Francesco Montomoli

Simulating Multifrequency Ground-Based Radiometric Measurements at Dome C—Antarctica

Recent interest by the research community in investigating Antarctica at low microwave frequency is stimulated by the availability of new satellite-borne radiometers. Special attention has been paid to the Dome C region of the East Antarctic Plateau, which was selected by the European Space Agency (ESA) as a calibration and validation test site for the soil moisture and ocean salinity (SMOS) mission. In order to support this mission and better characterize the site, several surface and airborne campaigns were conducted. Analysis of microwave measurements collected by ground-based radiometers at Dome C during the DOMEX experiments reveals that ice-sheet parameter-profiles have a significant impact on the microwave emission even at low frequencies. In order to assess this observation, a theoretical analysis of microwave emission was carried out using the multilayer dense medium radiative transfer theory under the quasi-crystalline approximation with coherent potentials and ice-sheet geophysical-parameter profiles (i.e., temperature, density, layering, and grain size) collected in the Dome C area. The electromagnetic model was used to fit the angular distribution of microwave observations collected at C- and L-bands at Dome C. The analysis identifies the variability in the snow density vertical profile as a major factor in determining the microwave signature of the snow emission at both L- and C-bands. A secondary role is played by the snow grain radius profile that appreciably influences C-band.

The retrieval and monitoring of vegetation parameters from COSMO-SkyMed images

The capability of COSMO-SkyMed in estimating vegetation biomass has been investigated in this paper. SAR data from COSMO-SkyMed were collected on two agricultural areas in Italy in 2010 at different dates during the vegetation cycle. The performances of X-band data have been compared with accurate ground truth measurements of soil and vegetation carried out simultaneously to satellite passes. Experimental data have been compared with model simulations obtained with a discrete element radiative transfer model. Moreover, an inversion algorithm, based on an Artificial Neural Network and trained by using AIEM and the radiative transfer model, has been applied to retrieve the plant water content of wheat and sunflower crops and to generate the corresponding plant water content maps.

Effect of forests on the retrieval of snow parameters from backscatter measurements

Abstract In preparation for the CoReH2O satellite mission, one of the three missions selected for scientific and technical feasibility studies within the Earth Explorer Programme of the ESA, experimental and theoretical studies have been under way in order to improve methods for the retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from microwave backscattering measurements. ARTT model capable of simulating scattering from a snow- covered vegetated terrain was developed and implemented to study the sensitivity to snow and vegetation parameters. A procedure for correcting the vegetation effect in the SWE retrieval algorithm has been suggested.

Observations and Simulation of Multifrequency SAR Data Over a Snow-Covered Boreal Forest

A significant part of the Earth affected by seasonal snow is covered by forest. Moreover, the presence of forest modifies the snow accumulation and its metamorphism during the winter season. Recent studies, which were carried out within the framework of ESAs CoReH2O Phase-A mission, demonstrate that multifrequency SAR data are able to quantify the amount of snow mass on land surfaces and or glaciers. On the other hand, the presence of forest has a significant impact on the propagation of the radar signal, depending on its structure, biomass, water content, and cover fraction. In particular, for dense forest scattering of vegetation strongly hides the signal from snow, and consequently, compromises the sensitivity to snow parameters. Within the development of the missions snow water equivalent (SWE) retrieval algorithm, a method to compensate the vegetation effect, and then to retrieve snow in sparse forested areas, was implemented. The method is based on the development of an e.m. model for simulating the backscattering of a snow-covered vegetated terrain and the availability of some ancillary data about forest characteristics. Model description and validation using real airborne and space-borne SAR data collected over a boreal test site in Finland are presented here. The use of the developed model in the SWE retrieval algorithm is also presented.

The Effect of Boreal Forest Canopy in Satellite Snow Mapping—A Multisensor Analysis

Satellite-based snow-cover monitoring is performed using optical, synthetic aperture radar (SAR), and passivemicrowave sensors. Effects of forest canopy on the observed signal need to be considered with all of these sensor types. Various models describing the interaction of electromagnetic radiation with forest canopy have been developed, but many of these are overly complex with high computational and ancillary data requirements. However, for retrieval purposes, simple models are preferred. This work aims at increasing the understanding of the effect of forest canopy on remote sensing observations of snow-covered terrain for both microwave and optical regimes and at quantifying the capability of simple zeroth-order models in simulating these effects. To achieve these goals, a spatial analysis of optical, SAR, and passive-microwave remote sensing data in the northern boreal forest region was performed. Model parameters for vegetation transmissivity as well as the properties of the underlying surface were optimized by utilizing lidar-ranging- and Landsat-based simplified proxy parameters describing forest canopy closure and stem volume. The results demonstrated that despite using these relatively simple proxies, a zeroth-order model can accurately estimate the extinction of electromagnetic signals in a forest, particularly for passive microwave and optical data. The SAR model successfully estimated the median of the observations, but larger scatter of the observations was reflected by a higher root mean square error and lower correlation between models and observations. Due to both good estimation accuracy and simplicity, the presented models can be considered to be applicable in existing snow retrieval algorithms.

HydroCosmo: The Monitoring of Hydrological Parameters on Agricultural Areas by using Cosmo- SkyMed Images

Abstract In this paper, the results of an experiment carried out for exploiting the capabilities of X-band Cosmo-SkyMed data in the monitoring of soil and vegetation characteristics are summarized. SAR data have been collected in two agricultural areas in Italy and compared with ground truth measurements of soil and vegetation parameters. A rather good sensitivity to vegetation features, biomass and the moisture of bare or slightly vegetated soils has been confirmed. On bare surfaces the effect of surface roughness was significant, as expected, due to the high observation frequency. Model simulations have also been performed for better explaining the backscattering response to soil moisture at this frequency. The different backscattering response according to vegetation types, which has already been observed at C-band, has been confirmed at X-band, too. The absorption due to thin vertical stems was observed on wheat crops, whereas sunflower showed a prevalent scattering behavior due to the large circular leaves.

The potential of multi-temporal Cosmo-Skymed SAR images in monitoring soil and vegetation

The results of an experiment carried out in Italy for exploiting the capabilities of X-band SAR in the monitoring of soil and vegetation characteristics are summarized in this paper. Data from X-band Cosmo-Skymed mission have been collected in two agricultural areas and compared with C-band data of ENVISAT/ASAR and with ground truth measurements. In general, a certain sensitivity to vegetation biomass and to moisture of bare soils has been found.

L-band characterization of Dome-C region using ground and satellites data

In recent decades, with the development of low-frequency missions such as SMOS and Aquarius, which have a large antenna, the need has arisen to find stable areas for the external calibration of L-band radiometers. “Cold sky” and “calm ocean” are routinely used as low reference temperatures, and Antarctica, in particular the East Antarctic Plateau, has been investigated in recent years as a potential candidate for higher reference temperatures. The reason for this interest lies in its geographical location (it can be seen several times a day by polar-orbiting satellites), as well as in the size, structure, spatial homogeneity, and thermal stability of this area. In particular the area of Dome-C, where the Italian-French base is located, was monitored in the past years using ground based radiometer and satellite data. Data acquired in new experiment, started in 2012, are described in the present study together to an analysis of SMOS data collected in the same area. The results pointed out that the brightness temperature over that region is very stable both in space and time and have individuated a large area able to contain several footprints of space-borne radiometers and thus is suitable for cross calibration between the sensors.

A pre-operational algorithm for the retrieval of snow depth and soil moisture from AMSR-E data

This work deals with mapping snow water equivalent as well as soil moisture at low resolution from multifrequency microwave radiometers. The algorithm developed and implemented in this work produces the spatial distribution at regional scale of snow depth (SD) and of soil moisture (SMC) of snow free areas by using the brightness temperatures of the Advanced Multifrequency Scanning Radiometer (AMSR-E).

Evaluation of vegetation effect on the retrieval of snow parameters from backscattering measurements: A contribution to CoReH2O mission

In preparation of the satellite mission CoReH2O, one of the three missions selected for scientific and technical feasibility studies within the Earth Explorer Programme of the European Space Agency, experimental and theoretical studies started in order to investigate backscatter properties of snow covered terrain and improve the methods for retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from backscattering measurements. First a radiative transfer model, able to simulating scattering from a vegetated snow-covered terrain was developed and implemented. Lastly, a sensitivity analysis on snow and vegetation parameters was conducted for coniferous forest. Results confirm that with increasing biomass the sensitivity to SWE strongly decreases. Moreover when biomass is in the 0–150 m3/ha range a procedure to correct the vegetation effect in the SWE retrieval algorithm is suggested