Monitoring pigment‐driven vegetation changes in a low‐Arctic tundra ecosystem using digital cameras

• Published in: Ecosphere
• Main Authors: Beamish, Alison L., Coops, Nicholas C., Hermosilla, Txomin, Chabrillat, Sabine, Heim, Birgit
• Other Authors: Natural Sciences and Engineering Research Council of Canada
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2018
• Subjects: Arctic; north slope; Tundra; Alaska
• Online Access: http://dx.doi.org/10.1002/ecs2.2123; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2123; https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2123

Abstract Arctic vegetation phenology is a sensitive indicator of a changing climate, and rapid assessment of vegetation status is necessary to more comprehensively understand the impacts on foliar condition and photosynthetic activity. Airborne and space‐borne optical remote sensing has been successfully used to monitor vegetation phenology in Arctic ecosystems by exploiting the biophysical and biochemical changes associated with vegetation growth and senescence. However, persistent cloud cover and low sun angles in the region make the acquisition of high‐quality temporal optical data within one growing season challenging. In the following study, we examine the capability of “near‐field” remote sensing technologies, in this case digital, true‐color cameras to produce surrogate in situ spectral data to characterize changes in vegetation driven by seasonal pigment dynamics. Simple linear regression was used to investigate relationships between common pigment‐driven spectral indices calculated from field‐based spectrometry and red, green, and blue ( RGB ) indices from corresponding digital photographs in three dominant vegetation communities across three major seasons at Toolik Lake, North Slope, Alaska. We chose the strongest and most consistent RGB index across all communities to represent each spectral index. Next, linear regressions were used to relate RGB indices and extracted leaf‐level pigment content with a simple additive error propagation of the root mean square error. Results indicate that the green‐based RGB indices had the strongest relationship with chlorophyll a and total chlorophyll, while a red‐based RGB index showed moderate relationships with the chlorophyll to carotenoid ratio. The results suggest that vegetation color contributes strongly to the response of pigment‐driven spectral indices and RGB data can act as a surrogate to track seasonal vegetation change associated with pigment development and degradation. Overall, we find that low‐cost, easy‐to‐use digital cameras can monitor vegetation ...