Tracking vegetation phenology of pristine northern boreal peatlands by combining digital photography with CO<sub>2</sub> flux and remote sensing data

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Abstract 2) exchange between ecosystems and the atmosphere. We employed digital cameras to monitor the vegetation phenology of three northern boreal peatlands during five growing seasons. We derived a greenness index (green chromatic coordinate, GCC) from the images and combined the results with measurements of CO2 flux, air temperature and high-resolution satellite data (Sentinel-2). From the digital camera images it was possible to extract greenness dynamics on the vegetation community and even species level. The highest GCC and daily maximum gross photosynthetic production (GPPmax) were observed at the site with the highest nutrient availability and richest vegetation. The short-term temperature response of GCC depended on temperature and varied among the sites and months. Although the seasonal development and year-to-year variation in GCC and GPPmax showed consistent patterns, the short-term variation in GPPmax was explained by GCC only during limited periods. GCC clearly indicated the main phases of the growing season, and peatland vegetation showed capability to fully compensate for the impaired growth resulting from a late growing season start. The GCC data derived from Sentinel-2 and digital cameras showed similar seasonal courses, but a reliable timing of different phenological phases depended upon the temporal coverage of satellite data.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Tracking vegetation phenology of pristine northern boreal peatlands by combining digital photography with CO2 flux and remote sensing data ; volume:19 ; number:19 ; year:2022 ; pages:4747-4765 ; extent:19
Biogeosciences ; 19, Heft 19 (2022), 4747-4765 (gesamt 19)

Creator
Linkosalmi, Maiju
Tuovinen, Juha-Pekka
Nevalainen, Olli
Peltoniemi, Mikko
Taniş, Cemal M.
Arslan, Ali N.
Rainne, Juuso
Lohila, Annalea
Laurila, Tuomas
Aurela, Mika

DOI
10.5194/bg-19-4747-2022
URN
urn:nbn:de:101:1-2022101305153399114278
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:28 AM CEST

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Associated

  • Linkosalmi, Maiju
  • Tuovinen, Juha-Pekka
  • Nevalainen, Olli
  • Peltoniemi, Mikko
  • Taniş, Cemal M.
  • Arslan, Ali N.
  • Rainne, Juuso
  • Lohila, Annalea
  • Laurila, Tuomas
  • Aurela, Mika

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