Object-orientated image analysis for the semi-automatic detection of dead trees following a spruce bark beetle (Ips typographus) outbreak

Abstract

The survey and continuing inventory in the Bavarian Forest National Park of deadwood areas resulting from a spruce bark beetle calamity are being performed by means of visual evaluation of colour infrared aerial photographs. With the aid of the object-oriented image analysis software eCognition, it was possible to develop a partially automated method for this purpose. In order to verify the classification results, a test area was classified, and the results compared with those obtained by the previously used method. In addition, the classification results from two consecutive years were compared, and accuracy assessment methods were used to scrutinize the results. Classification in the deadwood areas yielded a total classification accuracy of 91.5%. In regard to objectivity and degree of detail, the newly developed method is significantly superior to the former method, which is based on visual interpretation with a stereo workstation. One problem, however, was the insufficient spatial accuracy of the respective orthophotos. Because of this, it was not possible to detect changes over the course of specified time intervals. Therefore, a practical application of this method would require that the orthophotos from various dates or times be precisely spatially assigned. This requirement can be achieved with the production of new orthophotos.