Current methods for estimating photosynthesis and hence net primary productivity (NPP) of forest ecosystems from remote sensing are based on the relationship between (i) the fraction of incident photosynthetically-active radiation absorbed by the canopy (fPAR) and (ii) spectral indices (e.g. NDVI). However, ground-based estimates of fPAR used to quantify this relationship for a specific vegetation type are derived from measurements of canopy structure only (e.g. using light interception methods such as hemispherical photography). Using a coupled leaf-canopy model of radiative transfer, we demonstrated that NDVI is highly sensitive to both canopy foliar and understorey chlorophyll content, which could account for significant errors in remotely sensed estimates of fPAR and hence NPP.

Remotely sensed estimates of the foliar biochemical content of vegetation canopies could be used to derive indicators of ecosystem functioning at regional to global scales. In the past decade, a number of studies have reported strong correlations between the reflectance spectra of vegetation canopies and their foliar biochemical content. However, these studies have commonly employed multiple regression techniques or spectral indices to determine biochemical content, which have been found to be highly sensitive to variation in canopy architecture [such as leaf area index (LAI) and canopy closure] and understory. To date, these effects combined with the low signal-to-noise ratios of airborne spectrometers have inhibited the development of robust and portable spectral techniques for the estimation of canopy biochemical content. This paper reports on a theoretical study in which a leaf model, LIBERTY (leaf incorporating biochemicals exhibiting reflectance and transmittance yields), characterized specifically for conifer needles, was coupled with a hybrid geometric/radiative transfer bidirectional reflectance distribution function FLIGHT (forest light) model. By varying leaf biochemical content, LAI, canopy closure and understory, we analyzed the simulated canopy reflectance spectra to determine if the biochemical absorption features in leaf spectra were preserved at the canopy scale. Absorption features or wavelength regions that were both related to a specific biochemical of interest (water, lignin-cellulose) and persistent at the scale of both the leaf and the canopy were identified at a number of wavelengths or wavelength regions.

New satellite instruments that sample top-of-atmosphere radiance at a number of view angles offer the potential for improved retrieval of atmospheric aerosol opacity, land surface bidirectional reflectance, and biophysical parameters. This paper presents a method for simultaneous retrieval of aerosol opacity and land surface bidirectional reflectance, which utilizes the dual view capability of the second Along-Track Scanning Radiometer (ATSR-2). Analysis of a physically based model of light scattering results in two simple equations defining possible spectral variation of land surface bidirectional reflectance distribution function (BRDF). These are used as constraints to anew inversion of a model of atmospheric scattering to simultaneously retrieve atmospheric aerosol opacity and bidirectional reflectance from top-of-atmosphere radiance. The inversion assumes no a priori knowledge of the land surface cover. Sensitivity is evaluated using both simulated and field-measured data to reproduce expected ATSR-2 observations. Where an atmosphere of known aerosol scattering properties, but of unknown optical depth, is available, results show mean absolute error in retrieval of aerosol opacity of the greater of 0.02 or 15% relative error and bidirectional reflectance retrieval at 55 nm to an accuracy of <0.01. Where a number of candidate aerosol models are available, results show discrimination of dominant aerosol type is possible in 95% of cases considered. The methods perform best over dark surfaces, such as vegetation, but show accurate retrieval over soil and pixels containing a number of cover types.

The conifer leaf model LIBERTY (Leaf Incorporating Biochemistry Exhibiting Reflectance and Transmittance Yields) is an adaptation of radiative transfer theory for determining the optical properties of powders. LIBERTY provides a simulation, at a fine spectral resolution, of quasiinfinite leaf reflectance (as represented by stacked leaves) and single leaf reflectance. Single leaf reflectance and transmittance are important input variables to vegetation canopy reflectance models. A prototype parameterization of LIBERTY was based upon measurements of pine needles and known absorption coefficients of pure component leaf biochemicals. The estimated infinite-reflectance output was compared with the spectra of both dried and fresh pine needles with root mean square errors (RMSE) of 2.87% and 1.73%, respectively. The comparisons between measured and estimated reflectance and transmittance values for single needles were also very accurate with RSME of 1.84% and 1.12%, respectively. Initial inversion studies have demonstrated that significant improvements can be made to LIBERTY by utilizing in vivo absorption coefficients which have been determined by the inversion process. These results demonstrate the capability of LIBERTY to model accurately the spectral response of pine needles.

An artificial neural network was used to control for leaf water absorption during the estimation of lignin-cellulose and nitrogen concentration from the reflectance spectra of fresh slash pine needles. The inputs to the neural network comprised of spectral indices based upon wavelengths at the centre or wings of known absorption features of the biochemical compounds of interest. The results indicate that the neural network provides more accurate estimates of water concentration than when using spectral indices alone. More importantly, lignin-cellulose concentrations were estimated with an accuracy of around 3 per cent relative to mean value. However, an accuracy of only 24 per cent relative to mean value was achieved for estimates of nitrogen concentration.

A method for atmospheric correction of ATSR-2 optical imagery is presented which exploits the sensor's dual view capability. A general model of land surface bidirectional reflectance is developed and used as a constraint to simultaneously retrieve atmospheric aerosol opacity and bidirectional reflectance from top of atmosphere radiance. The inversion assumes no a priori knowledge of the land surface cover, Validation has been performed over boreal forest, showing close agreement between ATSR-2 optical depth retrieval and field measurements.

Remotely-sensed estimates of foliar biochemical concentrations of forests could provide valuable indicators of ecosystem function at regional to global scales. Empirical research has shown strong correlations between the amount of reflected radiation across absorption features and the concentration of biochemicals in vegetation in both laboratory and airborne spectral measurements. Statistics do not, however, provide us with information on the nature of the radiation interaction with canopy elements. A leaf model, LIBERTY (Leaf Incorporating Biochemicals Exhibiting Reflectance and Transmittance Yields), characterised specifically for conifer needles, has been coupled with a hybrid geometric/radiative transfer bi-directional reflectance distribution function (BRDF) model. The resultant output was evaluated for evidence that subtle spectral information due to variation in leaf biochemical concentrations was preserved at the canopy level. Sensitivity of the combined model to canopy variables, such as leaf area index (LAI) and understorey reflectance, demonstrate the need for careful characterisation of the canopy architecture if canopy biochemical composition is to be estimated accurately.

Presents validation of a method for estimation of forest bi-directional reflectance (BRDF) for an example of boreal forest. The method employs Monte Carlo solution of a hybrid geometric optical/radiative transfer model. The model output is compared with ground and airborne measurements of a mature jack pine site collected during BOREAS

This paper presents a method for retrieval of aerosol opacity and land surface bi-directional reflectance using data from the second Along-Track Scanning Radiometer (ATSR-2). The method is based on inversion of a physically based model of land surface reflectance to provide a constraint on the spectral variation of reflectance. Validation is performed for a range of cover types

Hypotheses were tested on the relation between forest leaf area index (LAI), high-spectral resolution reflectance data, the normalized difference vegetation index (NDVI) and the red-edge position (REP). Data were collected using a helicopter-mounted spectroradiometer over stands with LAI varying from 5.6 to 11.0. Linear correlations with reflectance were weak in the red and near-infrared regions and there was no significant relation with the NDVI above an LAI of 6. A strong non-linear correlation was found between plot LAI and the REP (r=0.91) and it is suggested that this index may be complementary to the NDVI for forest LAI estimation.

Presents a method and preliminary results for sensitivity analysis of shortwave atmospheric correction using a combined radiative transfer and multi-angular method. The analysis is focused on the use of the dual look capability of the Second Along-Track Scanning Radiometer (ATSR-2) to correct for the effects of atmospheric scattering. The spectral correlation of bi-directional reflectance is investigated as a means to retrieve aerosol loading over non-Lambertian surfaces

The reflectance of a canopy of mixed species may be affected, among other things, by the percentage cover of each species or by the proportion of each species in the total biomass. The likelihood of either property affecting reflectance is greatest when two species are differentiable spectrally and spatially as is the case for the species of grass and clover that are common in pasture in the U.K. This Letter examines the relations of the percentage cover of clover with reflectance and the proportion of clover in the total biomass with reflectance for a field of pasture in Belper in Derbyshire, U.K. using partial correlation analysis

In an effort to further develop the methods needed to remotely sense the biochemical content of plant canopies, we report the results of an experiment to relate the concentrations of chlorophyll, protein, starch, sugar, amaranthin, and water in fresh whole leaves to their reflectance at wavelengths throughout the visible and near infrared. This is an analysis of laboratory data from a previously reported experiment (Curran et al., 1991) in which 163 freshly excised leaves of the plant Amaranthus tricolor were measured for reflectance and biochemical content. Stepwise regression was used to generate an equation for the estimation of chemical concentration from derivative reflectance in selected wavelengths. The reduction of instrument noise through Fourier filtering and a sample control procedure to minimize spectral overlap had little effect on the correlation between derivative reflectance in selected wavelengths and chemical concentration but did enable absorption features attributable to sugar and protein to be detected. However, the minimization of spectral overlap did increase the number of wavelengths attributable to known absorption features that were selected by stepwise procedures. Using only derivative reflectance in wavelengths that were attributable to absorption by the chemical of interest, the coefficients of determination (R2) between estimated and measured concentrations of chlorophyll, amaranthin, starch, and water were 0.82 or above, with root-mean square errors that were 12.5% of the median or less.

The point of maximum slope in a reflectance spectrum of vegetation occurs at the boundary between red and near infrared wavelengths and is known as the “red edge”. There is a strong relationship between the red edge and the chlorophyll concentration of leaves and canopies. The aim of this research was to determine the effect of a second leaf pigment, red amaranthin, on the relationship between red edge and chlorophyll concentration. The red edge, chlorophyll concentration, and amaranthin concentration were recorded for 163 amaranth leaves in the laboratory. Experimental treatments with nitrate and salts caused a very large range in red edge (686–724 nm), chlorophyll concentration (0–20 mg/g), and amaranthin concentration (0–0.47 mg/g). There was a near-linear relationship between red edge and chlorophyll concentration for leaves with low amaranthin concentration (< 0.075 mg/g). This relationship was strongest for leaves from vegetative plants and was similar in form to that observed for a canopy. By contrast the red edge was at longer wavelengths and independent of chlorophyll concentration for leaves with high amaranthin concentration (0.075 mg/g), as a result of the strong absorption of visible light by amaranthin and the resultant movement of the red/near infrared boundary to longer wavelengths at higher amaranthin concentrations. This is the first reported study on the effect of a second leaf pigment on the relationship between red edge and chlorophyll concentration. The results suggest that the presence of a second leaf pigment would limit the use of a remotely sensed red edge for the estimation of chlorophyll concentration.