Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry

Forest canopy height is a critical parameter in better quantifying the terrestrial carbon cycle. It can be used to estimate aboveground biomass and carbon pools stored in the vegetation, and predict timber yield for forest management. Polarimetric SAR interferometry (PolInSAR) uses polarimetric separation of scattering phase centers derived from interferometry to estimate canopy height. A limitation of PolInSAR is that it relies on sufficient scattering phase center separation at each pixel to be able to derive accurate forest canopy height estimates. The effect of wavelength-dependent penetration depth into the canopy is known to be strong, and could potentially lead to a better height separation than relying on polarization combinations at one wavelength alone. Here we present a new method for canopy height mapping using dual-wavelength SAR interferometry (InSAR) at X- and L-band. The method is based on the scattering phase center separation at different wavelengths. It involves the generation of a smoothed interpolated terrain elevation model underneath the forest canopy from repeat-pass L-band InSAR data. The terrain model is then used to remove the terrain component from the single-pass X-band interferometric surface height to estimate forest canopy height. The ability of L-band to map terrain height under vegetation relies on sufficient spatial heterogeneity of the density of scattering elements that scatter L-band electromagnetic waves within each resolution cell. The method is demonstrated with airborne X-band VV polarized single-pass and L-band HH polarized repeat-pass SAR interferometry using data acquired by the E-SAR sensor over Monks Wood National Nature Reserve, UK. This is one of the first radar studies of a semi-natural deciduous woodland that exhibits considerable spatial heterogeneity of vegetation type and density. The canopy height model is validated using airborne imaging LIDAR data acquired by the Environment Agency. The rmse of the LIDAR canopy height estimates compared to theodolite data is 2.15 m (relative error 17.6%). The rmse of the dual-wavelength InSAR-derived canopy height model compared to LIDAR is 3.49 m (relative error 28.5%). From the canopy height maps carbon pools are estimated using allometric equations. The results are compared to a field survey of carbon pools and rmse values are presented. The dual-wavelength InSAR method could potentially be delivered from a spaceborne constellation similar to the TerraSAR system.     

Determining forest canopy characteristics using airborne laser data

A pulsed laser system was flown over a forested area in Pennsylvania which exhibited a wide range of canopy closure conditions. The lasing system acts as the ultraviolet light equivalent of radar, sensing not only the distance to the top of the forest canopy, but also the range to the forest floor. The data were analyzed to determine which components of the laser data could explain the variability in crown closure along the flight transect. Results indicated that canopy closure was most strongly related to the penetration capability of the laser pulse. Pulses were attenuated more quickly in a dense canopy. Hence the inability to find a strong ground return in the laser data after initially sensing the top of the canopy connoted dense canopy cover. Photogrammetrically acquired tree heights were compared to laser estimates; average heights differed by less than 1 m. The results indicated that the laser system may be used to remotely sense the vertical forest canopy profile. Elements of this profile are linearly related to crown closure and may be used to assess tree height.     

Relationships between polarimetric SAR backscatter and forest canopy and sub-canopy biophysical properties

This paper highlights the potential of multiwaveband polarimetric SAR data for the estimation of both canopy (percentage canopy closure) and sub-canopy (stem biomass) biophysical variables of a Sitka spruce forest in upland Wales. Stand stem biomass was estimated using forest survey data on diameter at breast height (DBH) and tree height from 0.01 ha plots. Photographs of the forest canopy were taken using a camera fitted with a wide-angle fisheye lens from a number of locations within a stand. The photographs were later digitized and estimates of stand percentage canopy closure were derived using image processing software. It was found that C-band HV and VV, and L-band HV and VV polarization backscatter were significantly related to stem biomass. There was no sensitivity to percentage canopy closure using single polarization backscatter but highly significant relationships were obtained using ratios of single polarization backscatter and variables derived from the polarization signatures. The strong correlations between C-band backscatter and stem biomass indicated a relationship between the structure of the top crown layer and sub-canopy biomass.     

Evaluate Quantitatively Effects of Understory on Leaf Area Index (LAI) Estimation Combining Active and Passive Remote Sensing Data

Natural forests have the vertical three\|dimensional structure of canopy and understory vegetation (shrubs,grasslands,and bare soil).Accurate and quantitative separation of understory vegetation is of great scientific significance and practicality on improving the precision of inversion of forest canopy leaf area index.value.Due to the limitations of traditional passive optical remote sensing data on directly acquiring 3D information,this study intends to combine active and passive ALS and HyperMap data with the Washington Botanic Garden as the key research area.On the basis of individual tree segmentation,the vertical stratification of the forest (forest canopy and undergrowth vegetation layer) is achieved.On this basis,the forest canopy laser point cloud data was used to remove the understory information from the optical image data.By comparing the results of the forest effective leaf area index obtained from aerial optical images and ground measurements,it was found that：(1) forest canopy density has a significant impact on the penetration of ALS data;(2) removal of understory information can effectively improve the forest crown accuracy of LAIe estimated.The correlation between Normalized Difference Vegetation Index (NDVI) and ground surface measured effective leaf area index increased from 0.087 to 0.591.In addition,the optical remote sensing image based on the removal of understory vegetation information was compared with the Simple Ratio vegetation index (SR) (the correlation increased from 0.209 to 0.559) and the simplified simple Ratio vegetation index (RSR) (the correlation increased from 0.147 to 0.358).The NDVI was most sensitive to changes in canopy leaf area index (correlation increased by 0.5).The method of quantitatively separating understory vegetation with the combined active and passive remote sensing data proposed in this study can effectively improve the accuracy of inversion of forest canopy leaf area index,and provide a solid foundation for quantitative and accurate estimate of forest biophysical parameters and study of carbon and water cycle processes.     

Vertical backscatter profile of forests predicted by a macroecological plant model

This study describes a new application of a macroecological model to describe the vertical profile of radar backscatter through forest canopy. Given layers of equally sized cylindrical scatterers, the model predicts that one layer within the forest canopy dominates the backscatter profile. This prediction is based on first-order theoretical approximations, in addition to results from a radiative transfer model parameterized by the macroecological model. This model is used to pre-empt specific backscatter trends with results predicting that Rayleigh and Optical backscatter follow negative and positive exponential trends respectively when plotted with respect to backscattering coefficient and branching level through the canopy. A maximum value is predicted by the model associated with the branching level located at the transitional zone between Rayleigh and Optical scattering. This finding follows directly from the size density distribution within a forest combined with dramatic reductions in cross-sectional trends exhibited through the transition. It is a result unrelated to resonant scattering or the effects of penetration depth. The feasibility of describing radar interactions using geometric optics is explored when limits are imposed on the physical optics scattering solution.

The findings offer a significantly new way of understanding the distribution of scattering from differently sized elements in a canopy, and challenge the widely held assumption that backscatter–biomass relationships saturate due to increased opacity of the canopy.     

Investigating the effect of the physical scattering mechanism of the dual-polarization sentinel-1 data on the temporal coherence optimization results

Polarimetric Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is an effective technique for increasing the number and phase quality of selected persistent scatterer (PS) pixels. In this technique, multitemporal polarimetric data is used to find the dominant scattering mechanism of targets in a stack of SAR data by polarimetric optimization and to improve the performance of PSI methods for deformation studies. The main goal of polarimetric optimization is to find the optimum scattering mechanism to generate interferograms with better quality. In this paper, we investigated the effect of the physical scattering mechanism on the temporal coherence optimization results. In this framework, we only optimized the physical scattering mechanism. This optimization is based on maximizing the temporal coherency criterion by changing the type of scattering mechanism to increase the number of PS with good phase quality. The proposed method is tested using a dataset of 17 dual-pol SAR data (VV/VH) acquired by Sentinel1-A satellite. This paper concludes that the phase quality of PS pixels can be improved by optimization of physical scattering mechanism. Also, the results show an overall increase of PS pixels density in different areas with respect to the conventional channel of VV.     

Forest canopy recovery from the 1938 hurricane and subsequent salvage damage measured with airborne LiDAR

The structure of a forest canopy often reflects its disturbance history. Such signatures of past disturbances or legacies can influence how the ecosystem functions across broad spatio-temporal scales. The 1938 hurricane and ensuing salvage operations which swept through New England represent the most recent large, infrequent disturbance (LID) in this region. Though devastating (downing ∼ 70% of the timber at Harvard Forest), the disturbance was not indiscriminate; it left behind a heterogeneous landscape comprised of different levels of canopy damage. We analyzed large-footprint LiDAR, from the Prospect Hill tract at Harvard Forest in central Massachusetts, to assess whether damage to the forest structure from the hurricane and subsequent timber extraction could be discerned after ∼ 65 years. Differences in LiDAR-derived measures of canopy height and vertical diversity were a function of the degree of damage from the 1938 hurricane and the predominant tree species which is, in part, a function of land use history. Higher levels of damage corresponded to slightly shorter canopies with a less even vertical distribution of return from the ground to the top. In addition, differences in canopy topography as revealed by spatial autocorrelation of canopy top heights were found among the damage classes. Less disturbed stands were characterized by lower levels of local autocorrelation for canopy height and higher levels of vertical diversity of LiDAR returns. These differences in canopy structure reveal that the forest tract has not completely recovered from the 1938 LID and salvage regime, which may have implications on arboreal and understory habitat and other ecosystem functions.     

3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains

A detailed 3D structural model of a conifer forest canopy was developed in order to simulate the reflectance (optical) and backscatter (microwave) signals measured remotely. We show it is feasible to model forest canopy scattering using detailed 3D models of tree structure including the location and orientation of individual needles. An existing structural growth model of Scots pine (Pinus sylvestris L.), Treegrow, was modified to simulate observed growth stages of a Scots pine canopy from age 5 to 50 years. The 3D tree models showed close structural agreement with in situ measurements. Needles were added to the structural models according to observed phyllotaxy (distribution). Individual trees were used to generate model canopies, which in turn were used to drive optical and microwave models of canopy scattering. Simulated canopy radiometric response was compared with airborne hyperspectral reflectance data (HyMAP) and airborne synthetic aperture RADAR (ASAR) backscatter data. Model simulations agreed well in general with observations, particularly at optical wavelengths where model simulations of low and high density canopy stands were shown to bracket observations. Relatively small sensitivity of observed reflectance to canopy age was captured reasonably well by the simulations. The choice of needle shape and phyllotaxy was shown to have a significant impact on multiple scattering behaviour at the branch scale. In the microwave domain, simulated backscatter values agreed reasonably well with observations at L-band, less so at X-band. L-band simulated backscatter significantly underestimated observed backscatter at younger canopy ages, probably as a result of inappropriate modelling of soil/understory. It is demonstrated that a combined structural and radiometric modelling approach provides a flexible and powerful method for simulating the remotely sensed signal of a forest canopy in the optical and microwave domains. This is particularly useful for exploring the impact of canopy structure on the resulting signal and also for combined retrievals of forest structural parameters from optical and microwave data.     

Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling

Methods for using airborne laser scanning (also called airborne LIDAR) to retrieve forest parameters that are critical for fire behavior modeling are presented. A model for the automatic extraction of forest information is demonstrated to provide spatial coverage of the study area, making it possible to produce 3-D inputs to improve fire behavior models.The Toposys I airborne laser system recorded the last return of each footprint (0.30-0.38 m) over a 2000 m by 190 m flight line. Raw data were transformed into height above the surface, eliminating the effect of terrain on vegetation height and allowing separation of ground surface and crown heights. Data were defined as ground elevation if heights were less than 0.6 m. A cluster analysis was used to discriminate crown base height, allowing identification of both tree and understory canopy heights. Tree height was defined as the 99 percentile of the tree crown height group, while crown base height was the 1 percentile of the tree crown height group. Tree cover (TC) was estimated from the fraction of total tree laser hits relative to the total number of laser hits. Surface canopy (SC) height was computed as the 99 percentile of the surface canopy group. Surface canopy cover is equal to the fraction of total surface canopy hits relative to the total number of hits, once the canopy height profile (CHP) was corrected. Crown bulk density (CBD) was obtained from foliage biomass (FB) estimate and crown volume (CV), using an empirical equation for foliage biomass. Crown volume was estimated as the crown area times the crown height after a correction for mean canopy cover.     

Measurement of canopy interception of solar radiation by stands of trees in sparsely wooded savanna

Abstract

A three-dimensional tree canopy model of scenes which consist of a discontinuous tree layer and a continuous field layer is described. ‘Scene’ or spatial average tree canopy layer transmissions are defined for direct solar radiation, diffuse sky radiation and emission of reflected radiation from the ground and field layers. Hemispherical canopy photographs are used to measure these three types of transmission and the measurements provide the parameters for the model which can be inverted to give estimates of the spatial average properties of a scene. The model requires only the frequency distribution of tree canopy diameters to be specified and these can be measured on the ground or on aerial photographs. The effect of each canopy is additive and so the model can be applied to any pattern and density of trees. Hemispherical photographs can be reinterpreted for any solar azimuth and zenith angle and are therefore applicable for long periods of time. Measurements in two areas of savanna woodland in Kordofan, Sudan, showed that canopy cover measured in the traditional way, which treats the canopy as opaque, overestimated interception by approximately half. Comparisons between Acacia Senegal and other species indicate that there are some significant differences in transmission characteristics between savanna tree species. The relevance of these observations to remote sensing of savanna field layer primary production is discussed.     

Allometric constraints on sources of variability in multi-angle reflectance measurements

Bidirectional reflectance signatures of vegetation are strongly shaped by the shadows cast between objects in a scene, such as tree crowns or leaves. Differences in the shape and spatial density of these objects result in distinct bidirectional reflectance distribution functions (BRDFs) in different biomes. We examined how allometry may constrain the variability of canopy architectural parameters in BRDF models, and consequently alter the attribution of variation in the simulated bidirectional reflectance factor (BRF). Allometry is the covariation between the size or number of organisms and their component parts.To test the importance of realistic variation and covariation of canopy architecture on BRDF, we incorporated the 3-D radiative transfer model DISORD (which uses the geometric optics (GO) model of Li and Strahler) into a Monte Carlo (MC) algorithm. The MC algorithm generated an ensemble of tree canopies whose parameters fulfilled the allometry of a set of measured forest plots from Russian forest inventory. The role of view geometry was directly considered using perturbations of the parameters to evaluate the sensitivity of the BRF itself, evaluated at different view angles, and the difference in BRF (ΔBRF) as measured at two view angles representing paired satellite observations.The allometrically constrained forest plots had reduced variation in ΔBRF compared to the uncorrelated plots, but the variation of the BRF itself is dramatically increased by allometry. The variation of the BRF is relatively constant among the view angles examined, whereas the variation in ΔBRF increases dramatically with larger phase angles. The BRF was most sensitive to canopy attributes that were important in radiative transfer, such as LAI and stem area index (SAI), but there were also large (∼ 40% of variance) contributions of geometric components such as tree number, crown size, and ground cover. By contrast, sensitivity of ΔBRF was dominated by ground cover, crown size and tree number, which all play a role in the GO calculations. The mix of sensitive parameters was not dramatically different between gymnosperms and angiosperms, nor between allometric and correlated runs. Together these results indicate that forest structure and leaf area could be usefully inverted together using paired observations with different viewing geometries. Ideal pairs of observations are those with large difference in phase angle, and along the gradient of the BRF peak, which most commonly occur with sequential MODIS/Terra overpasses.     

Shrub detection using disparate airborne laser scanning acquisitions over varied forest cover types

We explore the possibility of extending the national forest inventory-based point data of understory presence using region-wide, disparate lidar data for the southeastern USA. For this, we developed a simple inferential model that helps to understand the basic underlying relationships and associations between lidar predictor metrics and forest understory shrub presence over a wide range of forest types and topographic conditions. The model (a least absolute shrinkage and selection operator-based logistic regression model) had fair predictive performance (accuracy = 62%, kappa = 0.23). Hence, we were able to propose a set of biophysically meaningful predictor variables that represent understory (4), canopy (3), topographic conditions (1), and sensor characteristics (1). The single most important predictor variable was the understory layer canopy density, which is the ratio of lidar returns in the understory to those near the ground. Hence, we demonstrate that the interplay of several factors affects understory vegetation condition. Overall, our work highlights the potential value of using lidar to characterize understory conditions.     

Effective tree scattering and opacity at L-band

This paper investigates vegetation effects at L-band by using a first-order radiative transfer (RT) model and truck-based microwave measurements over natural conifer stands to assess the applicability of the τ ? ω (tau–omega) model over trees. The tau–omega model is a zero-order RT solution that accounts for vegetation effects with two vegetation parameters (vegetation opacity and single-scattering albedo), which represent the canopy as a whole. This approach inherently ignores multiple-scattering effects and, therefore, has a limited validity depending on the level of scattering within the canopy. The fact that the scattering from large forest components such as branches and trunks is significant at L-band requires that zero-order vegetation parameters be evaluated (compared) along with their theoretical definitions to provide a better understanding of these parameters in the retrieval algorithms as applied to trees.This paper compares the effective vegetation opacities, computed from multi-angular pine tree brightness temperature data, against the results of two independent approaches that provide theoretical and measured optical depths. These two techniques are based on forward scattering theory and radar corner reflector measurements, respectively. The results indicate that the effective vegetation opacity values are smaller than but of similar magnitude to both radar and theoretical estimates. The effective opacity of the zero-order model is thus set equal to the theoretical opacity and an explicit expression for the effective albedo is then obtained from the zero- and first-order RT model comparison. The resultant albedo is found to have a similar magnitude as the effective albedo value obtained from brightness temperature measurements. However, both are less than half of the single-scattering albedo estimated using the theoretical calculations (0.5?0.6 for tree canopies at L-band). This lower observed effective albedo balances the scattering darkening effect of the large theoretical single-scattering albedo with a first-order multiple-scattering contribution. The retrieved effective albedo is different from theoretical definitions and not the albedo of single forest elements anymore, but it becomes a global parameter, which depends on all the processes taking place within the canopy, including multiple-scattering and canopy ground interaction.     

Radar response of periodic vegetation canopies

Vector radiative transfer theory is used to model the scattered intensity from a layer of randomly oriented particles over a periodic rough surface. To account for the periodic nature of row-structured vegetation, the number density of particles within the layer is assumed to be varying periodically in the horizontal direction. Using Fourier series expansions and orthogonality properties, the radiative transfer equation is solved for the transformation matrix relating the incident and scattered intensities, from which the backscattering coefficient of the layer can be computed for any incidence direction and polarization configuration. The experimental component of this investigation consisted of radar observations at 1–5,4–75, and 9–5 GHz made by a truck-mounted system for a field of corn under three conditions: (a) full, which means that the corn plants were in their natural state, (b) defoliated, which was accomplished by stripping off the leaves and removing them, thereby leaving behind only bare vertical stalks, and (c) bare soil, which corresponds to the soil surface after having removed the stalks. The soil surface is modelled as a composite consisting of a deterministic periodic component and a random roughness component. A two-scale polarimetric scattering model is formulated and used to compare with the experimental observations. Excellent agreement between theory and measurements is realized as a function of both incidence and azimuth angles at all three microwave frequencies. The canopy model was then applied to the corn canopy under the two other conditions: stalks alone and full canopy. The model results were compared with radar backscatter measurements made for each of three look directions, including perpendicular and parallel to the row direction and at 45° relative to the row direction. For the stalk canopy, it was observed that the quasi-periodic arrangement of the stalks within the row enhances the backscatter at L-band when looking perpendicular to the row direction, which is attributed to a coherent-scattering effect associated with the stalks. A heuristic approach is used to model the quasi-periodic structure of the stalks by deriving a coherency factor which multiplies the first-order radiative solution for randomly located stalks. A similar coherency factor was also introduced for the leaves of the full canopy. The modified model was found to provide good agreement with experimental observations at L-band for all polarizations and at all look directions.     

Towards a detection of grassland cutting practices with dual polarimetric TerraSAR-X data

In this study, polarimetric synthetic aperture radar (SAR) parameters are analysed and compared with in situ measurements in order to develop a methodology for detecting cutting practices within grassland areas. The grasslands were monitored with TerraSAR-X radar imaging in dual polarization HH/VV mode and are located near the banks of the Kasari River, close to the Baltic Sea coast of Estonia. The parameters analysed include HH, VV, HH + VV, and HH – VV backscatter, HH/VV polarimetric coherence magnitude and phase, T₁₂ polarimetric coherence magnitude and phase, and also dual polarimetric entropy, alpha, and alpha dominant parameters. Using these parameters derived from the dual polarimetric TerraSAR-X data set, it was virtually impossible to distinguish tall grass (height >30 cm) from short grass (height <30 cm). On the other hand, it proved feasible to detect areas where grass had been cut and left on the ground. Several parameters showed specific behaviour for the state of grassland and the most notable change was found in the dual polarimetric dominant scattering alpha angle. This angle changed from 10° to 25° after tall grass had been cut and left on the ground. This behaviour of the dominant scattering alpha angle can effectively be described using a particle scattering model for vegetation backscattering.     

An airborne lidar sampling strategy to model forest canopy height from Quickbird imagery and GEOBIA

High-resolution digital canopy models derived from airborne lidar data have the ability to provide detailed information on the vertical structure of forests. However, compared to satellite data of similar spatial resolution and extent, the small footprint airborne lidar data required to produce such models remain expensive. In an effort to reduce these costs, the primary objective of this paper is to develop an airborne lidar sampling strategy to model full-scene forest canopy height from optical imagery, lidar transects and Geographic Object-Based Image Analysis (GEOBIA). To achieve this goal, this research focuses on (i) determining appropriate lidar transect features (i.e., location, direction and extent) from an optical scene, (ii) developing a mechanism to model forest canopy height for the full-scene based on a minimum number of lidar transects, and (iii) defining an optimal mean object size (MOS) to accurately model the canopy composition and height distribution. Results show that (i) the transect locations derived from our optimal lidar transect selection algorithm accurately capture the canopy height variability of the entire study area; (ii) our canopy height estimation models have similar performance in two lidar transect directions (i.e., north-south and west-east); (iii) a small lidar extent (17.6% of total size) can achieve similar canopy height estimation accuracies as those modeled from the full lidar scene; and (iv) different MOS can lead to distinctly different canopy height results. By comparing the best canopy height estimate with the full lidar canopy height data, we obtained average estimation errors of 6.0 m and 6.8 m for conifer and deciduous forests at the individual tree crown/small tree cluster level, and an area weighted combined error of 6.2 m, which is lower than the provincial forest inventory height class interval (i.e., ≈ 9.0 m).     

Effects of different flying altitudes on biophysical stand properties estimated from canopy height and density measured with a small-footprint airborne scanning laser

Canopy height distributions were created from small-footprint airborne laser scanner data collected over 133 georeferenced field sample plots and 56 forest stands located in young and mature forest. The plot size was 300-400 m² and the average stand size was 1.7 ha. Spruce and pine were the dominant tree species. Canopy height distributions were created from both first and last pulse data. The laser data were acquired from two different flying altitudes, i.e., 530-540 and 840-850 m above ground. Height percentiles, mean and maximum height values, coefficients of variation of the heights, and canopy density at different height intervals above the ground were computed from the laser-derived canopy height distributions. Corresponding metrics derived from the two different flying altitudes were compared. Only 1 of 54 metrics derived from the first pulse data differed significantly between flying altitudes. For the last pulse data, the mean values of the height percentiles were up to 50 cm higher than the corresponding values of the low-altitude data. The high-altitude data yielded significantly higher values for most of the canopy density measures. The standard deviation for the differences between high and low flying altitude for each of the metrics was estimated. The standard deviations for the height percentiles ranged from 0.07 to 0.30 cm in the forest stands, indicating a large degree of stability between repeated flight overpasses.The effect of variable flying altitude on mean tree height (h_L), stand basal area (G), and stand volume (V) estimated from the laser-derived height and density measures using a two-stage inventory procedure was assessed by randomly combining laser data from the two flying altitudes for each individual sample plot and forest stand. The sample plots were used as training data to calibrate the models. The random assignment was repeated 10,000 times. The results of the 10,000 trials indicated that the precision of the estimated values of h_L, G, and V was robust against alterations in flying altitude.     

Ground-based C-band tomographic profiling of a conifer forest stand

We provide a demonstration of the new tomographic profiling (TP) technique, here applied to forestry for the first time. The portable ground-based synthetic aperture radar (GB-SAR) system was used to capture profiles of the vertical polarimetric backscattering patterns through a ～7 m tall stand of Norway spruce trees. The TP scheme collects data as for normal SAR imaging, but with the antennae aligned in the along-track direction. Adaptive post-processing meant that each TP scan simultaneously captured along-track image transects over the incidence angle range 0°–60°. An important feature of the derived image products is that incidence angle is constant at every point within an image. The measured HH–VV height backscatter profiles were very similar, whilst the cross-/co-polarization ratio showed very little variation with height through the stand. Backscattering profiles showed closest agreement with the branch biomass distribution through the canopy, rather than with trunk or branch + trunk biomasses. Equivalent interferometric tree heights were estimated from the centre of mass of the backscatter-height distribution, which displayed increasing height with increasing incidence angle. There was no significant vertical separation between the cross- and co-polarization returns.     

Volumetric lidar return patterns from an old-growth tropical rainforest canopy

Rainforests represent the epitome of structural complexity in terrestrial ecosystems. However, measures of three-dimensional canopy structure are limited to a few areas typically < 1 ha with construction crane or walkway/platform access. An innovative laser profiling system, the Laser Vegetation Imaging Sensor (LVIS), was used to map canopy structure (i.e. based on height and vertical distribution of laser returns) of a tropical rainforest in Costa Rica. Within a 1km2 area of mature rainforest, canopy top height ranged from 8.4 to 51.6m based on the altimeter measures. The laser return density was most concentrated in the horizontal layer located 20-30m above the ground. Spatial patterns of the return were found to be isotropic based on north-south versus east-west vertical return profiles and exhibited properties of self-similarity.