we developed and tested the use of light emitting diodes (leds) to monitor vegetation reflectance in narrow spectral bands as a tool suitable for quantifying and monitoring ecosystem structure, function and metabolism. leds are appealing because they are inexpensive, small and reliable light sources that, when used in reverse mode, can measure spectrally selective radiation.weselected leds in red and nearinfrared wavebands as they are used to calculate the normalized difference vegetation index (ndvi). the lab experiments revealed that the leds showed linear relation with a hyper-spectral spectroradiometer (r2 > 0.94 and 0.99 for red and nir, respectively) and marginal sensitivity to temperature. to test the efficacy of this novel sensor, we measured spectral reflectance with leds over an annual grassland in california over 3.5 years. the led-sensor captured daily to inter annual variation of the spectral reflectance at the two bands with reliable and stable performance. the spectral reflectance in the two bands and ndvi proved to be useful to identify the leaf-on and leaf-off dates (mean bias errors of 5.3 and 4.2 days, respectively) and to estimate canopy photosynthesis (r2 = 0.91). we suggest that this novel instrument can monitor other structural and functional (e.g. leaf area index, leaf nitrogen) variables by employing leds that have other specific wavelengths bands. considering that off-the-shelf leds cover a wide range of wavebands from the ultraviolet to near-infrared regions, we believe that the research community could explore a range of similar instruments across a range of bands for a variety of ecological applications.
linking spectral reflectance indices with vegetation structure (e.g. leaf area index (lai)), function (e.g. nitrogen (n), phenology) and metabolism (e.g. gross primary productivity, evaporation) has advanced the understanding of ecosystem processes and their influence on biosphere-atmosphere interactions (baldocchi et al., 1996; gamon et al., 2006b; running et al., 1999). the reflectance of solar radiation in the visible and near-infrared portions of the electromagnetic spectrum is correlated with vegetation status, development and growth, and is monitored for this reason in remote sensing of terrestrial vegetation. spectral reflectance measured from air- and space-borne platforms covers broad areas repeatedly, but such measurements are prone to contamination by atmospheric effects (e.g. aerosol, clouds, etc.) (kobayashi and dye, 2005). thus, continuous observation of vegetation reflectance in situ is warranted to better understand the vegetation status with direct high spatial and temporal resolution data (gamon et al., 2006b).