A Versatile Method for Ice Particle Habit Classification Using Airborne Imaging Probe Data
A Versatile Method for Ice Particle Habit Classification Using Airborne Imaging Probe Data
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DOI：
10.1029/2018jd029163
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发表时间：
2018-12
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影响因子：
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通讯作者：
C. Praz;S. Ding;G. McFarquhar;A. Berne
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文献类型：
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作者：
C. Praz;S. Ding;G. McFarquhar;A. Berne
提出了一种从机载光学阵列探测器中自动分类冰粒习性的通用方法。使用多项逻辑回归模型实现分类。对于每个机载探测器，该模型基于从颗粒的二维图像中提取的大量几何和纹理描述符来确定颗粒习惯（在六个类别中）。该技术的应用和评估使用三个探头具有显着不同的规格：高容量降水光谱仪，二维立体探头，和云粒子成像仪。该方法的性能和鲁棒性使用标准的机器学习工具进行评估的基础上手动标记的每个所考虑的探针的数千个图像。这三个分类器表现出良好的性能，其特征在于整体准确率和Heidke技能得分超过90%。根据应用和用户偏好，可以轻松调整分类方案。为了更精确的输出，可以以嵌套的方式实现组内亚分类，这里用柱状晶体和聚集体来说明。的分类输出与三个探头的比较研究，提出了两个飞机飞行期间选择的三个探头一起工作时。结果在识别的习惯比例方面是全球一致的（一旦模糊和部分图像被自动丢弃）。预期不会完全一致，因为所考虑的三种探针对不同的粒度范围敏感。
A versatile method to automatically classify ice particle habit from various airborne optical array probes is presented. The classification is achieved using a multinomial logistic regression model. For each airborne probe, the model determines the particle habit (among six classes) based on a large set of geometrical and textural descriptors extracted from the two‐dimensional image of a particle. The technique is applied and evaluated using three probes with significantly different specifications: the high volume precipitation spectrometer, the two‐dimensional stereo probe, and the cloud particle imager. Performance and robustness of the method are assessed using standard machine learning tools on the basis of thousands of images manually labeled for each of the considered probes. The three classifiers show good performance characterized by overall accuracies and Heidke skill scores above 90%. Depending on the application and user preferences, the classification scheme can be easily adapted. For a more precise output, intraclass subclassification can be achieved in a nested fashion, illustrated here with columnar crystals and aggregates. A comparative study of the classification output obtained with the three probes is presented for two aircraft flight periods selected when the three probes were operating together. Results are globally consistent in term of proportions of habit identified (once blurry and partial images have been automatically discarded). A perfect agreement is not expected as the three considered probes are sensitive to different particle size range.