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Application of Haralick’s Texture Features for Rapid Detection of Windthrow Hotspots in Orthophotos

机译:Haralick纹理特征在矫正器中快速检测Windthrow热点的应用

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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).
机译:WindThrow和风暴损伤是实际林业的关键问题。我们提出了一种快速检测空气中的数字原子芯片中风热点的方法。因此,我们将Haralick的纹理特征应用于原子镜的50×50米的细胞,并用随机森林算法对细胞进行分类。我们将分类结果从验证集上设置的培训数据应用。所提出的方法的整体分类精度在76%之间的细胞细胞区分为96%,对于试图检测严重受损细胞的区别水平。所提出的方法可以在单日数据发生后立即快速检测森林中的WindThrow热点。只有单次倒下的树木的确定是不够的。将来的研究将研究应用于在其他数据源上的方法(例如,光学卫星数据)时的可能性和限制。

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