution within the near-surface and the soil characteristics on the state-of-the-art forward models that fail to reliably relate the near-surface soil moisture to observed sigma0 and TB. Concurrent passive microwave observations at C- and L-band were obtained from a previous conducted experiment in 2006. In addition, a field experiment was conducted to obtain simultaneous active and passive (AP) observations at L-band in 2012. These dataset were obtained at unprecedented high temporal resolution, every 15 minutes, from sandy, bare soils during highly dynamic periods. Procedures for AP sensor calibration were developed during the experiments. A methodology was implemented using dual-polarized C-band observation to estimate physically consistent soil parameters, for an irrigation event and subsequent drydown. These derived parameters were used in conjunction with the in situ moisture at deeper layers and different moisture profiles within the moisture sensing depth to obtain estimates of H-pol TB at L-band, that improve the RMSDs of TB estimates by 15 K during drydown periods. Furthermore, the complementarity of AP signatures was investigated by evaluating the sensitivity of sigma0 and emissivity (ep) to observed soil moisture and roughness measurements. It was found that the ep is consistently sensitive to the soil moisture on smooth and rough soil, but largely insensitive to surface roughness, in contrast to sigma0. Such complementarity of AP was utilized to estimate the soil moisture within moisture sensing depth using TB, while surface roughness was estimated from sigma0. These derived soil parameters provided physically consistent estimations of sigma0HH, sigma0 VV and TB with RMSDs of 1.47 and 1.24 dB, and 4.55 K, respectively, with respect to the observations during rough surface period.