The Moon is the heavenly body closest to Earth. In order to conduct an in-depth study on the Moon, select the landing site, and/or plan for roving exploration, researchers need to understand how long the Moon has existed and how it was formed. An internationally common method for age dating of the Moon in areas without lunar soil samples is to determine the absolute age of the Moon based on the number and sizes of impact craters. For the identification and extraction of impact craters required for age dating, we combined histogram of oriented gradients (HOG) features and support-vector machine (SVM) classifiers to set up a sample pool (including positive and negative samples) for lunar impact craters, thereby achieving automatic identification and extraction of impact craters of different sizes in the landing area of Chang'e-5.
KEYWORDS: Roads, Nomenclature, Data storage, Evolutionary algorithms, Data modeling, Visualization, Java, Data acquisition, Analytical research, Algorithm development
Implicit correlations exist between multi-source geospatial data, the association relation can’t be displayed intuitively and retrieved effectively, which leads to the difficulty in data utilization and data sharing. Aimed at this situation, association relation topic maps is constructed using topic map tools Ontopia in this article. Besides, to increase the efficiency of building topic map, the automatic generation algorithm of association relation topic map which based on C# is proposed. The result of experiment shows that the association relation topic map can be constructed correctly by using Ontopia tools and automatic generation algorithm.
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