Canopy Scattering Research Articles

A three-component scattering model for polarimetric SAR data

An approach has been developed that involves the fit of a combination of three simple scattering mechanisms to polarimetric SAR observations. The mechanisms are canopy scatter from a cloud of randomly oriented dipoles, evenor double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants and Bragg scatter from a moderately rough surface. This composite scattering model is used to describe the polarimetric backscatter from naturally occurring scatterers. The model is shown to describe the behavior of polarimetric backscatter from tropical rain forests quite well by applying it to data from NASA/Jet Propulsion Laboratory's (JPLs) airborne polarimetric synthetic aperture radar (AIRSAR) system. The model fit allows clear discrimination between flooded and nonflooded forest and between forested and deforested areas, for example. The model is also shown to be usable as a predictive tool to estimate the effects of forest inundation and disturbance on the fully polarimetric radar signature. An advantage of this model fit approach is that the scattering contributions from the three basic scattering mechanisms can be estimated for clusters of pixels in polarimetric SAR images. Furthermore, it is shown that the contributions of the three scattering mechanisms to the HH, HV, and VV backscatter can be calculated from the model fit. Finally, this model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem.

A theoretical analysis of the effect of forest structure on synthetic aperture radar backscatter and the remote sensing of biomass

Stand level forest canopy structure as measured by the size, density, and distribution of the stems, branches, and leaves may have a strong effect on SAR backscatter. This study used the Michigan Microwave Canopy Scattering model (MIMICS) and forest canopy biometric data from tropical and subtropical broadleaf forests to simulate a series of forest stands having equivalent above ground biomass while still exhibiting substantial structural differences. The model stands were made to represent a wide range of basic structural differences found in Earth’s broadleaf forests. The radar response to these structural differences is shown for the NASNJPL AIRSAR P-, L-, and C-band quadpol. configuration at incidence angles of 20°, 40°, and 60°. Results for three sets of equal-biomass-foreststands were generated: five structural types having a total above ground biomass of 5 kg/m2 (50 tonha), three structural types at 15 kg/m2 (150 tonsha), and three structural types at 30 kg/m2 (300 tonsha). Simplified model input were used to reduce the number of geometric variables tested across the range of structural types. The potential effect that extreme structural differences might have on the biomass signal and saturation threshold was assessed. Results indicate that structure can have a considerable effect on the SAR return for forests with equivalent above ground biomass. Differences in backscatter of up to 18 dB were predicted for some bands and polarizations. A forest canopy structural descriptor derived from the vegetation surface area to volume ratio (SAN), which is a measure of stuctural consolidation, appears to explain the differences in backscatter. In many vegetation stands structural consolidation is directly related to an increase in biomass during the thinning phase of forest succession. This structural effect may explain the good relationship between SAR backscatter and biomass in these cases.

Application of an artificial neural network in canopy scattering inversion

Abstract Owing to their recent success in other inversion tasks, application of an artificial neural network to the development of an inversion algorithm for radar scattering from vegetation canopies is considered. Because canopy scattering models are complicated functions of the desired biophysical parameters (vegetation biomass, leaf area index, soil moisture content, etc.), the development of an effective inversion algorithm is not a straightforward task. The Michigan Microwave Canopy Scattering (MIMICS) model, which has shown remarkable success in predicting the radar response to vegetation canopies, was used, as were measured polarimetric backscatter values. Hence, the radiative transfer simulation code, MIMICS, was used to produce some of the training data. The inputs to the neural network were the expected polarimetric backscatter values from specific canopies, while the outputs were the desired parameters, such as tree heights, crown thickness, leaf density, etc. Two special cases were examined: (1) inversion of MIMICS given modelled aspen stands of different ages; (2) inversion of measured data from the Duke forest loblolly pine stands. The MIMICS inversion shows that neural networks are capable of accurately inverting some of the parameters of such a complicated model. The implication is that once MIMICS is made to model the radar data for a specific application, then inversion of the radar data may be accomplished. The measured data inversion shows that, even without a model such as MIMICS, one may train a neural network to invert several parameters of interest. However, this depends on accurate and complete surveys of the ground truth data to be useful.

Adaptation of the MIMICS backscattering model to the agricultural context-wheat and canola at L and C bands

Presents the results obtained from the MIMICS (Michigan Microwave Canopy Scattering) forest backscattering model which was modified to accommodate agricultural parameters. In the MIMICS model, the forest canopy is divided into three regions: the crown layer, the trunk region, and the underlying rough ground. The crop cover situation is simulated by a rough ground and a crown layer composed of scatterers with different forms, distributions, and dielectric constants. The authors omit trunks from the final agricultural representation because these components are of the same order as the wavelength, contrary to the model's implicit assumptions. The simulation results are compared to ground based scatterometer data of wheat and canola. The paper describes the simulation results for the two crops at L and C bands and the two like polarizations. An analysis of the different backscattering mechanisms is also given for each crop. Good simulation results were obtained at L and C bands for HH polarization for both these crops throughout the growing season. An error analysis indicates that the soil moisture can be predicted with a precision better than 0.03 g/cm/sup 3/ for both crops, if all other model parameters are known. In addition, if the moisture is known, the height of the stems and the diameter of the leaves of the canola crop can be estimated with a precision better than /spl plusmn/5 cm and /spl plusmn/0.5 cm, respectively.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Radiative transfer modelling of discontinuous tree canopies at microwave frequencies

Development of a first-order radiative transfer model for predicting backscatter from tree canopies has been underway at the University of Michigan Radiation Laboratory for some time. This model is known as the Michigan Microwave Canopy Scattering (MIMICS) model. This article presents the second-generation MIMICS model (MIMICS II) which accounts for canopies with discontinuous (open) crown layer geometries. MIMICS II models open crown layers by treating the location, size, and shape of the individual tree crowns as random variables. The backscattering coefficients for the canopy are then determined by introducing statistics derived from these parameters into the radiative transfer solution. Application of the radiative transfer equations to the discontinuous canopy geometry is presented. The resulting model is a robust fully polarimetric solution that is applicable over a wide variety of canopy architectures. Model simulations are compared to results generated with the continuous canopy model. The effect of the open crown geometry is found to be most significant at shallow incidence angles and at high frequencies for trees with well-developed crowns. Under these conditions, the gaps in the crown layer give rise to a notable increase in crown layer transmissivity which allows the radar to see through to the lower layers of the canopy more easily, thereby directly affecting the backscatter contribution of the trunks and ground.

Modeling multi-frequency Diurnal backscatter from a walnut orchard

The Michigan Microwave Canopy Scattering Model (MIMICS) is used to model scatterometer data that were obtained during the August 1987 EOS (Earth Observing System) synergism study. During this experiment, truck-based scatterometers were used to measure radar backscatter from a walnut orchard in Fresno County, California. Multipolarized L- and X-band data were recorded for orchard plots for which dielectric and evapotranspiration characteristics were monitored. MIMICS is used to model a multiangle data set in which a single orchard plot was observed at varying impedance angles and a series of diurnal measurements in which backscatter from this same plot was measured continuously over several 24-h periods. MIMICS accounts for variations in canopy backscatter driven by changes in canopy state that occur diurnally as well as on longer time scales. L-band backscatter is dependent not only on properties of the vegetation but also on properties of the underlying soil surface. The behavior of the X-band backscatter is dominated by properties of the tree crowns.

Michigan microwave canopy scattering model

Abstract The Michigan Microwave Canopy Scattering model (MIMICS) is based on a first-order solution of the radiative-transfer equation for a tree canopy comprising a crown layer, a trunk layer and a rough-surface ground boundary. The crown layer is modelled in terms of distributions of dielectric cylinders (representing needles and/or branches) and discs (representing leaves), and the trunks are treated as dielectric cylinders of uniform diameter. This report describes MIMICS I, which pertains to tree canopies with horizontally continuous (closed) crowns. The model, which is intended for use in the 0·5-10GHz region at angles greater than 10° from normal incidence, is formulated in terms of a 4 × 4 Stokes-like transformation matrix from which the backscattering coefficient can be computed for any transmit/receive polarization configuration.