NDLI: Accurate prediction of ice disturbance in European deciduous forests with generalized linear models: a comparison of field-based and airborne-based approaches

Content Provider	Springer Nature Link
Author	Aszalós, Réka Somodi, Imelda Kenderes, Kata Ruff, Jás Czúcz, Bálint Standovár, Tibor
Copyright Year	2012
Abstract	We analyzed an ice disturbance event of deciduous forests in Hungary by Generalized Linear Models (GLM). Two statistical models were generated: the first model was based on a disturbance map created from a series of aerial photographs, and the second model was based on a map created by half-year-long intensive field work. The second map was considered as the reference map of ice disturbance. Our hypothesis was that the predictive power of the field-based statistical model would be significantly higher than that of the aerial photo-based model on the reference map. Elevation, slope, aspect, mixture ratio of beech, height of the dominant tree species and their interactions were used in the two (aerial photo- and field-based) GLMs as explanatory variables. The accuracy of the models was measured by the AUC (Area under the ROC curve) values. Sensitive area maps of ice disturbance were generated by both models. Our hypothesis was definitely rejected. Both models performed high predictive accuracy (median AUC > 0.9) with no significant difference in the prediction capacity regarding the reference ice disturbance pattern. Our study demonstrates that ice damage can effectively be predicted if remote sensing interpretation is coupled with GLM as predictive model.
Starting Page	1905
Ending Page	1915
Page Count	11
File Format	PDF
ISSN	16124669
Journal	Forstwissenschaftliches Centralblatt vereinigt mit Tharandter forstliches Jahrbuch
Volume Number	131
Issue Number	6
e-ISSN	16124677
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-07-05
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Forest damage GLM Susceptibility assessment Probability map Variable interactions Plant Ecology Plant Sciences Forestry
Content Type	Text
Resource Type	Article
Subject	Plant Science Forestry

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