Articles | Volume 13, issue 7
https://doi.org/10.5194/essd-13-3593-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-3593-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A distributed time-lapse camera network to track vegetation phenology with high temporal detail and at varying scales
Frans-Jan W. Parmentier
CORRESPONDING AUTHOR
Center for Biogeochemistry in the Anthropocene, Department of Geosciences, University of Oslo, Oslo, 0315, Norway
Department of Physical Geography and Ecosystem Science, Lund University, Lund, 223 62, Sweden
Department of Arctic and Marine Biology, UiT – The Arctic University of Norway, Tromsø, 9037, Norway
Lennart Nilsen
Department of Arctic and Marine Biology, UiT – The Arctic University of Norway, Tromsø, 9037, Norway
Hans Tømmervik
Norwegian Institute of Nature Research (NINA), FRAM – High North Centre for Climate and the Environment, Tromsø, 9296, Norway
Elisabeth J. Cooper
Department of Arctic and Marine Biology, UiT – The Arctic University of Norway, Tromsø, 9037, Norway
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Cited
15 citations as recorded by crossref.
- Time-Series of Cloud-Free Sentinel-2 NDVI Data Used in Mapping the Onset of Growth of Central Spitsbergen, Svalbard S. Karlsen et al. https://doi.org/10.3390/rs13153031
- Remote Sensing of Climate-Vegetation Dynamics and Their Effects on Ecosystems C. Chang et al. https://doi.org/10.3390/rs15215097
- Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska D. Yang et al. https://doi.org/10.1088/2752-664X/ad9eb8
- Improving ecological insights from dendroecological studies of Arctic shrub dynamics: Research gaps and potential solutions C. Power et al. https://doi.org/10.1016/j.scitotenv.2022.158008
- Visualizing seasonal habitats in river floodplains using timelapse photography and underwater video K. Myrvold & T. Holter https://doi.org/10.1007/s00027-025-01238-3
- The changing face of the Arctic: four decades of greening and implications for tundra ecosystems G. Frost et al. https://doi.org/10.3389/fenvs.2025.1525574
- Summer temperature—but not growing season length—influences radial growth of Salix arctica in coastal Arctic tundra J. Boyle et al. https://doi.org/10.1007/s00300-022-03074-9
- Comparative Performance Evaluation of Low-Cost, Continuous, Field-Deployable Trail Cameras for Agricultural Field Monitoring D. Suresh Babu et al. https://doi.org/10.3390/agriengineering8110452
- Towards crop monitoring in agro-photovoltaic systems: An image-driven modeling approach for fAPAR-derived biomass estimation M. Moretta et al. https://doi.org/10.1016/j.eja.2025.127748
- Initial Results of Site-Specific Assessment of Cereal Leaf Beetle (Oulema melanopus L.) Damage Using RGB Images by UAV F. Sári-Barnácz et al. https://doi.org/10.3390/rs18010058
- Opportunities and Challenges in Combining Optical Sensing and Epidemiological Modeling A. Mikaberidze et al. https://doi.org/10.1094/PHYTO-11-24-0359-FI
- Predictive modeling, pattern recognition, and spatiotemporal representations of plant growth in simulated and controlled environments: A comprehensive review M. Debbagh et al. https://doi.org/10.1016/j.plaphe.2025.100089
- Leaf phenology as an indicator of ecological integrity L. Spafford et al. https://doi.org/10.1002/ecs2.4487
- The northernmost hyperspectral FLoX sensor dataset for monitoring of high-Arctic tundra vegetation phenology and Sun-Induced Fluorescence (SIF) H. Tømmervik et al. https://doi.org/10.1016/j.dib.2023.109581
- Winters are changing: snow effects on Arctic and alpine tundra ecosystems C. Rixen et al. https://doi.org/10.1139/as-2020-0058
15 citations as recorded by crossref.
- Time-Series of Cloud-Free Sentinel-2 NDVI Data Used in Mapping the Onset of Growth of Central Spitsbergen, Svalbard S. Karlsen et al. https://doi.org/10.3390/rs13153031
- Remote Sensing of Climate-Vegetation Dynamics and Their Effects on Ecosystems C. Chang et al. https://doi.org/10.3390/rs15215097
- Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska D. Yang et al. https://doi.org/10.1088/2752-664X/ad9eb8
- Improving ecological insights from dendroecological studies of Arctic shrub dynamics: Research gaps and potential solutions C. Power et al. https://doi.org/10.1016/j.scitotenv.2022.158008
- Visualizing seasonal habitats in river floodplains using timelapse photography and underwater video K. Myrvold & T. Holter https://doi.org/10.1007/s00027-025-01238-3
- The changing face of the Arctic: four decades of greening and implications for tundra ecosystems G. Frost et al. https://doi.org/10.3389/fenvs.2025.1525574
- Summer temperature—but not growing season length—influences radial growth of Salix arctica in coastal Arctic tundra J. Boyle et al. https://doi.org/10.1007/s00300-022-03074-9
- Comparative Performance Evaluation of Low-Cost, Continuous, Field-Deployable Trail Cameras for Agricultural Field Monitoring D. Suresh Babu et al. https://doi.org/10.3390/agriengineering8110452
- Towards crop monitoring in agro-photovoltaic systems: An image-driven modeling approach for fAPAR-derived biomass estimation M. Moretta et al. https://doi.org/10.1016/j.eja.2025.127748
- Initial Results of Site-Specific Assessment of Cereal Leaf Beetle (Oulema melanopus L.) Damage Using RGB Images by UAV F. Sári-Barnácz et al. https://doi.org/10.3390/rs18010058
- Opportunities and Challenges in Combining Optical Sensing and Epidemiological Modeling A. Mikaberidze et al. https://doi.org/10.1094/PHYTO-11-24-0359-FI
- Predictive modeling, pattern recognition, and spatiotemporal representations of plant growth in simulated and controlled environments: A comprehensive review M. Debbagh et al. https://doi.org/10.1016/j.plaphe.2025.100089
- Leaf phenology as an indicator of ecological integrity L. Spafford et al. https://doi.org/10.1002/ecs2.4487
- The northernmost hyperspectral FLoX sensor dataset for monitoring of high-Arctic tundra vegetation phenology and Sun-Induced Fluorescence (SIF) H. Tømmervik et al. https://doi.org/10.1016/j.dib.2023.109581
- Winters are changing: snow effects on Arctic and alpine tundra ecosystems C. Rixen et al. https://doi.org/10.1139/as-2020-0058
Saved (final revised paper)
Latest update: 02 Nov 2026
Short summary
Satellites provide a global overview of Earth's ecosystems, but they have coarse resolutions and low revisit times. Small-scale vegetation patterns and sudden shifts in plant growth can easily be missed. In this paper, we show how to fill these gaps with vegetation indices obtained with ordinary time-lapse cameras deployed across a valley on Svalbard. We show how to adjust for unwanted camera movement and that vegetation indices from ordinary cameras compare well to those used by satellites.
Satellites provide a global overview of Earth's ecosystems, but they have coarse resolutions and...
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