Simonetta Paloscia

The potential of multifrequency polarimetric SAR in assessing agricultural and arboreous biomass

Polarimetric radar data collected by AIRSAR and SIR-C over agricultural fields, forests, and olive groves of the Italian Montespertoli site are analyzed. The objective is to investigate the radar capability in discriminating among various vegetation species and its sensitivity to agricultural and arboreous biomass. Results indicate that a combined use of P(0.45 GHz) and L- (1.2 GHz) bands allows one to discriminate between agricultural fields and other targets, while a combined use of L- and C- (5.3 GHz) bands allows the authors to discriminate within agricultural areas. To monitor biomass, P-band gives the best results for forests and olive groves, L-band appears to be good for crops with low plant density (m/sup -2/), while for crops with high plant density, both L- and C-bands are useful. The availability of crosspolarized data is important for both classification and biomass retrieval.

A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM/I satellites

The sensitivity of microwave emission at different frequencies to soil moisture in bare and vegetated soils has been investigated using experimental data. Since the best frequency for the measurement of soil moisture (L-band) is absent in current satellite sensors, it is necessary to seek alternative solutions. An algorithm is proposed for the retrieval of soil moisture based on the sensitivity to moisture of both the brightness temperature and the polarization index at C-band, one that is able to correct for the effect of vegetation by means of the polarization index at X-band. The algorithm has been tested by using experimental data collected with airborne microwave radiometers on agricultural areas and validated by using the data sets of special sensor microwave/imager (SMM/I) and scanning multichannel microwave radiometer (SMMR). These research activities are planned in view of coming new satellites: AQUA (NASA) and ADEOS-II (NASDA), which will be launched by the end of 2001. These will have new generation microwave radiometers (AMSR-E and AMSR) onboard, which show much better characteristics with respect to the previous sensors, in particular an enhanced spatial resolution.

Soil Moisture Estimates From AMSR-E Brightness Temperatures by Using a Dual-Frequency Algorithm

This paper investigates the possibility of estimating the soil moisture content (SMC) on a global scale from dual-frequency (C- and X-bands) microwave data of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Because some anomalous behavior was occasionally found in AMSR-E C- and X-band data, a calibration check compared the AMSR-E data with measurements from the SSM/I sensor over two reference targets, namely a Russian evergreen forest and the sea surface, both of which have already been studied in the past. The algorithm for retrieving soil moisture uses both the brightness temperature at C-band in horizontal polarization and the polarization index at X-band for correcting the effects of vegetation. This algorithm is based on a simplified radiative transfer (tau-omega) model, which has been inverted by using the Nelder-Mead iterative minimization method. The algorithm was validated with microwave data collected on two sites during the Microwave Alpine Soil Moisture Experiment 2002 (MASMEx02) and the Soil Moisture Experiment 2002 (SMEX02), respectively. The first site, in Italy, was characterized by natural vegetation covers, whereas the second site, in Iowa (U.S.), was covered primarily in agricultural crops. In general, the soil moisture estimated by the algorithm from AMSR-E data and the SMC measured on the ground were in good agreement with each other in both sites, and five classes of soil moisture were easily identified

Sensitivity to microwave measurements to vegetation biomass and soil moisture content: a case study

A comparative evaluation of the potential of active and passive microwave sensors in estimating vegetation biomass and soil moisture content is carried out. For this purpose, experimental data collected on an agricultural area by airborne scatterometers and radiometers during the AGRISCATT and AGRIRAD 1988 campaigns have been used. The results show that both microwave backscattering and emission are sensitive to vegetation biomass over a wide frequency range. Multifrequency observations seem to offer good probabilities for separating wide leaf from small leaf herbaceous crops, and for detecting different growth stages. Low frequency data (L band) at a steep incidence angle (10 degrees ) confirm that both the backscattering coefficient and the normalized temperature are correlated and sensitive to soil moisture content. >

Airborne GNSS-R Polarimetric Measurements for Soil Moisture and Above-Ground Biomass Estimation

Soil moisture content (SMC) and above-ground biomass (AGB) are key parameters for the understanding of both the hydrological and carbon cycles. From an economical perspective, both SMC and AGB play a significant role in the agricultural sector, one of the most relevant markets worldwide. This paper assesses the sensitivity of Global Navigation Satellite System (GNSS) reflected signals to soil moisture and vegetation biomass from an experimental point of view. For that, three scientific flights were performed in order to acquire GNSS reflectometry (GNSS-R) polarimetric observations over a wide range of terrain conditions. The GNSS-R data were used to obtain the right-left and right-right reflectivity components, which were then georeferenced according to the transmitting GNSS satellite and receiver positions. It was determined that for low-altitude GNSS-R airborne platforms, the reflectivity polarization ratio provides a highly reliable observable for SMC due to its high stability with respect to surface roughness. A correlation coefficient of 0.93 and a sensitivity of 0.2 dB/SMC (%) were obtained for moderately vegetated fields with a surface roughness standard deviation below 3 cm. Similarly, the copolarized reflection coefficient shows a stable sensitivity to forest AGB with equal to 0.9 with a stable sensitivity of 1.5 dB/(100 t/ha) up to AGB values not detectable by other remote sensing systems.

Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture

The use of Global Navigation Satellite Systems (GNSS) signals for remote sensing applications, generally referred to as GNSS-Reflectometry (GNSS-R), is gaining increasing interest among the scientific community as a remote sensing tool for land applications. This paper describes a long term experimental campaign in which an extensive dataset of GNSS-R polarimetric measurements was acquired over a crop field from a ground-based stationary platform. Ground truth ancillary data were also continuously recorded during the whole experimental campaign. The duration of the campaign allowed to cover a full crop growing season, and as a consequence of seasonal rains on the experimental area, data could be recorded over a wide variety of soil conditions. This enabled a study on the effects of different land bio-geophysical parameters on GNSS scattered signals. It is shown that significant power variations in the measured GNSS reflected signals can be detected for different soil moisture and vegetation development conditions. In this work we also propose a technique based on the combination of the reflected signal’s polarizations in order to improve the integrity of the observables with respect to nuisance parameters such as soil roughness.

Airborne multifrequency L- to Ka-band radiometric measurements over forests

Microwave radiometric measurements using airborne instruments in a frequency range from L- to Ka-band were carried out over six broad-leaved and one coniferous forest stands in Tuscany, Italy. Ground measurements of the main tree parameters were performed on the same stands. The analysis of the collected data indicated that the use of microwave emission at the highest frequencies makes it possible to identify some forest types, whereas L-band emission is more closely related to tree biomass. The relationships between emission and some significant tree parameters such as leaf area index, basal area, woody volume, and crown transparency are presented and discussed. The significant relationship between L-band emission and woody volume is further analyzed by means of a first-order radiative transfer model.

The potential of C- and L-band SAR in estimating vegetation biomass: the ERS-1 and JERS-1 experiments

The sensitivity of backscattering coefficient, measured by ERS-1 and JERS-1 radars, to vegetation biomass is discussed and compared with the best results achieved using multifrequency polarimetric JPL-AIRSAR data. Experimental results show that measurements with JERS-1/L-band and ERS-1/C-band SAR provide the means for detecting vegetation growth. In particular, the C-band signal of ERS radar was found to be very well correlated to forest woody volume.

Microwave emission from dry snow: a comparison of experimental and model results

Field measurements of microwave emission from snow-covered soil were carried out in 1996, 1997, and 1999 on the Italian Alps using a three-frequency dual polarized microwave system. At the same time, nivological time measurements were carried out using standard methods and an electromagnetic contact probe. Collected data confirmed the possibility of separating wet from dry snow and of estimating the water equivalent of dry snow. Simulations performed by means of a model based on the dense medium radiative theory (DMRT) were able to reproduce experimental data very well.

The SIR-C/X-SAR experiment on Montespertoli: sensitivity to hydrological parameters

Multi-frequency and multi-temporal polarimetric SAR measurements, carried out during SIR-C/X-SAR missions over the Montespertoli area have been analysed and compared with data collected at the same frequency and polarization, but at different dates, with the NASA/JPL AIRSAR. This paper presents an analysis of the achieved results aiming at evaluating the contribution of SAR data for estimating some geophysical parameters which play a significant role in hydrological processes and in particular soil moisture and roughness. The study has pointed out that in the scale of surface roughness typical of agricultural areas, a co-polar L-bandsensor gives the highest information content for estimating soil moisture and surface roughness. The sensitivity to soil moisture and surface roughness for individual fields is rather low since both parameters affect the radar signal. However, considering data collected at different dates and averaged over a relatively wide area that includes several fields, the correlation to...