Automatic detection of onset and cessation of tree stem radius increase using dendrometer data

Authors:
Mikko Korpela;Harri Mäkinen;Pekka Nöjd;Jaakko Hollmén;Mika Sulkava
Affiliations:
Aalto University School of Science and Technology, Department of Information and Computer Science, P.O. Box 15400, FI-00076 Aalto, Finland;Finnish Forest Research Institute - Southern Finland Regional Unit, P.O. Box 18, FI-01301 Vantaa, Finland;Finnish Forest Research Institute - Southern Finland Regional Unit, P.O. Box 18, FI-01301 Vantaa, Finland;Aalto University School of Science and Technology, Department of Information and Computer Science, P.O. Box 15400, FI-00076 Aalto, Finland;Aalto University School of Science and Technology, Department of Information and Computer Science, P.O. Box 15400, FI-00076 Aalto, Finland
Venue:
Neurocomputing
Year:
2010

Citing 1
Cited 2

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Logistic fitting method for detecting onset and cessation of tree stem radius increase

IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning

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Abstract

Dendrometers are devices, which measure continuously the stem radius of a tree. We studied the use of four data analysis methods for automatically and, thus, objectively determining the onset and cessation dates of radial increase based on dendrometer data. The cumulative sum chart, time series segmentation, Mann-Kendall test, and a Markov switching autoregressive model were compared. We used data measured in two stands in southern Finland to test the performance of the methods. Once configured properly, the cumulative sum chart produced results similar to those determined by an expert. The overall performance of the other methods was lower.