Articles | Volume 10, issue 1
Earth Syst. Sci. Data, 10, 173–184, 2018
Earth Syst. Sci. Data, 10, 173–184, 2018

  25 Jan 2018

25 Jan 2018

Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

Mikko Peltoniemi1, Mika Aurela2, Kristin Böttcher3, Pasi Kolari4, John Loehr5, Jouni Karhu6, Maiju Linkosalmi2, Cemal Melih Tanis2, Juha-Pekka Tuovinen2, and Ali Nadir Arslan2 Mikko Peltoniemi et al.
  • 1Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790, Helsinki, Finland
  • 2Finnish Meteorological Institute, Erik Palménin aukio 1, 00560 Helsinki, Finland
  • 3Finnish Environment Institute (SYKE), Mechelininkatu 34a, 00251 Helsinki, Finland
  • 4Department of Physics, University of Helsinki, P.O. Box 68, 00014 Helsinki, Finland
  • 5Lammi Biological Station, University of Helsinki, Pääjärventie 320, 16900 Lammi, Finland
  • 6Natural Resources Institute Finland (Luke), Paavo Havaksen tie 3, 90014 Oulun yliopisto, Finland

Abstract. In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository ( Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 ( Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

Short summary
Monitoring ecosystems using low-cost time lapse cameras has gained wide interest among researchers worldwide. Quantitative information stored in image pixels can be analysed automatically to track time-dependent phenomena, e.g. seasonal course of leaves in the canopies or snow on ground. As such, cameras can provide valuable ground references to earth observation. Here we document the ecosystem camera network we established to Finland and publish time series of images recorded between 2014–2016.