Abstract
We present a method for automated segmentation of dust storm areas on Mars images observed by an orbiter. We divide them into small patches. Normal basis vectors are obtained from the many small patches by principal component analysis. We train a classifier using coefficients of these basis vectors as feature vectors. All patches in test images are categorized into one of the dust storm, cloud, and surface classes by the classifier. Each pixel may be included in several dust storm patches. The pixel is classified as a dust storm or the other classes based on the number of dust storm patches that include the pixel. We evaluate the segmentation method by the receiver operator characteristic curve and the area under the curve (AUC). AUC for dust storm is 0.947–0.978 if dust storm areas determined by our visual inspection are assumed to be ground truth. Precision, recall, and F-measure for dust storm are 0.88, 0.84, and 0.86, respectively, if we remove false negative pixels efficiently and maintain the size of true positive dust storms using two different threshold values. The tuning parameters of the classifier used in this study are determined so that the accuracy for dust storm is maximized. We can also tune the classifier for cloud segmentation by changing the parameters.
Highlights
The planet Mars is regularly affected by dust storms that cover contiguous areas ranging in size from local (10,000 km2) to global (> 5 × 107 km2) and present a variety of hazards/challenges to present and future exploration of the planet
The wavy features in the northwest area of the image should not be recognized as dust storms, because they seem to be typical water ice clouds (WICs) associated with topographically generated gravity waves, the so-called lee waves
We have investigated an algorithm for automated segmentation of dust storms in Mars images observed by Mars Global Surveyor (MGS)/Mars Orbiter Camera (MOC)
Summary
The planet Mars is regularly affected by dust storms that cover contiguous areas ranging in size from local (10,000 km2) to global (> 5 × 107 km2) and present a variety of hazards/challenges to present and future exploration of the planet. Martian dust storms are atmospheric phenomena visualized by dust suspended in the atmosphere. The atmospheric phenomena controlling dust storms are suggested by the storms’ shapes and sizes, as well as the season, region, and local time of initiation. Wang et al (2011) showed the distribution of curvilinear dust storms in the southern hemisphere observed by MGS/MOC. Guzewich et al (2015) clearly showed the frequency, regionality, and seasonality of “textured dust storms” seen in MGS/MOC images. Guzewich et al (2017) revealed the relationship between the frequency of textured dust storms in images from the Mars Color
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