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Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA‐ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation. A permanent, global, in situ, site‐based forest biomass reference measurement system relying on ground data of the highest possible quality is therefore needed. Here, we have assembled a list of almost 200 high‐quality sites through an in‐depth review of the literature and expert knowledge. In this study, we explore how representative these sites are in terms of their coverage of environmental conditions, geographical space and biomass‐related forest structure, compared to those experienced by forests worldwide. This work also aims at identifying which sites are the most representative, and where to invest to improve the representativeness of the proposed system. We show that the environmental coverage of the system does not seem to improve after at least the 175 most representative sites are included, but geographical and structural coverages continue to improve as more sites are added. We highlight the areas of poor environmental, geographical, or structural coverage, including, but not limited to, Canada, the western half of the USA, Mexico, Patagonia, Angola, Zambia, eastern Russia, and tropical and subtropical highlands (e.g. in Colombia, the Himalayas, Borneo, Papua). For the proposed system to succeed, we stress that (1) data must be collected and processed applying the same standards across all countries and continents; (2) system establishment and management must be inclusive and equitable, with careful consideration of working conditions; and (3) training and site partner involvement in downstream activities should be mandatory. [ABSTRACT FROM AUTHOR]

The variability of C-band one-day tandem coherence measurements of forest is analyzed both statistically and with the aid of a soil-vegetation-atmosphere transfer model coupled to models for dielectric, backscattering coefficient, and coherence. Coherence depends strongly on both moisture and wind conditions. The dependence between coherence and moisture fluctuations in the soil and canopy is simulated using a simplified coherence model neglecting canopy coherence; trends are similar to those observed in measured coherence, but the range of variability observed in the satellite data is underestimated. Improved consistency with the data is achieved by using empirical estimates of canopy coherence derived from mature forest, but still with underestimated variability. The canopy coherence values cannot be predicted from the environmental model, and anomalous observations prevent the formulation of a reliable empirical predictor based on weather data; this could potentially be improved if higher time resolution wind data were made available. The study also suggests that canopy dielectric can vary rapidly in daylight, and that current models for dielectric may be inadequate to capture the effect of this behavior on coherence. Index Terms--Coherence, dielectric, dynamic, forest, multitemporal, synthetic aperature radar (SAR), vegetation.

We present results from experiments carried out in the ground-based synthetic aperture radar (GB-SAR) facility at the University of Sheffield to ascertain the role of polarimetric interferometry in crop height retrieval. To this end, a mature wheat canopy, grown in outdoor conditions, was reassembled inside the GB-SAR chamber and imaged at C-band using a two-dimensional scan. This allowed fully polarimetric tomography and interferometry. Interferometry using the VV, HH, and VH polarization states shows that the HH and VH interferograms retrieve a height close to the top of the soil layer for all angles of incidence considered, whereas the height retrieved from the VV interferogram increases with angle of incidence. The use of a Pauli basis gives poor results, due to the different location of the scattering phase centers in the VV and HH channels. The use of arbitrary polarization states shows that the top of the soil can be very accurately estimated using left-circular polarization, whereas, for angles of incidence close to 45[degrees], a polarization state similar to VV can be used to retrieve the top of the canopy; hence crop height can be recovered as the difference of these two interferometric heights. Polarimetric coherence optimization techniques are also studied. Unconstrained coherence optimization gives very unstable results, due to the small number of available samples. Constrained optimization results in stable retrieved heights, and the retrieved polarization states agree well with the polarization synthesis results. Index Terms--Coherence optimization, indoor SAR, synthetic aperture radar (SAR), vegetation monitoring.

Radiative transfer models have been widely used to interpret the radar backscatter from forested areas. Most of these models are based on an iterative solution of the radiative transfer equation, usually solved up to first or second order, thus taking into account single and double scattering. Although this method leads to results agreeing well with copolarized backscatter measurements, it produces less accurate estimates for horizontal-vertical (HV) polarization. This paper presents a radiative transfer backscatter model that accounts for multiple scattering by using the discrete ordinate and eigenvalue method applied to a layered medium. Using parameters derived from an architectural tree model, calculations at C- and L-band are compared with HV data acquired for a maritime pine forest in the southwest of France during the Spaceborne Imaging Radar-C missions. Good agreement is found at C-band for all values of forest biomass, and reasonable agreement at L-band for high biomass, when the soil backscatter plays a minor role. For low biomass, the L-band modeling is inadequate because of difficulties in estimating the soil backscatter. Comparison with calculations from a first-order radiative transfer model shows that multiple scattering is significant, especially at C-band. Index Terms--Cross polarization, discrete ordinate method, forest biomass, radiative transfer modeling, synthetic aperture radar (SAR).

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.

Several proposed near-future spaceborne radar missions, such as the Advanced Land Observing Satellite (ALOS) and TerraSAR, will include an L-band instrument. At such low frequencies, the Faraday rotation in the ionosphere, which rotates the polarization plane of the radar signal, becomes an important consideration in instrument design. In this paper, both simple analytic approximations and numerical models are used to derive likely values of Faraday rotation and determine their impact on polarimetric imagery and derived products. One-way rotations exceeding 5[degrees] are likely to significantly reduce the accuracy of geophysical parameter recovery, such as forest biomass. On average, Faraday rotation can be neglected at solar minimum, but correction methods are needed at other times of the solar cycle and under disturbed conditions. Methods for implementing such corrections based on estimates of the Faraday rotation and prerotation of the transmitted signal are described. Index Terms--Faraday rotation, image quality, Phased Array Type L-band Synthetic Aperture Radar (PALSAR), synthetic aperture radar (SAR), TerraSAR.

Polarimetric X- and C-band measurements by the University of Sheffield ground-based synthetic aperture radar (GB-SAR) indoor system provide three-dimensional images of the scattering processes in wheat canopies, at resolutions of around a wavelength (3-6 cm). The scattering shows a pronounced layered structure, with strong returns from the soil and the flag leaves, and in some cases a second leaf layer. Differential attenuation at horizontal(H) and vertical (V) polarization, due to the predominantly vertical structure of the wheat stems, gives rise to marked effects. At both C and X bands, direct return from the canopy exceeds the soil return at large incidence angles for VV polarization, but is comparable to or less than the soil return in all other cases. At HV, the apparent ground return is probably due to a double-bounce mechanism, and volume scattering is never the dominant term. Direct sensing of the crop canopy is most effective at X band, VV, and large incidence angles, under which conditions the return is dominated by the flag leaf layer. Field measurements with the outdoor GB-SAR system suggest, however, that for sensitivity to biomass and reduced susceptibility to disturbances by rainfall, a two-channel C-band system operating at a medium range of incidence angles is preferred. Index Terms--Agriculture, backscatter modeling, synthetic aperture radar (SAR).

An explicit form of the linear multichannel synthetic aperture radar (SAR) intensity filter, which preserves radiometry while optimally reducing speckle is derived, together with a compact expression for the theoretical gain in equivalent numbers of looks (ENLs). The filter can be applied to mixed data types, which is demonstrated using a combination of ERS and JERS satellite data, and confirms the filter performance predicted by the theory. Tests indicate that a simplified form of the filter, which neglects correlation between images, gives an ENL only slightly less than optimal, while being much easier to implement. Exact analysis of the effect of estimating filter weights shows that the linear increase in ENL with the number of images predicted for the ideal filter does not occur. In practice, the ENL is affected by the window size used to estimate the weights and saturates as the number of images increases. An efficient recursive form of the filter is described, which is most naturally applied to multitemporal data for the practically important case where the current image is uncorrelated with previous images in a data sequence. Index Terms--Agriculture, forestry, multitemporal filtering, speckle reduction.