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.radiative effect | spurious regression | plant ecology | carbon cycle

Initiated in 1984, the Committee Earth Observing Satellites' Working Group on Calibration and Validation (CEOS WGCV) pursues activities to coordinate, standardize and advance calibration and validation of civilian satellites and their data. One subgroup of CEOS WGCV, Land Product Validation (LPV), was established in 2000 to define standard validation guidelines and protocols and to foster data and information exchange relevant to the validation of land products. Since then, a number of leaf area index (LAI) products have become available to the science com-

Estimation of forest canopy cover has recently been included in many forest inventory programmes. In this study, after discussing how canopy cover is defined, different ground-based canopy cover estimation techniques are compared to determine which would be the most feasible for a large scale forest inventory. Canopy cover was estimated in 19 Scots pine or Norway spruce dominated plots using the Cajanus tube, line intersect sampling, modified spherical densiometer, digital photographs, and ocular estimation. The comparisons were based on the differences in values acquired with selected techniques and control values acquired with the Cajanus tube. The statistical significance of the differences between the techniques was tested with the nonparametric Kruskall-Wallis analysis of variance and multiple comparisons. The results indicate that different techniques yield considerably different canopy cover estimates. In general, labour intensive techniques (the Cajanus tube, line intersect sampling) provide unbiased and more precise estimates, whereas the estimates provided by fast techniques (digital photographs, ocular estimation) have larger variances and may also be seriously biased.Keywords forest canopy, canopy cover, canopy closure, Cajanus tube, line intersect sampling, spherical densiometer, digital photographs Addresses University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail lauri.korhonen@joensuu.fi Received 12 April 2006 Revised 22 September 2006 Accepted 26 September 2006 Available at http://www.metla.fi/silvafennica/full/sf40/sf404577.pdf tion of forest canopy cover has recently become an important part of forest inventories. First, canopy cover has been shown to be a multipurpose ecological indicator, which is useful for distinguishing different plant and animal habitats, assessing forest floor microclimate and light conditions, and 578 Silva Fennica 40(4), 2006 research articles estimating functional variables like the leaf area index (LAI) that quantifies the photosynthesizing leaf area per unit ground area (Jennings et al. 1999, Lowman and Rinker 2004). Secondly, many remote sensing applications involve estimation of either canopy cover (Gemmell 1999) or individual tree canopy area (Kalliovirta and Tokola 2005) as an intermediate stage in distinguishing the signals reflected from forest canopy and forest floor, after which, for instance, estimation of timber volume becomes possible (Bolduc et al. 1999). Canopy cover is also an important ancillary variable in the estimation of LAI using empirical or physically based vegetation reflectance models (Jasinski 1990, Spanner et al. 1990, Nilson and Peterson 1991, Knyazikhin et al. 1998, Kuusk and Nilson 2000. The validation of canopy cover estimates obtained from remotely sensed data and development of new remote sensing techniques require field-based canopy cover measurements. Finally, the international definition of a forest is based on canopy cover: the United Nations Food and Agricultural Organization (FAO) has defined forest as land of at...

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