Establishment of an automatic system for monitoring vegetation and environmental seasonal changes on Svalbard. (ASMoVEn)

The major project aim is to establish a distributed set of reference point for long time serial monitoring of vegetation-environment changes on Svalbard.

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Project type

  • field work
  • remote sensing
  • long-term monitoring


  • terrestrial biology
  • space physics

Project Keywords

  • biosphere / terrestrial ecosystems / alpine/tundra
  • biosphere / vegetation / plant phenology
  • land surface / landscape / landscape patterns
  • spectral/engineering / visible wavelengths / visible imagery
  • biosphere / vegetation / vegetation index

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Numerous satellites are continuously monitoring the arctic and an overwhelming amount of environmental remote sensing data are collected in northern areas. However, analysing and application of these data calls for information on processes and changes taking place on the ground. There is an urgent need for ground truth data. Available in situ data on Svalbard are scarce, lack coordinated methodology, and long-term time series of environmental parameters are highly requested. However, there are initiatives on environmental and vegetation monitoring taking place in Hornsund, Adventdalen and Ny-Ålesund. All three locations have ongoing interdisciplinary research projects and existing infrastructure for monitoring seasonal changes in snow and vegetation. The major project aim is to establish a distributed set of reference point for long time serial monitoring of vegetation-environment changes on Svalbard. The study design is based on a) permanent plots where 2 m tall racks are equipped with automatic time-laps cameras are data loggers sampling environmental data, and b) high resolution time-laps camera mounted up in the mountainside surveying the study areas. Furthermore, we want to improve cooperation between the Hornsund, Adventdalen and Ny-Ålesund research groups, harmonizing of methodology and instruments for monitoring seasonal changes, and sharing information to strengthen analysis with larger and more representative, spatial distributed data sets. Hence, this project will provide ground reference data for the remote sensing community as well as advance current knowledge within the field of plant ecology. The racks and landscape cameras provide crucial data for analysing relationships between vegetation indices (NDVI, EVI, PRI and others), temperature sums and length of growing season, plant phenology and plant productivity for the main vegetation types in terrestrial tundra ecosystems. Project metadata will be provided and implemented in the SIOS data management system service.

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