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Toward the end of A Man in Love, the second book in the fabulous, formidable My Struggle saga by Karl Ove Knausgârd, I read this line: 'My angry outbursts were [...]

I suppose they think they'll always feel like clipping the first jasmines of spring. Filling the house with flowers. Buying new clothes. I suppose they think they'll always imagine themselves [...]

I don't always have things to say. When that happens I sometimes read Elizabeth Bishop. And sooner or later I always arrive back at that portentous poem, 'One Art,' translated [...]

The objective of this paper is to carry out a systematic investigation about the sensitivity of radar to maize crop growth and soil moisture by considering a wide range of frequencies and angles and all linear polarizations. We show the results of a correlation study carried out on the data collected on a maize field at Suberg, in the Swiss region named Central Plain, by the multifrequency RAdio ScAtteroMeter (RASAM). This agricultural field was monitored over a long period of time at a wide range of frequencies and observation angles so that the correlation between the backscattering and crop height and the biomass and soil moisture was studied under several plant and observation conditions. Moreover, we describe some recent refinements applied to the vegetation scattering model developed at Tor Vergata University, Rome, Italy, and we evaluate the accuracy of extended comparisons between model outputs and RASAM signatures. The Tor Vergata model is finally applied to give a theoretical basis to the experimental correlation findings. Index Terms--Biomass, crops, modeling, radar, soil moisture.

This paper assess the possibilities of the synthetic aperture radar (SAR) sensors currently in orbit for the maize monitoring defining the configurations (polarization and incidence angles at C-band) maximizing the sensitivity to plant growth and reducing the impact of the soil moisture on the signal. Temporal evolution of the signal was simulated in all the possible configurations using the radiative transfer model developed by the University of Rome 'Tor Vergata.' The input parameters came from an intensive field campaign providing a detailed description of maize crop over the Belgian Loamy site all along the 2003 growing season. The model was validated for vertical (VV) and horizontal (HH) polarization using ERS, ENVISAT, and RADARSAT observations. The C-band SAR signal in single polarization was found to be sensitive to crop growth till the leaf area index (LAl) reached 4.6 [m.sup.2]/[m.sup.2], while the soil moisture influenced the signal for sparsely vegetated fields (LAI < 2.7 [m.sup.2]/[m.sup.2]). Dual-polarizations indexes were found sensitive to maize growth and less sensitive to soil moisture variations. The VV/VH polarization ratios computed from signal recorded at high incidence angle (35[degrees] to 45[degrees]) could be considered to assess the crop growth till LAI reached 4.9 [m.sup.2]/[m.sup.2] with low sensitivity to soil moisture. At the beginning of growth, the emergence of maize plants could be detected using the copolarized ratio (VV/HH) computed at low incidence angle. These indexes allow discriminating various crop conditions at a given date between fields of a same region. Index Terms--Dual polarization, maize growth, synthetic aperture radar (SAR) remote sensing, soil moisture.

Several efforts, aimed at developing and refining crop backscattering models, have been done during the last years. Although important advances have been achieved, it is recognized that further work is required, both in the electromagnetic characterization of single scatterers and in the combination of contributions. This work is focused on the description of leaf geometry and of the internal structure of stems. Recently developed routines, able to model the scattering cross sections of curved sheets and hollow cylinders, are adopted for this purpose and run within the multiple-scattering model developed at the University of Rome 'Tor Vergata.' Input parameters are taken from experimental campaigns. In particular, ground data collected over a maize field at the Central Plain site in 1988, over wheat and maize fields at the Loamy site in 2003, and over wheat fields at the Matera site in 2001 and 2003 are considered. The multitemporal backscattering coefficients at C-band are simulated. The results obtained under different assumptions are compared to each other, and with C-band radar signatures collected over the same fields. The influence of some critical factors, affecting crop backscattering, is discussed. It is demonstrated that a more detailed scatterer characterization may improve the model accuracy, especially in the case of hollow stems. Index Terms--Crop backscattering, curved sheet, hollow cylinder, model simulations.

In this work, multitemporal synthetic aperture radar (SAR) data in conjunction with an electromagnetic (EM) model and a vegetation growth model were used to monitor and explain burn-regrowth events of junco vegetation in a wetland environment. The data used were from Radarsat-1, ENVISAT Advanced Synthetic Aperture Radar (ASAR), and European Remote Sensing 2 (ERS-2) temporal series. The EM model is based on radiative transfer theory and describes junco vegetation as a set of vertical dielectric cylinders on a flat flooded surface. It was used, together with the vegetation growth model, to predict the temporal evolution of the radar response during a burn-regrowth event. This simulation was compared with the ERS-2 vertical (VV) data. It was observed a 'bell-shaped' temporal trend that was confirmed by the simulated data with a mean error of 2.5 dB. Additionally, in view of current and future ENVISAT ASAR Alternating Polarization Mode Precision data, the horizontal (HH) SAR temporal response was also simulated giving as a result strong differences between simulated HH and VV temporal trends. These differences are in good agreement with the ones observed between Radarsat-1 HH and ERS-2 VV SAR data acquired at close dates and also with the same differences observed between HH and VV ENVISAT ASAR data. Electromagnetic modeling results provide a sound theoretical interpretation of these observations. Index Terms--Electromagnetic (EM) models, radar, wetlands.

This paper describes an algorithm aimed at monitoring the soil moisture and the growth cycle of wheat fields using radar data. The algorithm is based on neural networks trained by model simulations and multitemporal ground data measured on fields taken as a reference. The backscatter of wheat canopies is modeled by a discrete approach, based on the radiative transfer theory and including multiple scattering effects. European Remote Sensing satellite synthetic aperture radar signatures and detailed ground truth, collected over wheat fields at the Great Driffield (U.K.) site, are used to test the model and train the networks. Multitemporal, multifrequency data collected by the Radiometer-Scatterometer (RASAM) instrument at the Central Plain site are used to test the retrieval algorithm. Index Terms--Crops, neural networks, radar, retrieval, scattering model.

The microwave model developed at the Tor Vergata University is used to simulate the emissivity of forests, in order to study the performance of an L-band spaceborne radiometer, similar to that carried by the Soil Moisture Ocean Salinity mission. The model is first validated, and the importance of a correct vegetation growth parametrization in the modeling procedure is pointed out. This model is also used to calibrate a simple zero-order radiative transfer model, since simple models have been recognized to be useful in retrieval applications at a global scale. In this paper, we show that although a zero-order approximation cannot be directly used for forests, a simple formulation may be applied, provided the albedo and the optical depth are defined as equivalent parameters. Index Terms--Emission model, forests, microwave radiometry, soil moisture.