Current issue: 53(3)

Under compilation: 53(4)

Impact factor 1.683
5-year impact factor 1.950
Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
Acta Forestalia Fennica
1953-1968
1933-1952
1913-1932

Articles containing the keyword 'UAVs'.

Category: Research article

article id 7721, category Research article
Sakari Tuominen, Andras Balazs, Eija Honkavaara, Ilkka Pölönen, Heikki Saari, Teemu Hakala, Niko Viljanen. (2017). Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables. Silva Fennica vol. 51 no. 5 article id 7721. https://doi.org/10.14214/sf.7721
Highlights: Hyperspectral imagery and photogrammetric 3D point cloud based on RGB imagery were acquired under weather conditions changing from cloudy to sunny; Calibration of hyperspectral imagery was required for compensating the effect of varying weather conditions; The combination of hyperspectral imagery and photogrammetric point cloud data resulted in accurate forest estimates, especially for volumes per tree species.

Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest variables of 298 sample plots. Data were captured from eleven separate test sites under weather conditions varying from sunny to cloudy and partially cloudy. Both calibrated hyperspectral reflectance images and uncalibrated imagery were tested in combination with a canopy height model based on RGB camera imagery using the k-nearest neighbour estimation method. The results indicate that this data combination allows accurate estimation of stand volume, mean height and diameter: the best relative RMSE values for those variables were 22.7%, 7.4% and 14.7%, respectively. In estimating volume and dimension-related variables, the use of a calibrated image mosaic did not bring significant improvement in the results. In estimating the volumes of individual tree species, the use of calibrated hyperspectral imagery generally brought marked improvement in the estimation accuracy; the best relative RMSE values for the volumes for pine, spruce, larch and broadleaved trees were 34.5%, 57.2%, 45.7% and 42.0%, respectively.

  • Tuominen, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID: http://orcid.org/0000-0001-5429-3433 E-mail: sakari.tuominen@luke.fi (email)
  • Balazs, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: andras.balazs@luke.fi
  • Honkavaara, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland ORCID ID:E-mail: eija.honkavaara@nls.fi
  • Pölönen, University of Jyväskylä, Faculty of Information Technology, P.O. Box 35, FI-40014 Jyväskylä, Finland ORCID ID:E-mail: ilkka.polonen@jyu.fi
  • Saari, VTT Microelectronics, P.O. Box 1000, FI-02044 VTT, Finland ORCID ID:E-mail: heikki.saari@vtt.fi
  • Hakala, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland ORCID ID:E-mail: teemu.hakala@nls.fi
  • Viljanen, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland ORCID ID:E-mail: niko.viljanen@nls.fi

Register
Click this link to register for Silva Fennica submission and tracking system.
Log in
If you are a registered user, log in to save your selected articles for later access.
Contents alert
Sign up to receive alerts of new content
Your selected articles

Committee on Publication Ethics A Trusted Community-Governed Archive