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

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