Simo Poso, Mark-Leo Waite. (1995). Calculation and comparison of different permanent sample plot types . Silva Fennica vol. 29 no. 2 article id 5554. https://doi.org/10.14214/sf.a9205

Keywords: forest inventories; forest monitoring; sampling; optimum sampling unit; permanent plot analysis

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A calculation procedure is presented for calculating and analysing remeasured permanent sample plots. Data for eight different fixed and variable size plot types were simulated on the basis of two stands whose trees were mapped and measured in 1982 and 1986. The accuracy and efficiency of the plot types were assessed and compared.

The calculation procedure is based on tree-wise expansion factors and the division of tree sampled into state/measurement classes. Nine classes were required for variable size plots and six for fixed size plots. A relascope plot with basal-area factor 1 (m²/ha) proved to be most efficient for estimating basal-area at a given time and a fixed size circular plot with radius 10 m for estimating basal-area increment over a given time period.

The main problems were related to the estimation of non-measurable variables, e.g., the initial diameters of ingrowth trees, i.e., trees having passed the threshold size during the measurement period. Most problematic were cut trees belonging to the ingrowth or sample enlargement classes. It is nevertheless thought that the system is appropriate for monitoring forest changes and making sensitivity analyses with permanent sample plots.

Poso, E-mail: sp@mm.unknown
Waite, E-mail: mw@mm.unknown

Category : Research article

article id 682, category Research article

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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