Windthrow and storm damage are crucial issues in practical forestry. We propose a method for rapid detection of windthrow hotspots in airborne digital orthophotos. Therefore, we apply Haralick’s texture features on 50 × 50 m cells of the orthophotos and classify the cells with a random forest algorithm. We apply the classification results from a training data set on a validation set. The overall classification accuracy of the proposed method varies between 76% for fine distinction of the cells and 96% for a distinction level that tried to detect only severe damaged cells. The proposed method enables the rapid detection of windthrow hotspots in forests immediately after their occurrence in single-date data. It is not adequate for the determination of areas with only single fallen trees. Future research will investigate the possibilities and limitations when applying the method on other data sources (e.g., optical satellite data).
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