Microwave scattering from mixed-species forests, Queensland, Australia

The potential of synthetic aperture radar (SAR) data for retrieving the above-ground and component (e.g., branch, trunk) biomass of mixed-species forests (including woodlands) typical to subtropical Queensland, Australia, was evaluated using a wave scattering model based on that of Durden et al. (1989). The model was parameterized using field data collected for nine forest types, which were selected through combined analysis of 1 : 4000 aerial photographs and light detection and ranging data. The simulated SAR backscatter data demonstrated a good correspondence at most frequencies and polarizations with Airborne SAR data. Analysis of scattering mechanisms revealed dominance of C-band horizontal-vertical (HV) volume scattering and increases with small-branch/foliage biomass, dominance of L- and P-band HH trunk-ground scattering and increases with trunk biomass, and dominance of L-band HV volume (branch) scattering and increases with large-branch biomass. The study concluded that above-ground biomass estimated using empirical relationships with selected SAR channels will be more reliable for forests of similar structural form due to dominance of microwave interaction with particular biomass components and the strength and consistency of relationships between these and the affiliated components that represent the total. In mixed-species forests, retrieval will be compromised by interaction with a greater diversity of structures and variability in relationships between structural components. Although empirical relationships with selected combinations of channels (e.g., L-band HH/HV) might allow retrieval of component and total biomass of forests containing trees of similar form (e.g., as mapped using Landsat sensor data), the use of SAR inversion models was considered a more appropriate route for retrieving the biomass of forests containing a mix of structural forms.     

Global Simulation of Brightness Temperatures at 6.6 and 10.7 GHz Over Land Based on SMMR Data Set Analysis

In the framework of the Soil Moisture and Ocean Salinity mission, a two-year (1987–1988) global simulation of brightness temperatures (TB) at L-band was performed using a simple model [L-band microwave emission of the biosphere, (L-MEB)] based on radiative transfer equations. However, the lack of alternative L-band spaceborne measurements corresponding to real-world data prevented from assessing the realism of the simulated global-scale TB fields. In this study, using a similar modeling approach, TB simulations were performed at C-band and X-band. These simulations required the development of C-MEB and X-MEB models, corresponding to the equivalent of L-MEB at C-band and X-band, respectively. These simulations were compared with Scanning Multichannel Microwave Radiometer (SMMR) measurements during the period January to August 1987 (corresponding to the end of life of the SMMR mission). A sensitivity study was also carried out to assess, at a global scale, the relative contributions of the main MEB parameters (particularly the roughness and vegetation model parameters). Regional differences between simulated and measured TBs were analyzed, discriminating possible issues either linked to the radiative transfer model (C-MEB and X-MEB) or due to land surface simulations. A global agreement between observations and simulations was discussed and allowed to evaluate regions where soil moisture retrievals would give best results. This comparison step made at C-band and X-band allowed to better assess how realistic and/or accurate the L-band simulations could be.     

Measurement and modeling of the millimeter-wave backscatterresponse of soil surfaces

The millimeter-wave (MMW) backscatter response of bare-soil was examined by conducting experimental measurements at 35 and 94 GHz using a truck-mounted polarimetric scatterometer and by developing appropriate models to relate the backscattering coefficient to the soil's surface and volume properties. The experimental measurements were conducted for three soil surfaces with different roughnesses under both dry and wet conditions. The experimental measurements indicate that in general the backscattering coefficient is comprised of a surface scattering component σ^s and a volume scattering component σ ^v. For wet soil conditions, the backscatter is dominated by surface scattering, while for dry conditions both surface and volume scattering are significant, particularly at 94 GHz. Because theoretical surface scattering models were found incapable of predicting the measured backscatter, a semiempirical surface scattering model was developed that relates the surface scattering component of the total backscatter to the roughness parameter ks, where k=2π/λ and s is the rms height, and the dielectric constant of the soil surface. Volume scattering was modeled using radiative transfer theory with the packed soil particles acting as the host material and the air voids as the scattering particles. The combined contribution of surface and volume scattering was found to provide good agreement between the model calculations and the experimental observations     

A semi-empirical backscattering model at L-band and C-band for asoybean canopy with soil moisture inversion

Radar backscatter measurements of a pair of adjacent soybean fields at L-band and C-band are reported. These measurements, which are fully polarimetric, took place over the entire growing season of 1996. To reduce the data acquisition burden, these measurements were restricted to 45° in elevation and to 45° in azimuth with respect to the row direction. Using the first order radiative transfer solution as a form for the model of the data, four parameters were extracted from the data for each frequency/polarization channel to provide a least squares fit to the model. For inversion, particular channel combinations were regressed against the soil moisture and area density of vegetation water mass. Using L-band cross-polarization and VV-polarization, the vegetation water mass can be regressed with an R ²=0.867 and a root mean square error (RMSE) of 0.0678 kg/m ². Similarly, while a number of channels, or combinations of channels, can be used to invert for soil moisture, the best combination observed, namely, L-band VV-polarization, C-band HV- and VV-polarizations, can achieve a regression coefficient of R²=0.898 and volumetric soil moisture RMSE of 1.75%     

Passive microwave remote sensing of forests: a model investigation

A model, based on the radiative transfer theory and the matrix doubling algorithm, is described and used to compute the emissivity e of forests. According to model simulations, the L-band emissivity trend versus forest biomass is more gradual than that of the backscatter coefficient. This gradual behavior is observed, in absence of leaves, also at C- and X-bands, while leaves anticipate saturation and make e higher in coniferous forests and lower in deciduous forests. Model results are successfully validated by some available experimental data. Operational aspects, concerning the potential of airborne and spaceborne radiometers in identifying forest type and estimating biomass, are discussed     

Simulated and observed backscatter at P-, L-, and C-bands fromponderosa pine stands

The authors compared the output of the Santa Barbara microwave canopy backscatter model to polarimetric synthetic aperture radar (SAR) data for three ponderosa pine stands (ST-2, ST-11, and SP-2) with discontinuous tree canopies near Mt. Shasta, California, at P-band (0.68-m wavelength), L-band (0.235-m wavelength), and C-band (0.056-m wavelength). Given the SAR data calibration uncertainty, the model made good predictions of the P-HH, P-VV, L-HH, C-HH, and C-HV backscatter for the three stands, and the P-HV and L-HV backscatter for ST-2 and SP-2. The model underestimated C-VV for the three stands, and P-HV, L-HV, and L-VV backscatter for ST-11. The observed and modeled VV-HH phase differences were ≃0° for the three stands at C-band and L-band, and for SP-2 at P-band. At P-band, the observed and modeled VV-HH phase differences were at least -80° for ST-2 and ST-11, which indicates that double-bounce scattering contributes to the total backscatter for the two stands     

Ku- and C-band SAR for discriminating agricultural crop and soilconditions

A method is proposed to estimate both green leaf area index (GLAI) and soil moisture (h_v), based on radar measurements at the Ku-band (14.85 GHz) and C-band (5.35 GHz) frequencies. The Ku-band backscatter at large incidence angles was found to be independent of soil moisture conditions and could be used alone to estimate GLAI. Then, the Ku-band estimate of GLAI could be used with a measurement of C-band backscatter in a canopy radiative transfer model to isolate the value of h_v. This concept was demonstrated with a set of Kuand C-band synthetic aperture radar (SAR) backscatter data acquired over agricultural fields in Arizona. The demonstration showed promise for operational application of the method, though several limitations were identified. Since both Ku- and C-band σ_° are sensitive to soil roughness, this approach must be applied only to fields of similar soil roughness or row direction. This limitation may be less serious for farm management applications since crop type and cultivation practices are generally well known and can be taken into consideration. Another limitation of the use of Ku- and C-band σ° is the apparent saturation of the Ku-band signal with increasing GLAI. Operational implementation of this approach will require dual-frequency sensors aboard an aircraft or orbiting satellite     

Characterizing L-Band Scattering of Paddy Rice in Southeast China With Radiative Transfer Model and Multitemporal ALOS/PALSAR Imagery

Rice is a major food supply in southeast China. With increased population and urbanization, reliable rice mapping is critical in this region. Because of frequent cloud cover and precipitation during the rice-growing season, it is difficult to conduct large-area rice monitoring with optical remote sensing techniques. L-band synthetic aperture radar (SAR), with its all-weather day and night imaging and canopy penetration capabilities, provides a unique alternative. In this study, a first-order radiative transfer model was developed to simulate L-band scattering properties of paddy rice. Three Advanced Land Observing Satellite (ALOS)/Phased-Array-Type L-band Synthetic Aperture Radar (PALSAR) images in dual-polarization mode (HH and HV) acquired in early tillering (June 28, 2007), tillering (August 13, 2007), and heading (September 28, 2007) stages were processed to test the temporal variation of rice backscatter. It was found that plant height and leaf mass amount were the two major structural parameters that contributed to rice backscatter in PALSAR images. The variation of the simulated HH backscatter matched with PALSAR observations in sample fields, although the simulated backscatter coefficients were around 3 dB lower than image-extracted values. Leaf volume scattering and leaf–ground double bounce were found as the two major scattering components in L-band HH polarization and increased with leaf layer height and density. This paper demonstrated that L-band HH backscatter was more sensitive to rice's structural variation than the VV backscatter and may therefore be more useful in rice mapping and modeling studies.      

Monitoring of rain water storage in forests with satellite radar

The sensitivity of radar backscatter to the amount of intercepted rain in temperate deciduous forests is analyzed to determine the feasibility of retrieval of this parameter from satellite radar data. A backscatter model is validated with X-band radar measurements of a single tree exposed to rain. A good agreement between simulation and measurements is observed and this demonstrates the ability of radar to measure the amount of intercepted rain. The backscatter model is next applied to simulate different satellite radar configurations. To account for forest variability, the backscatter difference between a wet and dry forest canopy is calculated for four deciduous tree species, above a wet and a dry soil. On average, the simulated backscatter of a wet forest canopy is 1 dB higher than the backscatter of a dry forest canopy at co-polarized L-band and 2 dB at co-polarized C and X-band. The simulated sensitivity is in agreement with observations. It is argued that current satellites can retrieve the amount of intercepted rain at best with a reliability of 50%, due to the variability in soil moisture, species composition and system noise. The authors expect that the reliability will improve with the launch of the next generation radar satellites. The results of this analysis may also be used to assess the influence of rain, fog or dew upon other radar applications for temperate deciduous forests     

Airborne Ku-Band Polarimetric Radar Remote Sensing of Terrestrial Snow Cover

Characteristics of the Ku-band polarimetric scatterometer (POLSCAT) data acquired from five sets of aircraft flights in the winter months of 2006-2008 for the second Cold Land Processes Experiment (CLPX-II) in Colorado are described in this paper. The data showed the response of the Ku-band radar echoes to snowpack changes for various types of background vegetation in the study site in north central Colorado. We observed about 0.15-0.5-dB increases in backscatter for every 1 cm of snow-water-equivalent (SWE) accumulation for areas with short vegetation (sagebrush and pasture). The region with the smaller amount of biomass, signified by the backscatter in November, seemed to have the stronger backscatter response to SWE in decibels. The data also showed the impact of surface hoar growth and freeze/thaw cycles, which created large snow-grain sizes, ice crust layers, and ice lenses and consequently increased the radar signals by a few decibels. The copolarized HH/VV backscatter ratio seems to indicate double-bounce scattering between the ground surface and snow or vegetation. The cross-polarized backscatter [vertical-horizontal (VH)] showed not only the influence of vegetation but also the strong response to snow accumulation. The observed HV/VV ratio suggests the importance of multiple scattering or nonspherical scattering geometry of snow grain in the dense-media radiative transfer scattering model. Comparison of the POLSCAT and QuikSCAT data was made and confirmed the effects of mixed terrain covers in the coarse-resolution QuikSCAT data.     

Calculations of the Microwave Brightness Temperature of Rough Soil Surfaces: Bare Field

A model for simulating the remotely sensed microwave brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is calculated from one minus its reflectivity, which is obtained by the integration of the bistatic scattering coefficients for rough soil surfaces. The soil brightness temperature is obtained from the product of the surface emissivity and the effective soil temperature, which is calculated with measured soil moisture profiles and soil temperature profiles at various soil depths. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation a and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both L-band (1.4 GHz) and C-band (5 GHz) frequencies. A nonlinear least squares fitting method is used to match the model calculations with the data, and the best fit results produce the parameter values of a and l that best characterize the surface roughness. The effect of rough surface shadowing is also incorporated into the model by introducing a shadowing function S(?), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for horizontal polarization are in excellent agreement with the data, both qualitatively and quantitatively. For vertical polarization, some discrepancies exist between the calculations and data. Possible causes of the discrepancy are discussed.     

Radar sensitivity to tree geometry and woody volume: a modelanalysis

A model, based on radiative transfer theory and the matrix doubling algorithm, is described and used to compute the backscatter coefficients σ°s of forests. The objective is to investigate the radar sensitivity to woody biomass and some geometrical tree properties like branch dimensions and orientation. Model computations show that the backscatter coefficient is sensitive to the woody volume, particularly at HV polarization, P and L band; however, the radar response is appreciably influenced also by branch dimensions and orientation. Comparisons with experimental results available in the literature are shown. The correspondence between predicted and measured σ°s is generally good, although a slight overestimation is noted at L band, while uncertainties about data calibration and soil properties make the comparisons more difficult, in some cases, at P band     

Effect of multiple scattering on the phase signature of wet subsurface structures: applications to polarimetric L- and C-band SAR

We propose a two-layer integral equation model (IEM) model including multiple-scattering terms to reproduce the phase signature of buried wet structures that we observed on L-band synthetic aperture radar (SAR) images. We have good agreement between the extended (single+multiple scattering) IEM model and previous results obtained using a single-scattering IEM model combined with finite-difference time-domain simulations. We show that the multiple scattering not only significantly influences the copolarized phase difference but can also be related to the soil moisture content. In order to assess the validity of our extended model, we performed radar measurements on a natural outdoor site and showed that they could be fairly well fitted to the extended model. A parametric analysis presents the dependence of the copolarized phase difference on roughness parameters (rms height and correlation length) and radar parameters (frequency and incidence angle). Our study also shows that the phase signature should allow detection of buried wet structures down to a larger depth for C-band (3.8 m) than for L-band (2.6 m). This signature could then be used to map subsurface moisture in arid regions using polarimetric SAR systems.     

Radar estimates of aboveground biomass in boreal forests ofinterior Alaska

Airborne SAR data gathered by the NASA/JPL three-frequency, polarimetric, radar system in winter, spring, and summer over the Bonanza Creek Experimental Forest, near Fairbanks, AK, are compared to estimates of whole-tree aboveground dry biomass from 21 forest stands and two clear-cuts. While C-band radar backscatter shows little sensitivity to biomass, L- and P-band radar backscatter increase by more than 6 dB when biomass increases from 5 to 200 tons/ha. Using second-order polynomial regressions, biomass values are predicted from the radar at L- and P-band and compared to actual biomass values. At P-band HV-polarization, the error in predicted biomass is about 30% of the actual biomass. When HV-, HH-, and VV-polarization are used together in the regression, the error in predicted biomass is about 20%. Errors obtained using L-band data are a few percents larger. These errors are caused by uncertainties in actual stand biomass estimates, significant inner-stand spatial variations in biomass, unusual conditions of forest stands following natural disturbances, along with interactions of the radar signals with a complex three-dimensional structure of the canopy. Multiple incidence angle data reveal that the incidence angle &thetas; _i of the radar illumination is also a factor influencing the retrieval of biomass, even at HV-polarization, when &thetas;_i>50° or &thetas;_i<25°. Finally, the radar response of the forest-and thereby the regression curves for biomass retrieval-are dependent on the seasonal and environmental conditions     

Stand age retrieval in production forest stands in New Zealand using C- and L-band polarimetric Radar

Regressions of single-, dual-, quad-, and full-polarization L- and C-band synthetic aperture radar (SAR) against stand age from 403 radiata pine stands in Kaingaroa Forest, New Zealand have been carried out, using the National Aeronautics and Space Administration's Airborne SAR instrument. The regressions attempted to find products suitable for the separation of young (two years or less) from old stands (25 years or older), and for the estimation of stand age. Local incidence angle had no significant effect for C-band, but was always significant for L-band, giving a standard error reduction of 13% to 32% for log stand age. Stand density was highly significant for both bands, giving standard error reductions of 7% to 47%. Single- and dual-polarization products were severely biased, and it was impossible to separate young and old stands, except L-band horizontal-(HH)-plus-horizontal-vertical (HV). C-band quad-polarization gave less bias and lower error than for that L-band, when local incidence angle and stand density were excluded. C-band full-polarization using covariance magnitudes gave no improvement over C-band quad-polarization, but L-band did give a significant improvement. The C- and L-band full-polarization products with six polarimetric indices gave significant improvements in the standard error. The results show that regressions of SAR data with stand age are possible with full- and quad-polarization L- and C-band datasets, although the prediction limits increase rapidly with stand age. The smallest error in estimated stand age, with an RMS of 3.22 years, was for L-band full-polarization with six polarimetric indices, calculated from a validation dataset. Separation of young and old forest stands was only possible for full-, quad-polarization, and the L-band HH-plus-HV products.     

Coherent effects in microwave backscattering models for forestcanopies

In modeling forest canopies, several scattering mechanisms are taken into account, (1) volume scattering; (2) surface-volume interaction; (3) surface scattering from forest floor. Depending on the structural and dielectric characteristics of forest canopies, the relative contribution of each mechanism in the total backscatter signal of an imaging radar can vary. In this paper, two commonly used first-order discrete scattering models, distorted Born approximation (DBA) and radiative transfer (RT) are used to simulate the backscattered power received by polarimetric radars at P-, L-, and C-bands over coniferous and deciduous forests. The difference between the two models resides on the coherent effect in the surface-volume interaction terms. To demonstrate this point, the models are first compared based on their underlying theoretical assumptions and then according to simulation results over coniferous and deciduous forests. It is shown that by using the same scattering functions for various components of trees (i.e. leaf, branch, stem), the radiative transfer and distorted Born models are equivalent, except in low frequencies, where surface-volume interaction terms may become important, and the coherent contribution may be significant. In this case, the difference between the two models can reach up to 3 dB in both co-polarized and cross-polarized channels, which can influence the performance of retrieval algorithms     

A combined method to model microwave scattering from a forest medium

A novel method, which employs both a matrix doubling algorithm and the first-order solution of a radiative transfer (RT) equation for modeling microwave backscattering from forest, is presented in the paper. The method is based on the assumption that a forest canopy can be divided into a number of distinct horizontal vegetation layers over a dielectric half-space rough surface. The scattering phase matrix of each layer is calculated by either matrix doubling to account for the multiple-scattering effect or first-order solution of an RT equation, depending on the scattering characteristics of the layer. The first-order solution of the RT equation is used for the trunk layer while the matrix doubling technique is applied to both the crown layer and understory. The advanced integral equation model and reflectivity matrix are used to calculate the noncoherent and coherent surface boundary conditions. Comparisons between model predictions and field measurements on radar backscattering coefficients for a walnut orchard showed a good agreement at both L-band and X-band and for all three polarizations. Comparative analyses of model predictions for backscattering from a forest medium calculated using the combined model, first-order RT model, and the standard matrix doubling model were also presented. Understory effects, that can significantly change the weight of each scattering mechanism, were also evaluated by using the combined method.     

Airborne multifrequency L- to Ka-band radiometric measurements overforests

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     

Improvement of Moisture Estimation Accuracy of Vegetation-Covered Soil by Combined Active/Passive Microwave Remote Sensing

The measured effects of vegetation canopies on radar and radiometric sensitivity to soil moisture are compared to first-order emission and scattering models. The models are found to predict the measured emission and backscattering with reasonable accuracy for various crop canopies at frequencies between 1.4 and 5.0 GHz, especially at angles of incidence less than 30°. The vegetation loss factor L (?) increases with frequency and is found to be dependent upon canopy type and water content. In addition, the effective radiometric power absorption coefficient of a mature corn canopy is roughly 1.75 times that calculated for the radar at the same frequency. Comparison of an L-band radiometer with a C-band radar shows the two systems to be complementary in terms of accurate soil moisture sensing over the extreme range of naturally occurring soil-moisture conditions. The combination of both an L-band radiometer and a C-band radar is expected to yield soil-moisture estimates that are accurate to better than +/-30 percent of true soil moisture, even for a soil under a lossy crop canopy such as mature corn. This is true even without any other ancillary information.     

FOSMEX: Forest Soil Moisture Experiments With Microwave Radiometry

The microwave Forest Soil Moisture Experiment (FOSMEX) was performed at a deciduous forest site at the Research Centre Julich (Germany). An L- and an X-band radiometer were mounted 100 m above ground and directed to the canopy. The measurements consist of dual- and single-polarized L- and X-band data and simultaneously recorded ground moisture, temperature, and meteorological data. The canopy L-band transmissivity was estimated from a subset of the FOSMEX data, where the ground was masked with a metalized foil. For the foliage-free canopy, the reflecting foil diminished the L-band brightness by ap24 K, whereas brightness increased by ap14 K when the foil was removed from below the foliated canopy. Depending on the assumption made on the scattering albedo of the canopy, the transmissivities were between 0.2 and 0.51. Furthermore, the contribution of the foliage was quantified. Although, the evaluation revealed the semitransparency of the canopy for L-band frequencies, the brightness sensitivity with respect to ground moisture was substantially reduced for all foliation states. The effect of ground surface moisture was explored in an irrigation experiment. The L-band measurements were only affected for a few hours until the water drained through the litter layer. This emphasizes the significance of the presence of litter for soil moisture retrieval from remotely sensed L-band brightness data. The FOSMEX database serves for further testing and improving radiative transfer models used for interpreting microwave data received from future spaceborne L-band radiometers flying over areas comprising a considerable fraction of deciduous forests.