Highlights: A change detection method for block falls' identification on Mars is proposed. The images and a training data set are prepared. A combination of SVM/HOG and blob detection is used. The results show a true positive rate of ~75% and a false detection rate of ~8.5%.
AbstractWe developed a change detection method for the identification of ice block falls using NASA's HiRISE images of the north polar scarps on Mars. Our method is based on a Support Vector Machine (SVM), trained using Histograms of Oriented Gradients (HOG), and on blob detection. The SVM detects potential new blocks between a set of images; the blob detection, then, confirms the identification of a block inside the area indicated by the SVM and derives the shape of the block. The results from the automatic analysis were compared with block statistics from visual inspection. We tested our method in 6 areas consisting of 1000×1000 pixels, where several hundreds of blocks were identified. The results for the given test areas produced a true positive rate of ~75% for blocks with sizes larger than 0.7 m (i.e., approx. 3 times the available ground pixel size) and a false discovery rate of ~8.5%. Using blob detection we also recover the size of each block within 3 pixels of their actual size.
Abstract. We have developed a method for automatically detecting the sources of ice block falls at the Martian north polar scarps. Multitemporal red-filter High Resolution Imaging Science Experiment (HiRISE) images were processed by using the open source NASA Ames Stereo Pipeline in combination with the USGS Integrated Software for Imagers and Spectrometers to produce 0.25 m resolution images as well as a 1 m resolution DTM. The multi-temporal HiRISE images were firstly ortho-rectified by the DTM, and then co-registered by using the Enhanced Correlation Coefficient Maximization (ECC) algorithm. We applied the change detection method on the well-aligned sub-meter scale HiRISE images, which were taken in Mars Year 29 and Mars Year 30, to investigate mass wasting at the scarp area centred at 85.0°N, 151.5°E. The idea of the change detection method is to identify changing shadow patterns based on the grayscale difference between the images. The final results show that erosion events occurred at the full length of this study’s scarp within one Mars Year. However, only the upper and lower part of the scarp show erosion activity, whereas the intermediate parts seem inactive, and this correlates with the slope.
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