Pauline Stenberg

Hyperspectral remote sensing of foliar nitrogen content

A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact—it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423–855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710–790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

Correcting LAI-2000 estimates for the clumping of needles in shoots of conifers

The LAI-2000 plant canopy analyzer tends to underestimate the leaf area index (LAI) of coniferous stands because of the clumped (nonrandom) arrangement of needle area in the crown. It has been proposed that, in stands where the individual shoots constitute the most important clumping elements, the LAI-2000 gives an estimate of shoot silhouette area index rather than LAI. To obtain the true LAI, the instrument reading should then be multiplied by a correction factor accounting for the overlap of needles on shoots. Testing of this hypothesis has so far been faulty due to incorrectly estimated correction factors. We define the appropriate correction factor, and examine its range of variation based on empirical data. Previous studies on the performance of the LAI-2000 in coniferous stands are reviewed based on the results. Our aim is to advocate further testing of whether, when, and how the LAI-2000 estimate can be corrected by accounting simply for the clumping of needles in shoots.

AVHRR-Based Forest Proportion Map of the Pan-European Area.

Abstract A methodology was developed and applied to estimating forest area and producing forest maps. The method utilizes satellite data and ground reference data. It takes into consideration the fact that a pixel rarely represents any single ground cover class. This is particularly true for low-spatial-resolution data. It also takes into consideration that the spectral classes overlap. The image was first classified using an unsupervised clustering method. A (multinormal) spectral density function was estimated for each class based on the spectral vectors (reflectance values) of the cluster members. Values of the target variable — the proportion of forested area — were determined for the spectral classes using sampling from CORINE (Coordination of Information on the Environment) Land Cover database. Each pixel was assigned class membership probabilities, which were proportional to the value of the density function of the respective class evaluated at the spectral value of the pixel. The estimate of forest area for the pixel was finally computed by multiplying the class membership probabilities by the class forest area and summing over all the classes. The method was applied over a mosaic of 49 Advanced Very High Resolution Radiometer (AVHRR) images acquired from the National Oceanic and Atmospheric Administration (NOAA)-14 satellite. The estimated forest areas were compared with those extracted from the full-coverage CORINE data and with official forest statistics reported to the European Commissions Statistical Office (EUROSTAT). The forest percentage (proportion of forest area of the total land area) of 12 countries of the European Union was underestimated by 1.8% compared to the CORINE data. It was underestimated by 4.2% when compared with EUROSTATs statistics and 6.0% when compared to United Nations Economic Commission for Europe/Food and Agricultural Organization (UN-ECE/FAO) statistics. The largest underestimation of forest percentage within a country (compared to CORINE) was in France (5.9%). The largest overestimation was found in Ireland, 15.6%.

A new parameterization of canopy spectral response to incident solar radiation: case study with hyperspectral data from pine dominant forest

A small set of independent variables generally seems to suffice when attempting to describe the spectral response of a vegetation canopy to incident solar radiation. This set includes the soil reflectance, the single-scattering albedo, canopy transmittance, reflectance and interception, the portion of uncollided radiation in the total incident radiation, and portions of collided canopy transmittance and interception. All of these are measurable; they satisfy a simple system of equations and constitute a set that fully describes the law of energy conservation in vegetation canopies at any wavelength in the visible and near-infrared part of the solar spectrum. Further, the system of equations specifies the relationship between the optical properties at the leaf and the canopy scales. Thus, the information content of hyperspectral data can be fully exploited if these variables can be retrieved, for they can be more directly related to some of the physical properties of the canopy (e.g. leaf area index). This paper demonstrates this concept through retrievals of single-scattering albedo, canopy absorptance, portions of uncollided and collided canopy transmittance, and interception from hyperspectral data collected during a field campaign in Ruokolahti, Finland, June 14–21, 2000. The retrieved variables are then used to estimate canopy leaf area index, vegetation ground cover, and also the ratio of direct to total incident solar radiation at blue, green, red, and near-infrared spectral intervals. D 2003 Elsevier Science Inc. All rights reserved.

Optical properties of leaves and needles for boreal tree species in Europe

Reliable information on the optical properties of leaves and needles is needed for parameterization of radiative transfer models and interpretation of remotely sensed data. The optical properties also convey information about the structure and biochemical constituents of the leaf or needle tissues, and can be linked to the photosynthetic processes of plants. Currently, very little is known about the optical properties of tree species in the European boreal zone. To bridge this gap, we measured directional-hemispherical reflectance and transmittance factors of the three most common tree species in this zone: Scots pine, Norway spruce and Silver birch. The measurements covered a wide spectral range from 350 to 2500 nm with a high spectral resolution of 3–10 nm. To explore the driving factors of the observed leaf-level optical properties, supplementary measurements of structural and biochemical traits of leaves and needles were made. The results showed that the transmittance of pine and spruce needles is clearly lower than reflectance, whereas for birch reflectance and transmittance were similar. In conifers, exposed needles had higher albedo than the shaded needles. Also, the spectra of needles were more dependent on canopy position than the spectra of birch leaves. The relationships between narrowband reflectances and chlorophyll and nitrogen percentage concentrations and specific leaf area were similar for all species, but the strongest correlations were observed for birch.

Leaf area index estimation of boreal forest using ENVISAT ASAR

A method for retrieval of leaf area index (LAI) using ENVISAT Advanced Synthetic Aperture Radar vertical/horizontal (VV/HH) polarization ratio was derived for boreal forests. Five alternating polarization single-look complex images of the test site were acquired in summer 2003. The swath range from IS1-IS6 was studied. The VV/HH polarization ratio correlated quite well with the ground truth LAI values. The mean error of the LAI estimates was 0.27 for the test site with mixed forest when data from all images and stands were used without separating between species (or swaths). The respective mean LAI estimation error was 0.3 for Norway spruce (Picea abies (L.) Karst.) and 0.07 for Scots pine (Pinus sylvestris L.) dominated stands.

Below‐Canopy distribution of photosynthetically active radiation and its relation to seedling growth in a boreal Pinus sylvestris stand

A simulation model was used to predict the spatial distribution of direct and diffuse photosynthetically active radiation below a heterogenous canopy of a Pinus sylvestris stand in eastern Finland. Seedling growth was related to both measured and predicted radiation. The model predicted rather well the overall pattern of radiation distribution beneath the canopy. All the growth parameters of Pinus sylvestris seedlings (height, current height increment and mean height increment) correlated positively with the amount of both measured and predicted radiation. The correlation between seedling growth and irradiance was better for predicted diffuse radiation than for total radiation. This was probably because diffuse radiation, being symmetrically distributed around trees, correlates more strongly than direct radiation with other factors affecting seedling growth.

Penumbra in within-shoot and between-shoot shading in conifers and its significance for photosynthesis

Abstract Simulations of the statistical distribution of direct solar irradiance in a Scots pine (Pinus sylvestris L.) crown were used to evaluate the effect of a penumbra (a partial shading of the solar disc) on the rate of photosynthesis. Three different situations were considered: the rate of photosynthesis was estimated at points on needles subjected to (a) shading from the same shoot, (b) shading from another shoot, and (c) both within- and between-shoot shading. Results showed that the penumbral effect of within-shoot shading was small, i.e., the assumption of parallel solar beam geometry within a shoot did not lead to serious underestimates of the rate of photosynthesis. In contrast, shading from another shoot (needle layer) situated further away than ca. 25 cm from the target point could be better characterised as diffuse shading. It is proposed that, in modelling the penetration of direct radiation in a coniferous stand, shading from a short distance (“within-shoot shading”) and that from a longer distance (“between-shoot shading”) be treated separately. A method is presented to estimate mean rates of photosynthesis based on this approach. This method was found to be more accurate than two commonly used methods to estimate photosynthesis, one of which is based on the assumption of parallel solar beam geometry (no penumbra) while the other assumes no stochastic variation in the direct solar component.

Retrieval of boreal forest LAI using a forest reflectance model and empirical regressions

Abstract Spectral invariants provide a novel approach for characterizing canopy structure in forest reflectance models and for mapping biophysical variables using satellite images. We applied a photon recollision probability (p) based forest reflectance model (PARAS) to retrieve leaf area index (LAI) from fine resolution SPOT HRVIR and Landsat ETM+ satellite data. First, PARAS was parameterized using an extensive database of LAI-2000 measurements from five conifer-dominated boreal forest sites in Finland, and mixtures of field-measured forest understory spectra. The selected vegetation indices (e.g. reduced simple ratio, RSR), neural networks and kNN method were used to retrieve effective LAI (Le) based on reflectance model simulations. For comparison, we established empirical vegetation index-LAI regression models for our study sites. The empirical RSR–Le regression performed best when applied to an independent test site in southern Finland [RMSE 0.57 (24.2%)]. However, the difference to the best reflectance model based retrievals produced by neural networks was only marginal [RMSE 0.59 (25.1%)]. According to this study, the PARAS model provides a simple and flexible modelling tool for calibrating algorithms for LAI retrieval in conifer-dominated boreal forests. The advantage of PARAS is that it directly uses field measurements to parameterize canopy structure (LAI-2000, hemispherical photographs) and optical properties of foliage and understory.

Modeling the Spectral Signature of Forests: Application of Remote Sensing Models to Coniferous Canopies

The vertical and horizontal structure of forest canopies is one of the most important driving factors of various ecosystem processes and has received increas- ing attention during the past 20 years and served as an impetus for earth observation missions. In the remote sensing community, the variables which describe canopy structure are called biophysical variables, and are directly coupled with the fun- damental physical problem behind remote sensing: radiative transfer in vegetation. There are basically three different approaches to interpreting biophysical variables from remotely sensed data: (1) empirical, (2) physically based, and (3) various com- binations of them. The physical approach builds upon an understanding of the phys- ical laws governing the transfer of solar radiation in vegetative canopies, and for- mulates it mathematically by canopy reflectance models which relate the spectral signal to biophysical properties of the vegetation. In this chapter, we will first out- line the basic principles and existing physically based model types for simulating the spectral signature of forests. After this, the focus is on the specific issues related to applying these models to the complex 3D structure of coniferous canopies.