%0 Research article
%T The use of digitized aerial photographs and local operation for classification of stand development classes
%A Wang, Guangxing
%A Poso, Simo
%A Waite, Mark-Leo
%A Holopainen, Markus
%D 1998
%J Silva Fennica
%V 32
%N 3
%R doi:10.14214/sf.682
%U https://silvafennica.fi/article/682
%X 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.