Current issue: 55(3)

Under compilation: 55(4)

Scopus CiteScore 2019: 3.1
Scopus ranking of open access forestry journals: 6th
PlanS compliant
Silva Fennica 1926-1997
Acta Forestalia Fennica

Articles containing the keyword 'calibration estimator'.

Category: Research article

article id 368, category Research article
Eero Muinonen. (2005). Generating a raster map presentation of a forest resource by solving a transportation problem. Silva Fennica vol. 39 no. 4 article id 368.
Necessary tools for raster map generation, for the approach based on the calibration estimator, were developed and implemented. The allocation of the area weight of each pixel to sample plots was formulated as a transportation problem, using a spectral distance measure as a transportation cost, and solved using the transportation simplex algorithm. Pixel level accuracy was calculated for the methods based on the calibration estimator so that the results could be compared with the results of the nearest neighbour estimation, the reference sample plot method (RSP) at pixel level. Local averaging in a 3 x 3 window was performed for each generated raster map as a postprocessing phase to smooth the map. Test plot results were calculated both for the unfiltered raster map and the filtered raster map. RSP produced the smallest RMSE in the pooled test data. Local averaging with a 3 x 3 filter decreased the pixel level error – and the bias – and the differences between the methods are smaller. Without local averaging, the pixel level errors of the methods based on solving the transportation problem were high. Raster map generation using the methods of this study forms an optional part – followed possibly by the classification of the pixel level results – of the whole computation task, when the area weight computation is based on the calibration estimation. For larger areas than in the present study, such as municipalities, the efficiency of the method based on the transportation model must be improved before it is a usable tool, in practice, for raster map generation. For nearest neighbour methods, the area size is not such a problem, because the inventory area is processed pixel by pixel.
  • Muinonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: (email)

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