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As the 7th Earth Explorer Mission within the ESA Earth Observation Program, BIOMASS will be the first spaceborne P-band polarimetric interferometric SAR (PolInSAR) mission, dedicated to global forest remote sensing. Compared with airborne PolInSAR, BIOMASS PolInSAR faces several intrinsic limitations, including the reduced number of baselines, low bandwidth of 6 MHz, and the 3-day repeat-pass acquisition mode. In this study, the capabilities of three-baseline PolInSAR in BIOMASS configuration and the spaceborne system-induced impacts are systematically evaluated. First, the BIOMASS data were simulated using the airborne P-band SAR acquisitions collected over two different tropical forests in Paracou, French Guiana, and Mondah, Gabon. Second, the forest height was retrieved using a three-baseline algorithm based on polarimetric coherence optimization with multi-baseline joint diagonalization. Finally, the impacts of spaceborne PolInSAR were quantified and analyzed. The results show that the performance of PolInSAR inversion in the spaceborne configuration decreases compared to that of the original airborne data. However, the three-baseline method still yields acceptable results, with a root-mean-square error ranging from 4.92 to 6.07 m and a correlation coefficient (R2) from 0.32 to 0.85, within hectare-scale forest height statistics. This study demonstrates that the limited bandwidth of BIOMASS has a certain impact on refined forest structure parameter retrieval, while the three-baseline PolInSAR method remains effective for large-scale forest mapping, with accuracy meeting the design requirements of the BIOMASS mission.

With the continuous development of electromagnetic detection systems, the working frequency of radar gradually expands towards the low-frequency band such as P- and L-band, and the low-frequency horn antenna has also attracted more and more attention. Given the problems of miniaturization, lightweight and ultra-wideband design of low-frequency horn antenna, this paper presents the optimal design for the feed balun, ridge curve, back-feed cavity and sidewall of the traditional horn antenna, and proposes a performance-enhanced double-ridged horn antenna covering 0.21-2.3 GHz. In the entire working band, the antenna has stable radiation patterns and good port-matching characteristics; its VSWR is less than 2 and the main lobes of patterns do not split or deteriorate. The proposed horn antenna can be used as a standard calibration or measurement antenna in antenna or material measurement systems. [ABSTRACT FROM AUTHOR]

FeSiAl alloys with a composition of Fe-9.6Si-5.4Al, also known as Sendust alloys, present the unique potential to exhibit efficient electromagnetic wave absorption (EMA) in the P-band. However, the electromagnetic properties of this type of alloy are highly sensitive to the shape, microstructure, and microchemistry, which then inspire the current research. The evolution of the microstructure/microchemistry of FeSiAl particles was systematically revealed in a single particle scale for the first time, and the resulting influence on the electromagnetic properties was investigated. Recrystallization occurs in the annealing process on FeSiAl particles and the oxide films on the surface evolve evidently when annealed in 5%H2/Ar or air, which can conduce improved electromagnetic properties. The FeSiAl particles annealed in 5%H2/Ar present efficient EMA in the P-L band while those in air contribute to high reflection loss. This work indicates the feasibility of achieving a high and adjustable EMA efficiency in the P-L band through microstructure and microchemistry tailoring.

In this article, we use the analytical Kirchhoff solution (AKS) and numerical Kirchhoff approach to study the bistatic scattering field ($\gamma $) from mountain terrain at P-band frequency. The study area is Grand Mesa, Colorado, USA, and the properties of land surface roughness are extracted from airborne lidar surveys. The bistatic scattering coefficient $\gamma $ of variance fields, denoted by${\gamma }_v$, for several cases of radar resolutions over a 3.6 km by 3.6 km area are calculated at various scattering azimuth angles. Based on the lidar measurements, the land surface is decomposed into ${f}_2 + {f}_3$, where ${f}_3$ is 30 m of deterministic planar patches to approximate the coarse topography and ${f}_2$ is modeled by random rough surfaces with correlation functions. Surface roughness statistics derived from the Lidar data give a typical root mean square height of 0.07 m and a correlation length of 3.6 m for ${f}_2$. The mean values of slopes of ${f}_3$ are 1.3° and 0° with a standard deviation of 1° each, respectively in the x and y directions. Simulations using AKS show that the values of bistatic scattering coefficients for the variance of scattered fields can reach above 10 dB over a range of azimuth angles ${\phi }_s$ in the vicinity of the specular direction. Even in mountainous regions, the value of the ${\gamma }_v$ around the forward scattering direction is much larger than that for radar backscattering, and thus could support the use of a synthetic aperture radar concept based on signals of opportunity with data acquisition near the forward direction.

P-band radiometry has been demonstrated to have a deeper sensing depth than L-band, making the consideration of multilayer microwave interactions necessary. In addition, the scattering and phase interference effects are different at the P-band, requiring a reconsideration of the need for coherent models. However, the impact remains to be clarified, and understanding the validity and limitations of these models at both L- and P-bands is crucial for their refinement and application. Therefore, two general categories of microwave emission models, including two stratified coherent models (Njoku and Wilhite) and four incoherent models (conventional tau-omega model and three multilayer models being zero-order, first-order, and incoherent solution), were intercompared for the first time on the same dataset. This evaluation utilized observations of L- and P-bands radiometry under different land cover conditions from a tower-based experiment in Victoria, Australia. Model estimations of brightness temperature (TB) were consistent with measurements, with the lowest root mean square error (RMSE) at P-band V-polarization under corn (2 K) and the highest RMSE at L-band H-polarization under bare soil (13 K). Coherent models performed slightly better than incoherent models under bare soil (3 K less RMSE), while the opposite was true under vegetated soil conditions (1 K less RMSE). Coherent and incoherent models showed maximum differences (3 K at P-band and 2 K at L-band), correlating strongly with soil moisture variations at 0–10 cm. Findings suggest that coherent and incoherent models performed similarly; thus, incoherent models may be preferable for estimating TB at L- and P-bands due to reduced computational complexity.

Accurate estimation of forest aboveground biomass (AGB) is crucial for research on terrestrial carbon cycling and global climate change. In this study, we introduce an improved approach for estimating forest AGB combining P-band and X-band interferometric synthetic aperture radar (InSAR) data. Forest AGB was estimated by combining unbiased forest height and volume backscatter intensity. For forest height, a multilayer model and subaperture decomposition technology were used to remove the penetration bias of the X-band and reduce the effects of forest scatterers on the extraction of a pure understory terrain phase based on P-band, respectively. For volume backscatter intensity, a ground cancellation algorithm based on P-band InSAR was used to eliminate ground scattering contributions unrelated to forest AGB. The proposed method was validated using airborne P-band InSAR data and spaceborne X-band InSAR data gathered over the study area on the Saihanba Forest Farm in Hebei, China. The unbiased forest height and volume backscatter intensity had stronger correlations with forest AGB than estimates derived from unimproved features. The proposed method returned high-precision estimates of forest AGB with an accuracy of 83.73%, an improvement of 8.80% over an estimate derived from unoptimized features. Additionally, AGB estimates combined with forest height and backscatter intensity were greater than those based on a single feature, with the contribution of the former is greater than that of the latter.

This article investigated the possibility of remotely sensing the soil moisture profile in thawed soil from multi-angular dual-polarized brightness temperature (TB) observations at P-band frequencies of 750 MHz and 409 MHz using a modified Burke model. Moreover, it was found that an excellent agreement (coefficient of determination R2 = 0.999 and root-mean-square error (RMSE) no more than RMSE = 0.6 K) could be achieved between the Njoku coherent brightness temperature model and the modified Burke model by introducing a reflectivity from the air-soil interface that takes into account the phases of the multiple re-reflected waves in the underlying layers. Based on the modified Burke model, the depths from which apparent moisture and temperature could be retrieved in a dielectrically-inhomogeneous, non-isothermal soil were investigated, being approximately ten times less than the depth for which apparent soil temperature could be retrieved. In general, the thickness of the emitting layer depends on the TB look angle and polarization, along with the moisture and temperature profiles of the soil. It was also shown that due to the effect of the Brewster angle, the H-polarization of TB was twice as sensitive (4 K/1%) to changes in volumetric soil moisture than V-polarization (1.9 K/1%). Based on multi-angular (10°-50°) observations of TB at H- and V-polarizations, a method of moisture profile retrieval in the top 5–15 cm soil (depending on surface moisture) was proposed using an exponential fitting function, the parameters of which are found in the course of solving the inverse problem. A decrease in the sensing frequency from 750 MHz to 409 MHz makes it possible to increase the accuracy of soil moisture profiles retrieval by a factor of two, being from RMSE = 1.6% (R2 = 0.946) to RMSE = 0.85% (R2 = 0.982) in the top 15 cm layer of soil. The conducted investigation shows the promise of using P-band observations of TB for soil moisture profile retrieval. [ABSTRACT FROM AUTHOR]

The field of P-band (0.3–1 GHz) absorption has witnessed rapid development in metamaterial absorbers due to their exceptional designability and the absence of restrictions imposed by the one-fourth wavelength rule. In this study, we combined carbonyl iron powder (CIP) composites with a periodic structure composed of metal capacitive patterns and employed a genetic algorithm (GA) to optimize the electromagnetic parameters of the CIP substrate. By selecting the appropriate shape and material for the units of pattern based on transmission line theory, as well as regulating relevant structural parameters, we successfully designed an ultra-thin broadband metamaterial absorber for the P-band. Experimental results demonstrate that within the range of 0.3–0.85 GHz, the reflection loss of our absorber remains below −5 dB, with a maximum value of −9.54 dB occurring at 0.45 GHz. Remarkably, this absorber possesses a thickness equivalent to only 1/293 of its working wavelength. Then, we conducted analyses on electric field distribution, magnetic field distribution, and energy loss density. Our findings suggest that high-performance absorption in metamaterials can be attributed to λ/4 resonant or coupling effects between structural units or diffraction phenomena. This absorber offers several advantages, including broad low-frequency absorption capability, ultra-thin profile, and convenient fabrication process, thus providing valuable theoretical insights for designing metamaterial structures. [ABSTRACT FROM AUTHOR]

P-band radiometry has been demonstrated to have a deeper sensing depth than L-band, making the consideration of multilayer microwave interactions necessary. In addition, the scattering and phase interference effects are different at the P-band, requiring a reconsideration of the need for coherent models. However, the impact remains to be clarified, and understanding the validity and limitations of these models at both L- and P-bands is crucial for their refinement and application. Therefore, two general categories of microwave emission models, including two stratified coherent models (Njoku and Wilhite) and four incoherent models (conventional tau-omega model and three multilayer models being zero-order, first-order, and incoherent solution), were intercompared for the first time on the same dataset. This evaluation utilized observations of L- and P-bands radiometry under different land cover conditions from a tower-based experiment in Victoria, Australia. Model estimations of brightness temperature (TB) were consistent with measurements, with the lowest root mean square error (RMSE) at P-band V-polarization under corn (2 K) and the highest RMSE at L-band H-polarization under bare soil (13 K). Coherent models performed slightly better than incoherent models under bare soil (3 K less RMSE), while the opposite was true under vegetated soil conditions (1 K less RMSE). Coherent and incoherent models showed maximum differences (3 K at P-band and 2 K at L-band), correlating strongly with soil moisture variations at 0–10 cm. Findings suggest that coherent and incoherent models performed similarly; thus, incoherent models may be preferable for estimating TB at L- and P-bands due to reduced computational complexity. [ABSTRACT FROM AUTHOR]

Radio frequency interference (RFI) represents all unwanted signals detected by radio receivers of a telescope. Unfortunately, the presence of RFI is significantly increasing with the technological development of wireless systems around the world. For this reason, RFI measurement campaigns are periodically necessary to map the RFI scenario around a telescope. The Sardinia Radio Telescope (SRT) is an Italian instrument that was designed to operate in a wide frequency band between 300 MHz and 116 GHz. One of the receivers of the telescope is a coaxial cryogenic receiver that covered a portion of the P and L bands (i.e., 305–410 MHz and 1300–1800 MHz) in its original version. Although the receiver was used for years to observe bright sources with sufficient results, its sub-bands can be redesigned considering the most recently evolved RFI scenario. In this paper, the results of a RFI measurement campaign are reported and discussed. On the basis of these results, the new sub-bands of the L-P receiver, together with the design of the new microwave filter selector block of the SRT receiver, are presented. In this way, SRT will cover up to 120 MHz and 460 MHz of −3 dB bandwidth at the P-band (290–410 MHz) and L-band (1320–1780 MHz), respectively. The bands of these filters are selected to reject the main RFI with high levels of amplitude and optimize the estimated antenna temperature and sensitivity of the receiver during the research activities, such as pulsar observations, very long baseline interferometer applications and spectroscopy science. [ABSTRACT FROM AUTHOR]

As an emerging technique, P-band (0.3–1 GHz) may improve soil moisture remote sensing compared to L-band (1.4 GHz) Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, because of its greater moisture retrieval depth resulting from its longer wavelength. Consequently, a number of tower-based experiments were undertaken in VIC, Australia, to understand and quantify potential improvements. The study reported here has extended the evaluation of the tau-omega model to a scenario with a dense corn canopy whose vegetation water content (VWC) reached ~20 kg/m2, and compared the soil moisture retrieval performance at P- and L-band. Based on the locally calibrated parameters, the results from both the single-channel algorithm (SCA) and dual-channel algorithm (DCA) approaches presented a clear reduction in vegetation impact at the P-band compared to L-band. While the root-mean-square error (RMSE) for the P-band did not achieve the 0.04- $\text{m}^{3}/\text{m}^{3}$ target accuracy of SMOS and SMAP, i.e., 0.054 $\text{m}^{3}/\text{m}^{3}$ for the SCA and 0.074 $\text{m}^{3}/\text{m}^{3}$ for the DCA, this performance can be regarded as acceptable considering the extremely high VWC. In comparison, the RMSEs at L-band were larger than 0.1 $\text{m}^{3}/\text{m}^{3}$ for both the SCA and the DCA approaches. Additionally, DCA performed better in correlation coefficient and unbiased RMSE, while SCA performed better in RMSE at the P-band due to the larger bias when using DCA. Moreover, the calibrated vegetation parameters at the P-band were found to apply to broader conditions than those at the L-band, likely due to the reduced vegetation impact. [ABSTRACT FROM AUTHOR]

Due to its rapid deployment, high-flexibility, and high-accuracy advantages, the unmanned-aerial-vehicle (UAV)-based differential synthetic aperture radar (SAR) tomography (D-TomoSAR) technique presents an attractive approach for urban risk monitoring. With its sufficiently long spatial and temporal baselines, it offers elevation and velocity resolution beyond the dimensions of range and azimuth, enabling four-dimensional (4D) SAR imaging. In the case of P-band UAV-SAR, a long spatial-temporal baseline is necessary to achieve high enough elevation-velocity dimensional resolution. Although P-band UAV-SAR maintains temporal coherence, it still faces two issues due to the extended spatial baseline, i.e., low spatial coherence and high sidelobes. To tackle these problems, we introduce a multi-master (MM) D-TomoSAR approach, contributing three main points. Firstly, the traditional D-TomoSAR signal model is extended to a MM one, which improves the average coherence coefficient and the number of baselines (NOB) as well as suppresses sidelobes. Secondly, a baseline distribution optimization processing is proposed to equalize the spatial–temporal baseline distribution, achieve more uniform spectrum samplings, and reduce sidelobes. Thirdly, a clustering-based outlier elimination method is employed to ensure 4D imaging quality. The proposed method is effectively validated through computer simulation and P-band UAV-SAR experiment. [ABSTRACT FROM AUTHOR]

In this work a novel absorber that can operate simultaneously at the previous (P) and terahertz (THz) frequencies is proposed. This innovation features a single configuration composed of NiCuZnBi ferrite with periodic microstructure on the surface. In P band, the absorber achieves an absorption efficiency of more than 90 % (with a reflection loss of less than −10 dB) across the frequency range of 429.5 to 1000 MHz. This extremely low frequency absorption is solely attributed to the inherent magnetic loss of NiCuZnBi ferrite and is independent of the surface structure of the absorber. In the THz band, with this same absorber, a single layer of NiCuZnBi microstructure unit can achieve broad absorption range from 351.8 to 1200 GHz due to local energy loss caused by diffraction effects. More importantly, we have revealed the principle that increasing the number of NiCuZnBi microstructure unit layers is beneficial for broadening the THz absorption bandwidth. By designing stacked multi-layer structural units, we increased the absorption bandwidth of the device from 848.2 GHz for single-layer structures to 932.8 GHz for two-layer structures and 969.1 GHz for three-layer structures, respectively. The cross-band device design method proposed here makes it possible to develop electromagnetic absorbers that cover the P-band, THz band, and even more other frequency bands, thereby meeting the requirements of future applications such as multi-spectrum electromagnetic stealth and 6G communication. [ABSTRACT FROM AUTHOR]

Precision irrigation management and crop water stress assessment rely on accurate estimation of root zone soil moisture. However, only the top 5 cm soil moisture can be estimated using the two current passive microwave satellite missions, Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), which operate at L-band (wavelength of ∼21 cm). Since the contributing depth of the soil to brightness temperature increases with observation wavelength, it is expected that a P-band (wavelength of ∼40 cm) radiometer could potentially provide soil moisture information from deeper layers of the soil profile. Moreover, by combining both L- and P- bands, it is hypothesized that the soil moisture profile can be estimated even beyond their individual observation depths. The aim of this study was to demonstrate the potential of combined L-band and P-band radiometer observations to estimate the soil moisture profile under flat bare soil using a stratified coherent forward model. Brightness temperature observations at L-band and P-band from a tower based experimental site across a dry (April 2019) and a wet (March 2020) period, covering different soil moisture profile shapes, were used in this study. Results from an initial synthetic study showed that the performance of a combined L-band and P-band approach was better than the performance of using either band individually, with an average depth over which reliable soil moisture profile information could be estimated (i.e. with a target root mean square error (RMSE) of less than 0.04 m3/m3) being 20 cm for linear and 15 cm for second-order polynomial functions. Other functions were also tested but found to have a poorer performance. Applying the method to the tower-based brightness temperature achieved an average estimation depth of 28 cm (20 cm) and 5 cm (5 cm) during the dry and wet periods respectively when using a second-order polynomial (linear) function. These findings highlight the opportunity of a satellite mission with L-band and P-band observations to accurately estimate the soil moisture profile to as deep as 30 cm globally.

The upcoming BIOMASS mission will provide P-band repeat-pass PolInSAR data from space for the improved mapping of global biomass. PolInSAR technique has been widely validated with the potential to invert forest height and estimate forest aboveground biomass (AGB). However, the robustness of PolInSAR-based AGB estimation across different sites still lacks full evaluation, especially for those with a varied forest type, heterogeneity (varied growth ratio between cover and height), and topographic relief. In this study, we concentrated on backscatter decomposition and forest height inversion, and developed a robust AGB estimation method that can be applied to different sites. Two dense and closed tropical forest sites (Paracou and Nouragues) and one open and heterogeneous boreal forest site (Krycklan) were selected as the study areas, and the corresponding airborne PolInSAR, LiDAR, and ground measured AGB data were used for validation and analysis. Results show that ground backscatter has the strongest correlation with AGB in boreal forests, but this correlation cannot be transferred to the tropical forests. Only canopy volume backscatter is almost free from topographic influence, and its relationship with AGB across three sites can be formulated using one exponential equation, producing the best estimation accuracy, with R2 of 0.79 and RMSE of 61.5 tons/ha (relative RMSE of 20.0 %). Multi-baseline PolInSAR retrieved forest height with little bias in spite of the presence of temporal decorrelation. One power equation can be used to correlate PolInSAR forest height with AGB across three different sites, and LOO (leave-one-out) validation shows the R2 of 0.85 and RMSE of 51.8 tons/ha (relative RMSE of 16.9 %). However, the RVoG-inverted PolInSAR FH was found to mainly represent the top forest height for open and heterogeneous forests, which means PolInSAR FH (forest height) lacks consideration for forest horizontal structure (e.g. forest density). In contrast, volume backscatter better captured forest density, and the proposed AGB model that combines PolInSAR FH and volume backscatter further improved the AGB estimation accuracy, especially for open forests: the plot-scale validation from all three sites shows R2 was improved from 0.79 (volume backscatter) and 0.85 (PolInSAR FH) to 0.89, and RMSE decreased from 61.5 and 51.8 to 45.2 (relative RMSE of 14.7 %) tons/ha; for region-scale validation, R2 was improved from 0.77 and 0.83 to 0.89, and RMSE decreased from 64.2 (relative RMSE of 39.0 %) and 54.5 (34.5 %) to 48.1 (29.4 %) tons/ha.

The penetration capability of P-band radar waves through dense vegetation, along with the ability of tomography to separate the contributions of different layers in a vertical reflectivity profile, make P-band radar tomography a promising tool for digital terrain modeling in forested areas, specifically in dense tropical forests under which terrain topography remains poorly known. This paper aims to assess the overall quality of a digital terrain model (DTM) produced using tomographic processing of airborne P-band SAR imagery acquired during the TropiSAR campaign in French Guiana. Many quality descriptors are used to evaluate the quality of this DTM. Position and slope accuracies are computed based on a lidar DTM considered as the reference, and the impact of several parameters on these accuracies is studied, namely, slope, slope orientation, off-nadir angle and local incidence angle. The realism of the landforms is also studied according to geomorphological criteria. The results of this multicriteria accuracy assessment show the high potential of P-band SAR tomography in depicting the topography under forests, despite the intrinsic limitations related to the slant range geometry: the absolute elevation error is around 2 m; the slope is overestimated with an error of about 16°, mainly due to a processing artifact for which easy and direct solutions exist. Indeed, this error is equal to about 3° in flat artifact-free areas. These errors vary depending on the acquisition parameters and the local topography. The shapes are globally well preserved. These results are also discussed in the frame of the upcoming BIOMASS mission developed by the European Space Agency (ESA) and expected to be launched in 2024. [ABSTRACT FROM AUTHOR]

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This article proposes a closed-form asymptotic solution for the bistatic coherent scattering of a multilayered rough surface structure based upon its effective dielectric constant (EDC) in specular direction. The EDC is modeled by establishing an equivalence of the coherent scattering between the multilayered rough surface structure and a half-space homogeneous medium. The scattering solution is then solved using the scalar Kirchhoff approximation (SKA) method. This new method is referred to as the SKA-EDC method, and it is applied to analyze the sensitivity of the EDC and coherent reflectivity to bare soils with realistic parameters at P- and L-bands. The result indicates that EDC can give different responses to the soil moisture variations with respect to the coherent reflectivity, enabling the potentials of root-zone soil moisture retrieval. At incidence angle smaller than 35°, EDC gives the same value for both polarizations, and the coherent reflectivity can show a significant response to soil at depths <15–50 cm at 0.80 GHz and <5–15 cm at 1.57 GHz, depending on soil moisture. The simulation also demonstrates that subsurface roughness has a trivial effect on the EDC and coherent reflectivity for three rough surfaces separated by continuously dielectric profiles. Subsurface can, thus, be assumed to be flat for reducing uncertainty in soil moisture inversion algorithms when the subsurface roughness is unknown. [ABSTRACT FROM AUTHOR]

Temporal variations in synthetic aperture radar (SAR) backscatter over forests are of concern for any SAR mission with the goal of estimating forest parameters from SAR data. In this article, a densely sampled, two-year long time series of P-band (420 to 450 MHz) boreal forest backscatter, acquired by a tower-based radar, is analyzed. The experiment setup provides time series data at multiple polarizations. Tomographic capabilities allow the separation of backscatter at different heights within the forest. Temporal variations of these multipolarized, tomographic radar observations are characterized and quantified. The mechanisms studied are seasonal variations, effects of freezing conditions, diurnal variations, effects of wind, and the effects of rainfall on backscatter. An emphasis is placed on upper-canopy backscatter, which has been shown to be a robust proxy for forest biomass. The canopy backscatter was more stable than ground-level backscatter during nonfrozen conditions, supporting forest parameter retrieval approaches based on tomography or interferometric ground notching. Large backscatter variations during frozen conditions, which may be detected using cross-polarized backscatter observations, can result in large errors in forest parameter estimates. Diurnal backscatter variations observed during hot periods were likely connected to tree water transport and storage mechanisms. Backscatter changes were also observed during strong winds. These variations were small in comparison to the variations due to freeze-thaw and soil moisture changes and should not result in significant forest parameter estimation errors. The presented results are useful for designing physically based and semiempirical scattering models that account for temporal changes in scattering characteristics.

The spaceborne aperture radar (SAR) technique based on a combination of P-band signals of opportunity (SoOp) reflectometry with a sparse array of receivers at low earth orbits (LEOs) and transmit signals from the United States Navy's Mobile User Objective System operating on a geosynchronous altitude has been analyzed. The design focuses on the forward-looking geometry near the specular direction, which allows a high surface reflectivity, in order to obtain adequate signal-to-noise ratio (SNR) with a moderate receiving antenna gain. The sparse array is utilized to sharpen the across-track resolution and reduce the iso-range ambiguity. The formulation for match filtering and illustrations of point target response are presented. This work shows that an array of five to seven receivers is able to achieve an across-track resolution of about 200 m in the outer portion of swath and about 1 km in the center part of swath. The along-track resolution can reach 10 m or better due to the feasibility of a long dwell time for Doppler filtering. We find that the sparse array allows the reduction of the iso-range ambiguity to a level of lower than 5% for a major portion of swath, ~70% or greater depending on the number of receivers and spacing. We have completed an SNR formulation, which can consistently account for both coherent and incoherent scattering regardless the spatial resolution. An analysis of SNR based on the Kirchhoff approximation for rough surface scattering has been performed. We find that it is possible to obtain a swath width of 100 km with an SNR of 5 dB or better for a constellation of seven satellites with a receiving antenna directivity of 15 dBi at a LEO altitude of 675 km for a wide range of surface roughness. Our study suggests the promise of the SoOpSAR concept for high-resolution remote sensing of land surfaces.

Hybrid-polarimetric architecture may become a new option for spaceborne quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) mainly due to the range ambiguity improvement without loss of polarization information. To inherit the analytical methods developed for the conventional quad-pol SAR data, it is necessary to transform the hybrid quad-pol SAR data into a linear polarimetric basis. However, this operation will result in deterioration of azimuth ambiguity performance. The theoretical analysis on range and azimuth ambiguities in quad-pol SAR has been relatively complete, which is also summarized in this article. Yet, there is no real data to verify the equivalence of polarization information and to compare the ambiguity levels. Based on P-band airborne experiment, real hybrid and conventional quad-pol SAR data are used for comparative verification. In addition, considering that polarimetric target decomposition is often used in the practical applications, we suggest a new perspective from target decomposition for the ambiguities in quad-pol SAR. Identical polarimetric processing results for two sets of comparative data verify that hybrid quad-pol SAR data are indistinguishable from conventional quad-pol SAR data. The demonstrated intensity images and decomposed RGB images with azimuth ambiguities, acquired by the two quad-pol modes, completely conform to the theory. [ABSTRACT FROM AUTHOR]

Fostered by the upcoming BIOMASS mission, this article explores long-term trends of P-band temporal decorrelation over a tropical forest due to a time series of 617 days acquired during the TropiScat-2 experiment. The interest in this unique time series is twofold. First, it provides consistent statistics to monitor the yearly evolution of temporal coherences according to specific time scales of the BIOMASS tomographic and interferometric phases. Second, it provides key insights to explore new processing approaches with the combination of data from different orbit directions (ascending/descending) and different mission cycles separated by about seven months according to the current acquisition plan. For the first time, this study shows that 18-day coherences (corresponding to the time interval between the first and last acquisitions of the BIOMASS tomographic processing) can vary significantly according to rainy and dry seasons (medians from 0.3 to 0.9). The extension to time intervals of up to 90 days within both seasons and over two consecutive years puts forward the key role of the typical sporadic rainfalls occurring during dry periods in tropical rainforests, with a stronger impact on temporal coherence evolution compared to the more reproducible rainy seasons. Furthermore, outstanding values significantly above zero have been obtained for the 7- and 14-month coherences (medians of 0.35 and 0.2, respectively), opening the way to new methods of change detection. Overall, this study highlights the role of P-band temporal decorrelation not only as a disturbance factor for coherent applications but also as a relevant indicator of forest changes. [ABSTRACT FROM AUTHOR]

An arc-shaped distributed multilayer capacitive loading structure combined with resistive loading is presented in this paper to enhance the radiation performance of folded bowtie antenna (FBA). The radiation efficiency of the loaded bowtie antenna (BA) is improved, and the low-frequency bandwidth is broadened by the bent loop circuits. Additionally, a novel technique of cavity groove is proposed to design the reflector. The optimized cavity tightly coupling with the radiation part overcomes the shortcomings of conventional cavity-backed BAs. The improved ultra-wideband (UWB) FBA with low profile is then designed and fabricated. The basic geometry of the proposed antenna is combined by a novel acorn-shaped bent bowtie patch and a hollowed stepped back cavity. The simulated -10 dB impedance bandwidth of the proposed antenna is over 100 MHz-1100 MHz while the measured operating bandwidth is 250 MHz-850 MHz. This BA of folded type obtains a high realized gain of 4 dBi at 850 MHz and a narrow pattern over the whole band. Time-domain measurements and field tests for practical ground-penetrating radar (GPR) applications have been carried out and the results demonstrate the advanced performance.

P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%–36% (27–33 t/ha) for airborne data and 38%–39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity. [ABSTRACT FROM AUTHOR]

The spaceborne synthetic aperture radar (SAR) system working at P-band, is vulnerable to the ionospheric effect. The ionospheric scintillation will introduce random phase fluctuations into the SAR signal and deteriorate the imaging performance. In this paper, a minimum-entropy autofocusing method based on the intelligent optimization strategy is proposed to compensate for the scintillation phase error in spaceborne P-band SAR images. A refined particle swarm optimization (Re-PSO) is proposed to provide an intelligent strategy in SAR autofocusing. Compared with the traditional minimum-entropy autofocusing methods, the proposed Re-PSO algorithm is a heuristic method which has extremely strong exploring abilities to the global optimum. The genetic multi-crossover operator and the gradient accelerator are utilized to improve the convergence property of the basic PSO. Furthermore, since the isolate strong scatterers are not required in minimum-entropy SAR autofocusing, the proposed method has strong robustness. The simulations on point and area targets validate the effectiveness and better performance of the proposed method.

Currently, near-surface soil moisture at a global scale is being provided using National Aeronautics and Space Administration’s (NASA’s) Soil Moisture Active Passive (SMAP) and European Space Agency’s (ESA’s) Soil Moisture and Ocean Salinity (SMOS) satellites, both of which utilize L-band (1.4 GHz; 21 cm wavelength) passive microwave remote sensing techniques. However, a fundamental limitation of this technology is that the water content can only be measured for approximately the top 5-cm layer of soil moisture, and only over low-to-moderate vegetation covered areas in order to meet the 0.04 $\text{m}^{3}/\text{m}^{3}$ target accuracy, limiting its applicability. Consequently, a longer wavelength radiometer is being explored as a potential solution for measuring soil moisture in a deeper surface layer of soil and under denser vegetation. It is expected that P-band (wavelength of 40 cm and frequency of 750 MHz) could potentially provide soil moisture information for the top $\sim 10$ -cm layer of soil, being one-tenth to one-quarter of the wavelength. In addition, P-band is expected to have higher soil moisture retrieval accuracy due to its reduced sensitivity to vegetation water content and surface roughness. To demonstrate the potential of P-band passive microwave soil moisture remote sensing, a short-term airborne field experiment was conducted over a center pivot irrigated farm at Cressy in Tasmania, Australia, in January 2017. First results showing a comparison of airborne P-band brightness temperature observations against airborne L-band brightness temperature observations and ground soil moisture measurements are presented. The P-band brightness temperature was found to have a similar but stronger response to soil moisture compared to L-band. [ABSTRACT FROM AUTHOR]

A single-frequency dielectric model at 435 MHz for mineral soils is proposed. The dielectric model was created on the basis of the laboratory dielectric measurements of three soil samples with clay content in the range of 9.1%–41.3%. The input parameters of the dielectric model are volumetric soil moisture and clay content. The output parameter of the dielectric model is complex permittivity (CP). The model prediction errors are comparable with the errors of instrumental measurements of the CP for refractive index and normalized attenuation 0.1–0.3 and 0.06–0.12, respectively, in terms of root-mean-square error (RMSE). The comparative analysis of dielectric predictions in the case of the developed model proved to obtain a better accuracy than the existing dielectric models. The created model may be recommended for practical use in the algorithms of soil-moisture retrieval in the P-band. [ABSTRACT FROM AUTHOR]

To date, models describing the complex dielectric constant (CDC) of tundra soils with different contents of organic matter (more than 30%) in the P-band were poorly reported and not developed. In this letter, a refractive dielectric model for moist organic soils at a frequency of 435 MHz was developed. The model was developed on the basis of dielectric measurements of five samples of organic soils with different organic content from 35% to 80% and the soil moisture from air-dry to field capacity at a temperature of 20 °C. The developed model is a function of only two parameters, namely, the organic content by weight and volumetric soil moisture. The new model and future BIOMASS mission will be creating the bases for developing new soil moisture profile retrieving algorithms in the root zone. [ABSTRACT FROM AUTHOR]

In this letter, a theoretical study of the ionospheric influence on the accuracy of measuring the terrain height using a bistatic interferometer composed of a P-band synthetic aperture space radar and a ground receiver was carried out. A method for calculating the height measurement error that takes into account the interferometer geometry, the influence of the ionosphere parameters, additive noise, and spatial decorrelation of radar images is presented. The numerical dependences are obtained that allow estimating the optimal range of the interferometric base values and the height measurement error for point and extended targets. [ABSTRACT FROM AUTHOR]

Effective water management in agriculture requires a comprehensive understanding of the distribution of water content throughout the soil profile to the root zone. This knowledge empowers farmers and water managers to make informed decisions regarding irrigation timing and quantity for optimizing crop growth. To estimate the soil moisture profile, this study utilized combined L- and P-band radiometry with four incoherent radiative transfer models, including three multi-layer models based on a zero-order (IZ), first order (IF) and incoherent solution (IS) approximation, and a uniform model (UM) model, as well as the stratified coherent Njoku model (NM). The impact of vegetation was considered through the conventional tau-omega model. Linear (Li) and second-order polynomial (Pn2) functions were used to represent the shape of the soil moisture profile. Observations from a tower-based experiment under various land cover conditions, including bare, bare-weed, grass, wheat and corn, were used. The root mean square error (RMSE) was calculated between the observed and estimated soil moisture profiles. The results revealed comparable RMSE values for all five radiative transfer models, with the Pn2 function outperforming the Li function in estimating the soil moisture of deeper layers. Regardless of the employed radiative transfer model, utilizing combined L- and P-band radiometry and employing the Pn2 function yielded RMSEs of 0.03 m3/m3, 0.08 m3/m3, and 0.1 m3/m3 over depths of 0–5 cm, 0–30 cm, and 0–60 cm, respectively. A comparison between the incoherent and stratified coherent Njoku radiative transfer models indicated that the latter slightly outperformed the former under the dry bare soil conditions, exhibiting a 0.003 m3/m3 lower RMSE at the surface while nearly equal performance at the bottom of the profile. Furthermore, the multi-layer incoherent radiative transfer models provided only a slightly better estimate than the UM model, especially for shallow layers, with the average RMSE over the entire profile being 0.002 m3/m3 lower. Consequently, the complexity of the multi-layer incoherent and coherent radiative transfer models is not justified for this small gain in performance. The depth for which the UM model provided a reasonable soil moisture estimate ranged from 1 cm (under wet corn) to 39 cm (under dry bare), and depended on the soil moisture profile gradient and soil moisture content values in the shallow layers. These important findings pave the way for estimating soil moisture profile on a global scale using combined L- and P-band radiometry from future satellite missions. • Combined L-band and P-band radiometry was used to estimate soil moisture profiles. • Second-order polynomial surpassed linear function in estimating deep soil moisture. • Multilayer coherent models slightly outperformed uniform model for shallow layers. • Differences between models were minor, particularly for second-order polynomial. • The uniform model estimates: 1 cm (wet corn) to 39 cm (dry bare). [ABSTRACT FROM AUTHOR]

Environmental conditions and seasonal variations affect the backscattered radar signal from a forest. This potentially causes errors in a biomass retrieval scheme using data from the synthetic aperture radar (SAR) data. A better understanding of these effects and the electromagnetic scattering mechanisms in forests is required to improve biomass estimation algorithms for current and upcoming P- and L-band SAR missions. In this paper, temporal changes in HH-, VV-, and HV-polarized P- and L-band radar backscatter and temporal coherence from a boreal forest site are analyzed in relation to environmental parameters. The radar data were collected from a stand of mature Norway spruce ( Picea abies (L.) Karst.) with an above-ground biomass of approximately 250 tons/ha at intervals of 5 min from January to August 2017 using the BorealScat tower-based scatterometer. It was observed that subzero temperatures during the winters cause large variations (4 to 10 dB) in P- and L-band backscatter, for which the HH/VV backscatter ratio offered some mitigation. High wind speeds were also seen to cause deviations in the average backscatter at P-band due to decreased double-bounce scattering. Severe temporal decorrelation was observed at L-band over timescales of days or more, whereas the P-band temporal coherence remained high (>0.9) for at least a month neglecting windy periods. Temporal coherence at P-band was highest during night times when wind speeds are low.

Decorrelation of X, C, and L-band InSAR (Interferometric Synthetic Aperture Radar) over densely vegetated regions is a common obstacle for detecting ground deformation beneath forest canopies. Using long-wavelength P-band SAR sensors (wavelength of 69.72 cm), which can penetrate through dense forests and collect relatively consistent signals from ground surface, is one potential solution. Here, we experimented using the NASA JPL (Jet Propulsion Laboratory)’s P-band AirMOSS (Airborne Microwave Observatory of Subcanopy and Subsurface) radar system to collect repeat-pass P-band SAR data over densely vegetated regions in Oregon and California (USA), and generated by far the first P-band InSAR results to test the capability of P-band InSAR for geohazard detection over forested terrains. Our results show that the AirMOSS P-band InSAR could retain coherence two times as high as the L-band satellite ALOS-2 (Advanced Land Observing Satellite-2) data, and was significantly more effective in discovering localized geohazards that were unseen by the ALOS-2 interferograms over densely vegetated areas. Our results suggest that the airborne P-band InSAR could be a revolutionary tool for studying geohazards under dense forest canopies.

Spatial resolution is one of the most important characteristics of a radar image. Significant limitations in communication regulations should be taken into account concerning radar facilities in long-wave frequency ranges (P or VHF). These limitations do not allow high resolution of a radar facility. The article presents a possible conceptual design of a small spacecraft with a bistatic dual-frequency P-VHF radar facility. The system under consideration is characterized by the displacement of the transmitting station in the process of imaging and stationary position of the receiving station. The synchronization of the system is ensured by organizing a direct channel of signal propagation between the transmitter and receiver. The distinctive feature of the system is simultaneous radiation of direct impulses of the space-borne radio transmitting device in two bands. The influence of the atmosphere on the radar resolution is compensated as a result of joint processing at the ground receiving station. It is expected that total spatial resolution can be brought up to 2 meters due to the simultaneous operation in dual-frequency ranges. The results of a full-scale ground-based experiment simulating the work of the proposed radar complex are presented in the article.

In this letter, we present an experimental assessment of vegetation height retrieval in tropical forests based on P-band synthetic aperture radar (SAR) acquisitions. Two approaches are implemented and compared: 1) parametric height estimation by minimizing the least-square problem between random volume over ground (RVoG) model predictions and multibaseline SAR data and 2) thresholding the vertical backscattering profiles that are focused by SAR Beam-forming tomography. The data set under analysis is from the ESA AfriSAR campaign that was flown over Gabon in 2016. Results show that at a resolution of $25~\text{m}\times 25~\text{m}$ , which corresponds to about 80 independent looks, both of the two approaches are able to retrieve forest height to within an accuracy of about 3 m or better over the interval of forest height between 30 and 50 m when compared to Light Detection and Ranging (LiDAR) measurements. [ABSTRACT FROM AUTHOR]

Active microwave-based retrieval of soil moisture in vegetated areas has uncertainties due to the sensitivity of the signal to both soil (dielectric constant and roughness) and vegetation (dielectric constant and structure) properties. A multi-frequency acquisition system would increase the number of observations that may constrain soil and/or vegetation parameter retrievals. In order to realize this constraint, an understanding of microwaves interaction with the surface and vegetation across frequencies is necessary. Different microwave frequencies have varied interactions with the soil–vegetation medium and increasing penetration into the soil and canopy with the decreasing frequency. In this study, we examine the contributions of different scattering mechanisms to coincident observations from two microwave frequencies (L and P) of airborne synthetic aperture radar instruments. We quantify contributions of surface, vegetation volume, and double-bounce scattering components. Results are analyzed and discussed to guide future multi-frequency retrieval algorithm designs. [ABSTRACT FROM AUTHOR]

The article presents an analysis of options for designs of the antenna system for a synthetic aperture space radar (SAR), with acceptable performance characteristics in L- and P-bands. At the first stage the analysis of the current state of producing spacecraft with L- and P-band radars that use quite large folding antenna structures is carried out. It is shown that to obtain high performance of SAR in L- and P-band large folding reflectors with the diameter of up to15 meters are used. Further, variants of antenna systems are discussed and compared to determine the best combination in terms of the characteristics obtained and design complexity. An antenna system is proposed in the paper that uses antennae of the Yagi-aerial type as antenna array elements. The possibility of creating a space system consisting of several unified small spacecraft with L- and P-band SAR on board is shown.

Currently, creation of space -based P-band radar systems is a vital problem in the development of Earth remote sensing systems. These systems make it possible to solve the problem of monitoring vegetation on the Earths surface, to carry out soil analysis and detect objects detecting hidden in foliage. Such systems are, however, difficult to produce due to the necessity of using large- aperture antenna systems. Expanding active phased arrays and reflector antennas are most common for the task. Structures of this kind are characterized by considerable mass and dimensions, which does not make it possible to regard small satellites as their carriers. A system with an array of four transceiving Yagis is proposed. The systems are shown to possess sufficient characteristics to solve the target tasks. The structures simplicity makes it possible to install the systems on small satellites, which drastically reduces the cost and time of production.

Forest type classification using spaceborne remote sensing is a challenge. Low-frequency Synthetic Aperture Radar (SAR) signals (i.e., P-band, ∼0.69 m wavelength) are needed to penetrate a thick vegetation layer. However, this measurement alone does not guarantee a good performance in forest classification tasks. SAR tomography, a technique employing multiple acquisitions over the same areas to form a three-dimensional image, has been demonstrated to improve SAR’s capability in many applications. Our study shows the potential value of SAR tomography acquisitions to improve forest classification. By using P-band tomographic SAR data from the German Aerospace Center F-SAR sensor during the AfriSAR campaign in February 2016, the vertical profiles of five different forest types at a tropical forest site in Mondah, Gabon (South Africa) were analyzed and exploited for the classification task. We demonstrated that the high sensitivity of SAR tomography to forest vertical structure enables the improvement of classification performance by up to 33%. Interestingly, by using the standard Random Forest technique, we found that the ground (i.e., at 5–10 m) and volume layers (i.e., 20–40 m) play an important role in identifying the forest type. Together, these results suggested the promise of the TomoSAR technique for mapping forest types with high accuracy in tropical areas and could provide strong support for the next Earth Explorer BIOMASS spaceborne mission which will collect P-band tomographic SAR data.

Freeze-thaw (FT) and moisture dynamics within the soil active layer are critical elements of boreal, arctic and alpine ecosystems, and environmental change assessments. We evaluated the potential for detecting dielectric changes within different soil layers using combined L- and P-band radar remote sensing as a prerequisite for detecting FT and moisture profile changes within the soil active layer. A two-layer scattering model was developed and validated for simulating radar responses from vertically inhomogeneous soil. The model simulations indicated that inhomogeneity in the soil dielectric profile contributes to both L- and P-band backscatter, but with greater P-band sensitivity at depth. The difference in L- and P-band responses to soil dielectric profile inhomogeneity appears suitable for detecting associated changes in soil active layer conditions. Additional evaluation using collocated airborne radar (AIRSAR) observations and in situ soil moisture measurements over alpine tundra indicates that combined L- and P-band SAR observations are sensitive to soil dielectric profile heterogeneity associated with variations in soil moisture and FT conditions.

Abstract The RMoG (Random-Motion-over-Ground) model is commonly used to obtain tree height values from PolInSAR images. The RMoG model borrows its structure function from conventional RVoG (Random-Volume-over-Ground) model which is limited for modelling structural variety in canopy layer. This paper extends the RMoG model to improve tree height estimation accuracy by using a Fourier-Legendre polynomial as the structure function. The new model is denoted by the RMoG L model. The proposed modification makes height estimation less prone to errors by enabling more flexibility in representing the vertical structure of the vegetation layer. We applied the RMoG L model on airborne P- and L-band PolInSAR images from the Remingstorp test site in southern Sweden. We compared it with the RMoG and the conventional RVoG models using Lidar height map and field data for validation. For P-band, the relative error was equal to 37.5% for the RVoG model, to 23.7% for the RMoG model, and to 18.5% for the RMoG L model. For L-band it was equal to 30.54% for the RVoG model, to 20.02% for the RMoG model, and to 21.63% for the RMoG L. We concluded that the RMoG L model estimates tree height more accurately in P-band, while in L-band the RMoG model was equally good. The RMoG L model is of a great value for future SAR sensors that are more focused than before on tree height and biomass estimation. [ABSTRACT FROM AUTHOR]

Environmental conditions and seasonal variations affect the backscattered radar signal from a forest. This potentially causes errors in a biomass retrieval scheme using data from the synthetic aperture radar (SAR) data. A better understanding of these effects and the electromagnetic scattering mechanisms in forests is required to improve biomass estimation algorithms for current and upcoming P- and L-band SAR missions. In this paper, temporal changes in HH-, VV-, and HV-polarized P- and L-band radar backscatter and temporal coherence from a boreal forest site are analyzed in relation to environmental parameters. The radar data were collected from a stand of mature Norway spruce (Picea abies (L.) Karst.) with an above-ground biomass of approximately 250 tons/ha at intervals of 5 min from January to August 2017 using the BorealScat tower-based scatterometer. It was observed that subzero temperatures during the winters cause large variations (4 to 10 dB) in P- and L-band backscatter, for which the HH/VV backscatter ratio offered some mitigation. High wind speeds were also seen to cause deviations in the average backscatter at P-band due to decreased double-bounce scattering. Severe temporal decorrelation was observed at L-band over timescales of days or more, whereas the P-band temporal coherence remained high ($>$ 0.9) for at least a month neglecting windy periods. Temporal coherence at P-band was highest during night times when wind speeds are low. [ABSTRACT FROM AUTHOR]

Researches carried out in the last years have shown that the use of P-band SAR tomography (TomoSAR) largely improves the retrieval of the above-ground biomass (AGB) in tropical forests, providing a most encouraging element toward the systematic employment of TomoSAR techniques in the frame of the upcoming spaceborne mission BIOMASS. All of these researches were carried out using campaign data acquired in a single day, and under stable (mostly sunny) weather conditions. The impact of temporal decorrelation was considered in the literature by analyzing ground-based Radar data from the TropiSCAT campaign (Paracou, French Guiana), and found not to be a show-stopper for BIOMASS tomography. Yet, the validity of this analysis was limited to sunny days only. Accordingly, a precise assessment of the impact of changing weather conditions on TomoSAR is currently missing. The aim of this paper is to provide a first experimental element to fill this gap. To do this, data from the TropiSCAT archive are reprocessed to mimic BIOMASS repeat-pass tomography. Since BIOMASS tomography will be implemented by taking seven acquisitions with a revisit time of three days, we form tomograms by taking two TropiSCAT antennas every three days (and three antennas on the last day), which means that any single tomogram is actually obtained by mixing seven different days and under different weather conditions. The quality of tomographic imaging is then assessed by evaluating the observed backscattered power fluctuations in the tomogram time series. While imaging quality is observed to degrade by mixing different days, the resulting temporal variations of the backscattered power in the canopy layer are within 1.5-dB rms in cross polarization. For this forest site, this error is translated into an AGB error of about 50–100 t/ha, which is 20% or less of forest AGB. [ABSTRACT FROM AUTHOR]

Polarimetric Synthetic Aperture Radar Interferometry (PolInSAR) has shown potential for the retrieval of a forest canopy height model (CHM) and the underlying solid earth digital terrain model (DTM). However, because of non-volume decorrelation and other unavoidable errors, the robustness of retrieval heights is sensitive to the spatial baseline of the selected InSAR pairs, which relates forest parameters to measured coherence. Within the context of the random volume over ground (RVoG) model and the three-stage inversion method, we aimed to quantify the influence of spatial baseline on the inversions at P-band, which are distinct from the inversions at higher frequency due to the non-negligible ground contributions. This information assists in optimal baseline selection and the development of robust inversion schemes. Assumptions about the extinction coefficient and additional DTM or DEM were used to reduce the influence of ground contribution on CHM and DTM inversion, respectively. Inversions from published airborne repeat-pass P-band PolInSAR data with four different spatial baselines were validated against LiDAR-derived DTM and CHM data. The results show that a longer spatial baseline performed better in DTM inversion. The longest baseline produced the best R 2 of 0.995 and RMSE of 0.555 m, much better than the smallest baseline with an R 2 of 0.794 and RMSE of 3.74 m. A threshold height could be identified that determines the overestimation and underestimation of CHM inversion due to the non-volume decorrelation. Different baselines produced different threshold heights, making CHM inversion only accurate for a limited range of forest height around the threshold. The optimal baseline produced a CHM with R 2 of 0.605 and RMSE of 2.67 m. Additionally, we found that using multiple baselines has the potential to improve CHM inversion, improving the R 2 to 0.827 and RMSE to 0.876 m in our study. [ABSTRACT FROM AUTHOR]

Understanding the scattering mechanisms from the ground surface in the presence of different vegetation densities is necessary for the interpretation of P-band Synthetic Aperture Radar (SAR) observations and for the design of geophysical retrieval algorithms. In this study, a quantitative analysis of vegetation and soil scattering mechanisms estimated from the observations of an airborne P-band SAR instrument across nine different biomes in North America is presented. The goal is to apply a hybrid (model- and eigen-based) three component decomposition approach to separate the contributions of surface, double-bounce and vegetation volume scattering across a wide range of biome conditions. The decomposition makes no prior assumptions about vegetation structure. We characterize the dynamics of the decomposition across different North American biomes and assess their characteristic range. Impacts of vegetation cover seasonality and soil surface roughness on the contributions of each scattering mechanism are also investigated. Observations used here are part of the NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission and data have been collected between 2013 and 2015. [ABSTRACT FROM AUTHOR]

This work is aimed at showing the present capabilities and future potentialities of an imaging radar system that can be mounted onboard flexible aerial platforms, such as helicopters or small airplanes, and may operate in the UHF and VHF frequency bands as Sounder and as Synthetic Aperture Radar (SAR). More specifically, the Sounder operates at 165 MHz, whereas the SAR may operate either at 450 MHz or at 860 MHz. In the work, we present the first results relevant to a set of Sounder and SAR data collected by the radar during a helicopter-borne campaign conducted in 2018 over a desert area in Erfoud, Morocco, just after the conclusion of a system upgrading procedure. In particular, a first analysis of the focusing capabilities of the Sounder mode and of the polarimetric and interferometric capabilities of the SAR mode is conducted. The overall system, originally developed by CO.RI.S.T.A. according to a ASI funding set up in 2010, has been upgraded in the frame of a contract signed in 2015 between ASI and different private and public Italian Research Institutes and Universities, namely CO.RI.S.T.A., IREA-CNR, Politecnico di Milano and University of Trento.