Articles | Volume 19, issue 19
https://doi.org/10.5194/bg-19-4747-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-4747-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Oct 2022
Research article |
| 11 Oct 2022
| 11 Oct 2022
Tracking vegetation phenology of pristine northern boreal peatlands by combining digital photography with CO2 flux and remote sensing data
Maiju Linkosalmi
CORRESPONDING AUTHOR
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
Juha-Pekka Tuovinen
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
Olli Nevalainen
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
Mikko Peltoniemi
Bioeconomy and Environment, Natural Resources Institute Finland (Luke), 00790 Helsinki, Finland
Cemal M. Taniş
Arctic Space Centre, Finnish Meteorological Institute, 00560
Helsinki, Finland
Ali N. Arslan
Arctic Space Centre, Finnish Meteorological Institute, 00560
Helsinki, Finland
Juuso Rainne
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
Annalea Lohila
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
Tuomas Laurila
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
Mika Aurela
Climate System Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
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Total article views: 1,831 (including HTML, PDF, and XML)
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Cited
16 citations as recorded by crossref.
- Inter-Annual Variability of Peatland Vegetation Captured Using Phenocam- and UAV Imagery G. Simpson et al. 10.3390/rs17030526
- Upscaling field-measured seasonal ground vegetation patterns with Sentinel-2 images in boreal ecosystems Y. Pang et al. 10.1080/01431161.2023.2234093
- Upscaling peatland mapping with drone-derived imagery: impact of spatial resolution and vegetation characteristics J. Steenvoorden & J. Limpens 10.1080/15481603.2023.2267851
- Fine-Scale Phenology of Urban Trees From Satellite Image Time Series: Toward a Comprehensive Analysis of Influencing Factors C. Bressant et al. 10.1109/JSTARS.2024.3411304
- Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands M. Antala et al. 10.3390/rs17010032
- A Study of Dominant Vegetation Phenology in a Sphagnum Mountain Peatland Using In Situ and Sentinel‐2 Observations R. Garisoain et al. 10.1029/2023JG007403
- Spring phenology in photosynthesis control and modeling for a temperate bog H. He et al. 10.3389/fenvs.2025.1548578
- Reindeer shape soil methanogenic and methanotrophic communities in subarctic fen peatlands, with a minor impact on methane emissions — A field study R. Laiho et al. 10.1016/j.soilbio.2024.109590
- Using a Phenocamera to Monitor Urban Forest Phenology K. Zhang et al. 10.3390/f16020239
- Vegetation phenology patterns in semi-arid savannah woodlands of Gonarezhou National Park, Southeastern Zimbabwe T. Murwendo et al. 10.1016/j.ijgeop.2023.04.003
- Combined Effects of Meteorological Factors, Terrain, and Greenhouse Gases on Vegetation Phenology in Arid Areas of Central Asia from 1982 to 2021 R. Tian et al. 10.3390/land13020180
- Challenges and Limitations of Remote Sensing Applications in Northern Peatlands: Present and Future Prospects A. Abdelmajeed & R. Juszczak 10.3390/rs16030591
- Meteorological responses of carbon dioxide and methane fluxes in the terrestrial and aquatic ecosystems of a subarctic landscape L. Heiskanen et al. 10.5194/bg-20-545-2023
- Tracking photosynthetic phenology using spectral indices at the leaf and canopy scales in temperate evergreen and deciduous trees J. Guo et al. 10.1016/j.agrformet.2023.109809
- Using Spectral Indices Derived from Remote Sensing Imagery to Represent Arthropod Biodiversity Gradients in a European Sphagnum Peat Bog M. Minor et al. 10.3390/arthropoda1010006
- Comparing multispectral and hyperspectral UAV data for detecting peatland vegetation patterns Y. Pang et al. 10.1016/j.jag.2024.104043
16 citations as recorded by crossref.
- Inter-Annual Variability of Peatland Vegetation Captured Using Phenocam- and UAV Imagery G. Simpson et al. 10.3390/rs17030526
- Upscaling field-measured seasonal ground vegetation patterns with Sentinel-2 images in boreal ecosystems Y. Pang et al. 10.1080/01431161.2023.2234093
- Upscaling peatland mapping with drone-derived imagery: impact of spatial resolution and vegetation characteristics J. Steenvoorden & J. Limpens 10.1080/15481603.2023.2267851
- Fine-Scale Phenology of Urban Trees From Satellite Image Time Series: Toward a Comprehensive Analysis of Influencing Factors C. Bressant et al. 10.1109/JSTARS.2024.3411304
- Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands M. Antala et al. 10.3390/rs17010032
- A Study of Dominant Vegetation Phenology in a Sphagnum Mountain Peatland Using In Situ and Sentinel‐2 Observations R. Garisoain et al. 10.1029/2023JG007403
- Spring phenology in photosynthesis control and modeling for a temperate bog H. He et al. 10.3389/fenvs.2025.1548578
- Reindeer shape soil methanogenic and methanotrophic communities in subarctic fen peatlands, with a minor impact on methane emissions — A field study R. Laiho et al. 10.1016/j.soilbio.2024.109590
- Using a Phenocamera to Monitor Urban Forest Phenology K. Zhang et al. 10.3390/f16020239
- Vegetation phenology patterns in semi-arid savannah woodlands of Gonarezhou National Park, Southeastern Zimbabwe T. Murwendo et al. 10.1016/j.ijgeop.2023.04.003
- Combined Effects of Meteorological Factors, Terrain, and Greenhouse Gases on Vegetation Phenology in Arid Areas of Central Asia from 1982 to 2021 R. Tian et al. 10.3390/land13020180
- Challenges and Limitations of Remote Sensing Applications in Northern Peatlands: Present and Future Prospects A. Abdelmajeed & R. Juszczak 10.3390/rs16030591
- Meteorological responses of carbon dioxide and methane fluxes in the terrestrial and aquatic ecosystems of a subarctic landscape L. Heiskanen et al. 10.5194/bg-20-545-2023
- Tracking photosynthetic phenology using spectral indices at the leaf and canopy scales in temperate evergreen and deciduous trees J. Guo et al. 10.1016/j.agrformet.2023.109809
- Using Spectral Indices Derived from Remote Sensing Imagery to Represent Arthropod Biodiversity Gradients in a European Sphagnum Peat Bog M. Minor et al. 10.3390/arthropoda1010006
- Comparing multispectral and hyperspectral UAV data for detecting peatland vegetation patterns Y. Pang et al. 10.1016/j.jag.2024.104043
Latest update: 16 May 2025
Short summary
Vegetation greenness was monitored with digital cameras in three northern peatlands during five growing seasons. The greenness index derived from the images was highest at the most nutrient-rich site. Greenness indicated the main phases of phenology and correlated with CO2 uptake, though this was mainly related to the common seasonal cycle. The cameras and Sentinel-2 satellite showed consistent results, but more frequent satellite data are needed for reliable detection of phenological phases.
Vegetation greenness was monitored with digital cameras in three northern peatlands during five...
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