Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns

Reference:

Mikko Korpela, Harri Mäkinen, Mika Sulkava, Pekka Nöjd, and Jaakko Hollmén. Smoothed prediction of the onset of tree stem radius increase based on temperature patterns. In Jean-Fran cois Boulicaut, Michael R Berthold, and Tamás Horváth, editors, Discovery Science, Proc. 11th Intl. Conf., DS 2008, volume 5255 of LNAI, pages 100–111. Springer, 2008.

Abstract:

Possible changes of the growing season of trees would have significant consequences on forest production. Predicting the onset of tree growth on the basis of climate records can be used for estimating the magnitude of such changes. Conventional methods for estimating the onset of tree growth use cumulative temperature sums. These estimates, however, are quite coarse, and raise questions about making better use of the weather information available. We approach the problem of predicting the onset of tree growth with a predictor based on a combination of a k-nearest neighbor regressor and a linear regressor. The inputs are weighted sums of daily temperatures, where the weights are determined by a subset of Bernstein polynomials chosen with a variable selection methodology. The predictions are smoothed for consecutive days to give more accurate results. We compare our proposed solution to the more conventional approach. The proposed solution is found to be better.

Suggested BibTeX entry:

@inproceedings{KoMaEtc2008,
    author = {Mikko Korpela and Harri M{\"a}kinen and Mika Sulkava and Pekka N{\"o}jd and Jaakko Hollm{\'e}n},
    booktitle = {Discovery Science, Proc. 11th Intl. Conf., DS 2008},
    editor = {Boulicaut, Jean-Fran{\c c}ois and Berthold, Michael R and Horv{\'a}th, Tam{\'a}s},
    pages = {100--111},
    publisher = {Springer},
    series = {LNAI},
    title = {Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns},
    volume = {5255},
    year = {2008},
}