Ilkka Korpela, Lauri Mehtätalo, Lauri Markelin, Anne Seppänen, Annika Kangas. (2014). Tree species identification in aerial image data using directional reflectance signatures. Silva Fennica vol. 48 no. 3 article id 1087. https://doi.org/10.14214/sf.1087

Keywords: forestry; reflectance calibration; BRDF; mixed-effects modeling; Monte-Carlo simulation

Highlights: Multispectral reflectance data showed a strong and spectrally correlated tree effect; There was no gain in species classification from using species-specific differences of directional reflectance in real data and only a marginal improvement in simulated data; The directional signatures extracted in multiple images are obscured by the intrinsic within-species variation, correlated observations and inherent reflectance calibration errors.

Abstract | Full text in HTML | Full text in PDF | Author Info

Tree species identification using optical remote sensing is challenging. Modern digital photogrammetric cameras enable radiometrically quantitative remote sensing and the estimation of reflectance images, in which the observations depend largely on the reflectance properties of targets. Previous research has shown that there are species-specific differences in how the brightness observed changes when the viewing direction in an aerial image is altered. We investigated if accounting for such directional signatures enhances species classification, using atmospherically corrected, real and simulated multispectral Leica ADS40 line-camera data. Canopy in direct and diffuse illumination were differentiated and species-specific variance-covariance structures were analyzed in real reflectance data, using mixed-effects modeling. Species classification simulations aimed at elucidating the level of accuracy that can be achieved by using images of different quality, number and view-illumination geometry. In real data, a substantial variance component was explained by tree effect, which demonstrates that observations from a tree correlate between observation geometries as well as spectrally. Near-infrared band showed the strongest tree effect, while the directionality was weak in that band. The gain from directional signatures was insignificant in real data, while simulations showed a potential gain of 1–3 percentage points in species classification accuracy. The quality of reflectance calibration was found to be important as well as the image acquisition geometry. We conclude that increasing the number of image observations cancels out random observation noise and reflectance calibration errors, but fails to eliminate the tree effect and systematic calibration inaccuracy. Directional reflectance constitutes a marginal improvement in tree species classification.

Korpela, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland E-mail: ilkka.korpela@helsinki.fi
Mehtätalo, Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lauri.mehtatalo@uef.fi
Markelin, Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland E-mail: lauri.markelin@fgi.fi
Seppänen, Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: anne.seppanen@arbonaut.com
Kangas, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland E-mail: annika.kangas@helsinki.fi

Click this link to register to Silva Fennica.

If you are a registered user, log in to save your selected articles for later access.

Contents alert

Your selected articles
Send to email

Matala J., Kilpeläinen H. et al. (2020) Sawlog quality and tree dimensions of Scots pine.. Silva Fennica vol. 54 no. 3 article id 10389 (remove) | Edit comment

Ryynänen M., (1980) X-ray radiography of ageing Scots pine seeds. Silva Fennica vol. 14 no. 1 article id 5071 (remove) | Edit comment

Lintunen A., (2023) Passion for science Silva Fennica vol. 57 no. 2 article id 23043 (remove) | Edit comment

Lakari O. J., (1920) Studies on forest site types in Northern Finland Acta Forestalia Fennica vol. 14 no. 4 article id 7037 (remove) | Edit comment

Laurén A., (2026) Weight of a Name Silva Fennica vol. 60 no. 1 article id 26022 (remove) | Edit comment

Mikola P., Kangas E. et al. (1959) Silvicultural research in Finland from 1901 to 1.. Acta Forestalia Fennica vol. 70 no. 3 article id 7493 (remove) | Edit comment

Novitskaya L., Nikolaeva N. et al. (2016) The greatest density of parenchyma inclusions in.. Silva Fennica vol. 50 no. 3 article id 1461 (remove) | Edit comment

Tokola T., Heikkilä J. (1997) Improving satellite image based forest inventory.. Silva Fennica vol. 31 no. 1 article id 5610 (remove) | Edit comment

Kangas A., Gobakken T. et al. (2018) Value of airborne laser scanning and digital aer.. Silva Fennica vol. 52 no. 1 article id 9923 (remove) | Edit comment

Fabra Crespo M., Saastamoinen O. et al. (2015) Perceptions and realities: public opinion on for.. Silva Fennica vol. 48 no. 5 article id 1140 (remove) | Edit comment

Siipilehto J., Allen M. et al. (2020) Stand-level mortality models for Nordic boreal f.. Silva Fennica vol. 54 no. 5 article id 10414 (remove) | Edit comment

Harstela P., Tervo L. (1978) Comparison of methods for harvesting in sapling .. Silva Fennica vol. 12 no. 2 article id 4991 (remove) | Edit comment

Lachowicz H., Bieniasz A. et al. (2019) Variability in the basic density of silver birch.. Silva Fennica vol. 53 no. 1 article id 9968 (remove) | Edit comment

Lindroos A.-J., Ryhti K. et al. (2019) Leaching of heavy metals and barium from forest .. Silva Fennica vol. 53 no. 2 article id 10088 (remove) | Edit comment

Wallius V., Kunttu J. et al. (2024) Attractiveness of wood-frame multi-storey buildi.. Silva Fennica vol. 58 no. 5 article id 23035 (remove) | Edit comment

Follow @SilvaFennica