Examination of a classification model for damaged areas of windfall trees:data analysis for damage caused by typhoon no. 23 in October 2004.

The purpose of this study was to assess the suitability of a classification model for the determination of damaged areas of windfall trees caused by typhoon No. 23 in October 2004. Data input to the classification model encompassed seven factors: altitude, slope direction, slope angle, flow accumulation, curvature, wetness index, and land use type. The output data had four possible results: no damage and three levels of damage. A classifier was used for five classification algorithms. The eighteen modules included eight decision tree modules, two rulebased modules, two instance-based modules, two Bayes modules, and four function-type modules. Data reduction by clustering was used to improve the efficiency of our analysis by removing unnecessary data from the training data. The constructed models were evaluated using “Sensitivity” and “Specificity” indexes. The GIS analysis showed that large amounts of windfall-tree damage were observed in valley landform areas, which indicated that the soil moisture conditions such as flow accumulation and wetness index were high. Many of these areas were located on north, northeast and northwest facing slopes. As a result of modeling by a classifier, the instance-based algorithm outputted a relatively good classification. When performing data reduction by clustering, the classification accuracy tended to improve. When making estimates for an entire study area with a reduced number of samples, we found that it was possible to produce an adequate simulation for situations where the training data was reduced to around one-tenth of the original information, without negatively affecting the model performance. We suggest that the index of the multiplication of “Sensitivity” and “Specificity” is effective as an indicator of model performance. keyword : clustering, data reduction, sensitivity, specificity, windfall-tree damage 1 J. For. Plann. 20: 1-12 (2015) tree damage and the areas likely to be affected. Generally, windfall-tree damage caused by a typhoon occurs due to a complicated relation between stand factors (e.g., tree species, tree age, the ratio of tree height to stem diameter) and topographical factors (e. g., soil type, soil water) (Nakamura et al., 1995; Kamimura and Shiraishi, 2007). We studied the effects of these factors on the windfall-tree damage resulting from typhoon T0423 using the results of a tree census undertaken at Ohno University Forest (Hirao, 2006). The tree census indicated deformation or breakage in many trees that had a small dbh (diameter at breast height) and small crown height ratio. The purpose of this study was to assess the suitability of a model for classifying damaged areas of windfall trees, by applying various classification algorithms as data mining techniques based on windfall-tree damage data and topographical factors calculated from GIS. In general, the amount of windfall-tree data was extremely small in relation to the number of trees in the study area. We then undertook data reduction by clustering as a technique to improve the efficiency of the analysis by positively reducing unnecessary data from the training data. We made an estimation for the entire study area using the training data as samples after data reduction by clustering.