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Articles by Markus Haakana

Category: Research article

article id 458, category Research article
Sakari Tuominen, Kalle Eerikäinen, Anett Schibalski, Markus Haakana, Aleksi Lehtonen. (2010). Mapping biomass variables with a multi-source forest inventory technique. Silva Fennica vol. 44 no. 1 article id 458. https://doi.org/10.14214/sf.458
Map form information on forest biomass is required for estimating bioenergy potentials and monitoring carbon stocks. In Finland, the growing stock of forests is monitored using multi-source forest inventory, where variables are estimated in the form of thematic maps and area statistics by combining information of field measurements, satellite images and other digital map data. In this study, we used the multi-source forest inventory methodology for estimating forest biomass characteristics. The biomass variables were estimated for national forest inventory field plots on the basis of measured tree variables. The plot-level biomass estimates were used as reference data for satellite image interpretation. The estimates produced by satellite image interpretation were tested by cross-validation. The results indicate that the method for producing biomass maps on the basis of biomass models and satellite image interpretation is operationally feasible. Furthermore, the accuracy of the estimates of biomass variables is similar or even higher than that of traditional growing stock volume estimates. The technique presented here can be applied, for example, in estimating biomass resources or in the inventory of greenhouse gases.
  • Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: sakari.tuominen@metla.fi (email)
  • Eerikäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Schibalski, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany ORCID ID:E-mail:
  • Haakana, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
  • Lehtonen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
article id 367, category Research article
Sakari Tuominen, Markus Haakana. (2005). Landsat TM imagery and high altitude aerial photographs in estimation of forest characteristics. Silva Fennica vol. 39 no. 4 article id 367. https://doi.org/10.14214/sf.367
Satellite sensor data have traditionally been used in multi-source forest inventory for estimating forest characteristics. Their advantages generally are large geographic coverage and large spectral range. Another remote sensing data source for forest inventories offering a large geographic coverage is high altitude aerial photography. In high altitude aerial photographs the spectral range is very narrow but the spatial resolution is high. This allows the extraction of texture features for forest inventory purposes. In this study we utilized a Landsat 7 ETM satellite image, a photo mosaic composed of high altitude panchromatic aerial photographs, and a combination of the aforementioned in estimating forest attributes for an area covering approximately 281 000 ha in Forestry Centre Häme-Uusimaa in Southern Finland. Sample plots of 9th National Forest Inventory (NFI9) were used as field data. In the estimation, 6 Landsat 7 ETM image channels were used. For aerial photographs, 4 image channels were composed from the spectral averages and texture features. In combining both data sources, 6 Landsat channels and 3 aerial image texture channels were selected for the analysis. The accuracy of forest estimates based on the Landsat image was better than that of estimates based on high altitude aerial photographs. On the other hand, using the combination of Landsat ETM spectral features and textural features on high altitude aerial photographs improved the estimation accuracy of most forest attributes.
  • Tuominen, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland ORCID ID:E-mail: sakari.tuominen@metla.fi (email)
  • Haakana, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland ORCID ID:E-mail:

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