Editorial for the Special Issue “Microwave Indices from Active and Passive Sensors for Remote Sensing Applications”

Since the early 1980s, the capabilities of satellite sensors operating at microwaves for the remote sensing of Earth’s surface have been widely assessed in a number of studies (e.g., [1]). Due to the high sensitivity of microwave emission and scattering to water content in the observed surfaces, microwave sensors, both active (scatterometers, SAR) and passive (radiometers), can provide useful information on the hydrological and carbon cycles, enabling the retrieval of the main soil, snow and vegetation parameters (e.g., [2,3]).

Further research demonstrated that a significant accuracy improvement could be obtained by combining data collected at different frequencies and polarizations in appropriate indices, with respect to the one achievable with single frequency/polarization observations. In particular, Microwave Indices have been successfully related to the main geophysical parameters associated to land hydrological cycle, such as soil moisture content, plant water content and snow depth or snow water equivalent (e.g., [4,5,6]).

The research conducted on microwave radiometry pointed out that given combinations of data acquired by satellite sensors such as SSM/I, AMSR-E and AMSR2 can be successfully related to snow and vegetation parameters. Among these indices, the Frequency Index, which is the difference between the brightness temperatures at two frequencies (i.e., Ka and Ku bands), showed a marked sensitivity to snow cover [7], while the Spectral Polarization Indices, which are obtained combining different polarizations and frequencies, were able to correctly identify relevant values of snow depths [8,9,10,11]. Moreover, the Polarization Indices, obtained at lower frequencies (i.e., X- and C-bands) as the difference between the two polarizations (H and V), showed a significant correlation to the vegetation biomass, allowing the correction for the effects of vegetation in the retrievals of soil moisture and the retrieval of herbaceous and agricultural vegetation biomass [11].

Similar results have been obtained in the case of active sensors (i.e., SAR and scatterometers) operating at C- and X- bands; their derived indices, as the Radar Vegetation Index (RVI) [12], were proven to be highly related to vegetation structure and vegetation biomass. These indices have been largely used for correcting the effect of vegetation cover in soil moisture retrievals and in estimating the vegetation biomass [13,14].

This special issue was aimed at providing an overview of the capabilities of Microwave Indices for remote sensing applications. Besides demonstrating their sensitivity to the main parameters of soil, vegetation and snow, the special issue was focused on the use of Microwave Indices in retrieval algorithms devoted to the estimate of soil moisture, vegetation biomass and snow depth/water equivalent, at both the local and global scale.

The obtained results sufficiently demonstrated that the synergy between observations at different frequencies and polarizations can significantly improve the capabilities of microwave sensors in observing and retrieving parameters related to the hydrological and the carbon cycles.

In particular, the studies belonging to this special issue demonstrated the capabilities of microwave derived indices for a number of applications that span from the retrieval of soil moisture based on Sentinel-1 data in wetland ecosystems [15] to the assessment of RVI as microwave metric of vegetation cover [16]. Also, the potential of Sentinel-1 cross ratio VH/VV in monitoring crop conditions was successfully evaluated [17] and the use of SAR derived vegetation descriptors for improving the soil moisture retrieval was exploited in [18], while the fusion of scatterometric and SAR data, aimed again at the soil moisture retrieval, is proposed in [19]. Finally, the synergy of Sentinel-1 and 2 in detecting grassland phenology in mountain regions is exploited in [20]. As applications devoted to snow monitoring, the co-pol. and dual-frequency ratios at Ku-, X- and C-bands were demonstrated to be adequately sensitive to variations in snow thickness for the Antarctic first year ice [21]. In [22], the combination of active and passive microwave acquisitions allowed characterizing the seasonal behavior of snow properties and retrieving the effective correlation length and the snow water equivalent. Finally, an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in monitoring soil moisture, snow depth and vegetation biomass was presented in [23].