Ground-based imaging spectrometry of canopy phenology and chemistry in a deciduous forest

Phenology, annual life cycles of plants and animals, is a dynamic ecosystem attribute and an important feedback to climate change. Vegetation phenology is commonly monitored at canopy to continental scales using ground based digital repeat photography and satellite remote sensing, respectively. Existing systems which provide sufficient temporal resolution for phenological monitoring, however, lack the spectral resolution necessary to investigate the coupling of phenology with canopy chemistry (e.g. chlorophyll, nitrogen, lignin-cellulose content). Some researchers have used narrowband (\u3c10 nm resolution) spectrometers at phenology monitoring sites, yielding new insights into seasonal changes in leaf biochemistry. Such instruments integrate the spectral characteristics of the entire canopy, however, masking considerable variability between species and plant functional types. There is an opportunity, then, for exploring the potential of imaging spectrometers to investigate the coupling of canopy phenology and the leaf biochemistry of individual trees. During the growing season of April-October 2013 we deployed an imaging spectrometer with a spectral range of 371-1042 nm and resolution of ~5 nm (Surface Optics Corporation 710; San Diego, CA) on a 35 m tall tower at the Harvard Forest, Massachusetts. The image resolution was ~0.25 megapixels and the field of view encompassed approximately 20 individual tree crowns at a distance of 20-40 m. The instrument was focused on a mixed hardwoods canopy composed of 4 deciduous tree species and one coniferous tree species. Scanning was performed daily with an acquisition frequency of 30 minutes during daylight hours. Derived imagery were used to calculate a suite of published spectral indices used to estimate foliar content of key pigments: cholorophyll, carotenoids and anthocyanins. Additionally, we calculated the photochemical reflectance index (PRI) as well as the position and slope of the red edge as indicators of mid- to late-summer plant stress. Changes in the spectral shape and indices throughout the growing season revealed coupling of leaf biochemistry and phenology, as visually observed in situ. Further, the spectrally rich imagery provided well calibrated reflectance data to simulate vegetation index time series of common spaceborne remote sensing platforms such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat. Comparisons between the simulated time series and in situ phenology observations yielded an enhanced interpretation of vegetation indices for determining phenological transition dates. This study demonstrates an advance in our ability to relate canopy phenology to leaf-level dynamics and demonstrates the role that ground-based imaging spectrometry can play in advancing spaceborne remote sensing of vegetation phenology