## 1 Introduction  
Optical data sampling in broad or narrow wavelength bands provides a complement to micrometeorological measurements and vegetation sampling for estimation of biogeochemical processes. It also provides a link between measurements from Earth observation platforms and ground observations. We present an optical sampling network and data from the first year of measurement, which demonstrate the use of these data for observation of phenology and vegetation productivity (Figure 1). **Figure 1.** Sampling sites (red dots). D = Denmark, F = Finland, N = Norway, and S = Sweden. Eddy covariance measurements today provide a direct way of monitoring fluxes of greenhouse gases at the ecosystem level, thereby enabling the assessment of carbon fluxes and vegetation productivity [1]. Net ecosystem exchange (NEE) is the net flux of carbon dioxide between the ecosystem and the atmosphere. The footprint of the flux measurements is a complex function of the height of measurement, the roughness of the area and vegetation, and the meteorological conditions [2]. Though the flux data have profoundly improved our ability to understand ecosystem processes, the fluxes represent the exchanges of CO\({}_{2}\) between the biosphere and the atmosphere across a relatively widespread area. Data from eddy covariance towers display variations from subtle vegetation changes. However, flux tower sites are expensive to set up and are not directly comparable to satellite measurements when up-scaling flux measurement to global scale with the aid of remote sensing data. Furthermore, these complicated systems often face interruptions due to technical problems, such aspower failure. Optical data and field observations can complement and aid the analysis of these fluxes, e.g., mapping the phenological development of overstorey and understorey vegetation components, and providing proxy data that can complement flux measurements during periods of missing data. Optical sampling is considerably cheaper than eddy-covariance measurements, and such sensors can hence be installed at a larger number of sites. Normally, the size of the footprint from eddy covariance measurements approaches that of coarse-resolution satellite sensors, e.g., Terra/MODIS, with a nominal footprint area between 250 \(\times\) 250 m and 1 km \(\times\) 1 km, depending on wavelength band. Reflected radiation observed from these satellites can hence be directly related to eddy covariance data for upscaling purposes. Numerous studies have demonstrated the feasibility in modeling vegetation productivity, notably gross primary productivity (GPP), based on the light use efficiency concept [3-9], or statistical models [10-13]. However, satellite measurements vary due to a number of factors, including variations in illumination and viewing geometry, clouds and atmospheric conditions, variations in the pixel footprint, sensor noise, and influence of various meteorological events like snowfall, rain, and haze. Measuring with optical sensors near the ground to eliminate or minimize some of these factors will enable better understanding of the satellite measurements. The prospect of monitoring vegetation phenology from Earth observation platforms has attracted a lot of attention. With the emergence of long time data records from Earth observation sensors it is now possible to observe variations in phenological parameters, like length of the growing season. Visible changes in vegetation phenology may act as important indicators of climatic change, as phenology responds to the effect of several physiological and biogeochemical factors of the ecosystem [14]. Current ground-based observations indicate that the recent climate-induced change in spring onset is in the order of _ca._ 2.5 days earlier per decade across Europe [15].