Species classification of individually segmented tree crowns in high-resolution aerial images using radiometric and morphologic image measures

This paper presents a method to automatically classify segmented tree crowns from high spatial resolution colour infrared aerial images as one of the four most common tree species in Sweden. The species are Norway spruce (Picea abies Karst.), Scots pine (Pinus sylvestris L.), birch (Betula pubescens Ehrh.), and aspen (Populus tremula L.). The proposed method uses four different image measures, one measure for each species. The measures are based on colour information as well as the shape of the segmented tree crowns. A segment is examined by the measures one by one and if one measure becomes true, the segment is interpreted as that species. The analysis continues with the next segment. The method is evaluated on two sets of images. The first set consists of 14 images of naturally regenerated forest with pixel size corresponding to 3 cm. These images contain approximately 50 visible tree crowns each; a total of 791 crown segments are used. The overall classification result for these images is 77%. If only the distinction between conifers and deciduous is made, the result is 91%. The second set consists of two images with a pixel size of 10 cm. Here, the overall classification result is 71%.