Abstract
This work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils. Experimental results obtained with ground-based radiometers on different types of natural surfaces by the Microwave Remote Sensing Group of IFAC-CNR starting from ‘80s, are summarized and interpreted by means of theoretical models. It has been pointed out that, with respect to single frequency/polarization observations, microwave indices revealed a higher sensitivity to some significant parameters, which characterize the hydrological cycle, namely: soil moisture, vegetation biomass and snow depth or snow water equivalent. Electromagnetic models have then been used for simulating brightness temperature and microwave indices from land surfaces. As per vegetation covered soils, the well-known tau-omega (τ-ω) model based on the radiative transfer theory has been used, whereas terrestrial snow cover has been simulated using a multi-layer dense-medium radiative transfer model (DMRT). On the basis of these results, operational inversion algorithms for the retrieval of those hydrological quantities have been successfully implemented using multi-channel data from the microwave radiometric sensors operating from satellite.
Highlights
Microwave radiometry has been used since the first space Earth’s observations to investigate some important surface phenomena over the oceans and land at global scale
This work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils
The early experiments demonstrated that parameters such as ice concentration, wind speed and precipitations over the ocean, as well as some physical characteristics of soil, snow and vegetation can be retrieved at different levels of accuracy and reliability with more or less sophisticated instruments and algorithms developed in several times since the ‘80s. (e.g., [1])
Summary
Microwave radiometry has been used since the first space Earth’s observations to investigate some important surface phenomena over the oceans and land at global scale. Some Microwave Indices have been successfully related to the main geophysical parameters associated to land hydrological cycle, such as soil moisture (SMC), Plant Water Content (PWC), and Snow Depth (SD) or Snow Water Equivalent (SWE) These indices have been used for implementing operational retrieval algorithms based on data from different channels of satellite radiometric sensors (e.g., SMMR, SSM/I, AMSR-E, AMSR2). Other combinations of frequency channels and polarizations have been tested to evaluate their sensitivity to SWE and, among these indices, the Spectral Polarization Difference defined as SPD = (TbKuV − TbKaV) + (TbKuV − TbKaH) was identified as the best correlated quantity to SD and SWE [38] Both FI and SPD present rather high correlation (in terms of R2) to SD and SWE, as demonstrated in [41], where the comparison of radiometric data with ground truth has shown the following logarithmic regressions: FI = 9.4 Ln(SWE) − 27.59 (R2 = 0.71); SPD = 22.76 Ln(SWE) − 58.32 (R2 = 0.76) in a range of SWE up to 500 mm.
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