Monitoring pigment-driven vegetation changes in a low-Arctic tundra ecosystem using digital cameras
Autor: | Nicholas C. Coops, Txomin Hermosilla, Sabine Chabrillat, Alison Beamish, Birgit Heim |
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Rok vydání: | 2018 |
Předmět: |
0106 biological sciences
Chlorophyll a 010504 meteorology & atmospheric sciences Ecology Phenology Growing season Climate change 15. Life on land 010603 evolutionary biology 01 natural sciences Tundra chemistry.chemical_compound chemistry 13. Climate action medicine Environmental science Ecosystem sense organs Physical geography Arctic vegetation medicine.symptom Vegetation (pathology) Ecology Evolution Behavior and Systematics 0105 earth and related environmental sciences |
Zdroj: | Ecosphere |
Popis: | 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 have 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 colour, 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 (RMSE). 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 colour 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 status and changes related to seasonal foliar condition and photosynthetic activity in three dominant, low-Arctic vegetation communities. |
Databáze: | OpenAIRE |
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