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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles by Ville Kankare

Category: Research note

article id 9986, category Research note
Ninni Saarinen, Joanne C. White, Michael A. Wulder, Annika Kangas, Sakari Tuominen, Ville Kankare, Markus Holopainen, Juha Hyyppä, Mikko Vastaranta. (2018). Landsat archive holdings for Finland: opportunities for forest monitoring. Silva Fennica vol. 52 no. 3 article id 9986. https://doi.org/10.14214/sf.9986
Highlights: The 45-year Landsat archive contained 30 076 images for Finland by December 31, 2017; 16.3% of these were acquired within ±30 days of August 1 (northern hemisphere summer), have <70% cloud cover, and a 30 m spatial resolution; Using time series analyses, these data provide unique information that complements other datasets available for forest monitoring and assessment in Finland.

There is growing interest in the use of Landsat data to enable forest monitoring over large areas. Free and open data access combined with high performance computing have enabled new approaches to Landsat data analysis that use the best observation for any given pixel to generate an annual, cloud-free, gap-free, surface reflectance image composite. Finland has a long history of incorporating Landsat data into its National Forest Inventory to produce forest information in the form of thematic maps and small area statistics on a variety of forest attributes. Herein we explore the spatial and temporal characteristics of the Landsat archive in the context of forest monitoring in Finland. The United States Geological Survey Landsat archive holds a total of 30 076 images (1972–2017) for 66 scenes (each 185 km by 185 km in size) representing the terrestrial area of Finland, of which 93.6% were acquired since 1984 with a spatial resolution of 30 m. Approximately 16.3% of the archived images have desired compositing characteristics (acquired within August 1 ±30 days, <70% cloud cover, 30 m spatial resolution). Data from the Landsat archive can augment forest monitoring efforts in Finland, provide new information for science and applications, and enable retrospective, systematic analyses to characterize the development of Finnish forests over the past three decades. The capacity to monitor trends based upon this multi-decadal record with the addition of new measurements is of benefit to multisource inventories and offers nationally comprehensive spatially-explicit datasets for a wide range of stakeholders and applications.

  • Saarinen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland; School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID: https://orcid.org/0000-0003-2730-8892 E-mail: ninni.saarinen@helsinki.fi (email)
  • White, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland; Canadian Forest Service, (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada ORCID ID: http://orcid.org/0000-0003-4674-0373 E-mail: joanne.white@canada.ca
  • Wulder, Canadian Forest Service, (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada ORCID ID: https://orcid.org/0000-0002-6942-1896 E-mail: mike.wulder@canada.ca
  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland ORCID ID:E-mail: annika.kangas@luke.fi
  • Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID ID:E-mail: sakari.tuominen@luke.fi
  • Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: ville.kankare@helsinki.fi
  • Holopainen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: markus.holopainen@helsinki.fi
  • Hyyppä, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02431 Masala, Finland ORCID ID:E-mail: juha.hyyppa@nls.fi
  • Vastaranta, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID: https://orcid.org/0000-0001-6552-9122 E-mail: mikko.vastaranta@uef.fi
article id 1125, category Research note
Anssi Krooks, Sanna Kaasalainen, Ville Kankare, Marianna Joensuu, Pasi Raumonen, Mikko Kaasalainen. (2014). Predicting tree structure from tree height using terrestrial laser scanning and quantitative structure models. Silva Fennica vol. 48 no. 2 article id 1125. https://doi.org/10.14214/sf.1125
Highlights: The analysis of tree structure suggests that trees of different height growing in similar conditions have similar branch size distributions; There is potential for using the tree height information in large-scale estimations of forest canopy structure.
We apply quantitative structure modelling to produce detailed information on branch-level metrics in trees. Particularly we are interested in the branch size distribution, by which we mean the total volume of branch parts distributed over the diameter classes of the parts. We investigate the possibility of predicting tree branch size distributions for trees in similar growing conditions. The quantitative structure model enables for the first time the comparisons of structure between a large number of trees. We found that the branch size distribution is similar for trees of different height in similar growing conditions. The results suggest that tree height could be used to estimate branch size distribution in areas with similar growing conditions and topography.
  • Krooks, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland ORCID ID:E-mail: Anssi.Krooks@fgi.fi
  • Kaasalainen, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland ORCID ID:E-mail: Sanna.Kaasalainen@fgi.fi (email)
  • Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland ORCID ID:E-mail: ville.kankare@helsinki.fi
  • Joensuu, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland ORCID ID:E-mail: marianna.joensuu@alumni.helsinki.fi
  • Raumonen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland ORCID ID:E-mail: Pasi.Raumonen@tut.fi
  • Kaasalainen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland ORCID ID:E-mail: Mikko.Kaasalainen@tut.fi

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