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

Authors:
Mark J. Brewer;Mika Sulkava;Harri Mäkinen;Mikko Korpela;Pekka Nöjd;Jaakko Hollmén
Affiliations:
Biomathematics & Statistics Scotland, The Macaulay Land Use Research Institute, Craigiebuckler, Scotland, UK;Aalto University School of Science, Department of Information and Computer Science, Aalto, Finland;Finnish Forest Research Institute, Southern Finland Regional Unit, Vantaa, Finland;Aalto University School of Science, Department of Information and Computer Science, Aalto, Finland and University of Helsinki, Department of Computer Science, University of Helsinki, Finland;Finnish Forest Research Institute, Southern Finland Regional Unit, Vantaa, Finland;Aalto University School of Science, Department of Information and Computer Science, Aalto, Finland
Venue:
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
Year:
2011

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

Neurocomputing

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Abstract

Dendrometers are devices which measure the stem radius of a tree continuously. We studied the use of logistic and generalised logistic models for exploring dendrometer data and for automatically determining the onset and cessation dates of radial increase. We used data measured in two stands in southern Finland to test the performance of the models. In the detection task, the generalised logistic models performed well compared to earlier approaches. In addition, the exploratory analysis revealed distinct differences between growth patterns of trees in different calendar years.