Guangxing Wang, Simo Poso, Mark-Leo Waite, Markus Holopainen. (1998). The use of digitized aerial photographs and local operation for classification of stand development classes. Silva Fennica vol. 32 no. 3 article id 682. https://doi.org/10.14214/sf.682

Keywords: calibration; classification; digitized aerial photographs; plot window location; local operation

Abstract | View details | Full text in PDF | Author Info

The increasing capacity of modern computers has created the opportunity to routinely process the very large data sets derived by digitizing aerial photographs. The very fine resolution of such data sets makes them better suited than satellite imagery for some applications; however, there may be problems in implementation resulting from variation in radial distortion and illumination across an aerial photograph. We investigated the feasibility of using local operators (e.g., non-overlapping moving window means and standard deviations) as auxiliary data for generating stand development classes via three steps: (i) derive 6 local operators intended to represent texture for a 16 by 16 m window corresponding to a forest inventory sampling unit, (ii) apply a calibration process (e.g., accounting for location relative to a photo's principal point and solar position) to these local operators, and (iii) apply the calibrated local operators to classify the forest for stand development. Results indicate that calibrated local operators significantly improve the classification compared to what is possible using uncalibrated local operators and satellite images.

Wang, Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, IL, USA E-mail: wang12@staff2.cso.uiuc.edu
Poso, Department of Forest Resource Management, P.O. Box 24, FIN-00014 University of Helsinki, Finland E-mail: sp@nn.fi
Waite, Department of Forest Resource Management, P.O. Box 24, FIN-00014 University of Helsinki, Finland E-mail: mlw@nn.fi
Holopainen, Department of Forest Resource Management, P.O. Box 24, FIN-00014 University of Helsinki, Finland E-mail: mh@nn.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

Hagfors E. A. M., (1936) Monographic studies on theory of forestry, part .. Acta Forestalia Fennica vol. 42 no. 7 article id 7324 (remove) | Edit comment

Noordermeer L., Gobakken T. et al. (2025) Effects of sample tree selection and calculation.. Silva Fennica vol. 59 no. 2 article id 25003 (remove) | Edit comment

Matisons R., Šņepsts G. et al. (2018) Dominant height growth of European beech at the .. Silva Fennica vol. 52 no. 1 article id 7818 (remove) | Edit comment

Lindblad J., Routa J. et al. (2018) Weather based moisture content modelling of harv.. Silva Fennica vol. 52 no. 2 article id 7830 (remove) | Edit comment

Tuominen S., Pitkänen T. et al. (2017) Improving Finnish Multi-Source National Forest I.. Silva Fennica vol. 51 no. 4 article id 7743 (remove) | Edit comment

Löyttyniemi K., Hiltunen R. et al. (1982) Monoterpene composition of needle oil of Pinus o.. Silva Fennica vol. 16 no. 4 article id 5167 (remove) | Edit comment

Eriksson G., (1991) Challenges for forest geneticists. Silva Fennica vol. 25 no. 4 article id 5465 (remove) | Edit comment

Pöntynen V., (1936) The consumption of wood in forest manufacturing .. Acta Forestalia Fennica vol. 45 no. 3 article id 7335 (remove) | Edit comment

Hertz M., (1934) Forest Sercvice of Finland in 1859‒1934 Acta Forestalia Fennica vol. 43 no. 1 article id 7327 (remove) | Edit comment

Aro P., (1942) Results of sawing experiments using wooden bow saw Acta Forestalia Fennica vol. 50 no. 21 article id 7374 (remove) | Edit comment

Leinonen I., Hänninen H. (2002) Adaptation of the timing of bud burst of Norway .. Silva Fennica vol. 36 no. 3 article id 534 (remove) | Edit comment

Alho P., (1990) The history of forests in Finland after the last.. Silva Fennica vol. 24 no. 1 article id 5404 (remove) | Edit comment

Samarasinghe S., Kulasiri D. et al. (2007) Neural networks for predicting fracture toughnes.. Silva Fennica vol. 41 no. 1 article id 309 (remove) | Edit comment

Follow @SilvaFennica