Non-Gaussian submarine landform type identification method based on multi-fractal spectrum characteristic

Abstract

The invention discloses a non-Gaussian submarine landform type identification method based on a multi-fractal spectrum characteristic. The method comprises the following steps of 1) calculating depthdistribution skewness and kurtosis according to submarine depth measurement data and determining whether a landform is a non-Gaussian landform; 2) calculating the multi-fractal spectrum characteristicof the non-Gaussian landform; 3) using the multi-fractal spectrum characteristic as an original variable, and applying a factor analysis method to extract a landform factor; 4) according to the landform factor, using a support vector machine to design a landform type classifier; and 5) calculating landform depth distribution skewness and kurtosis of a landform to be identified, determining the nongaussianity of the landform, calculating the multi-fractal spectrum characteristic of the non-Gaussian landform and the landform factor, and using the designed classifier to identify a landform type.The method has advantages that the method is simple, a calculated amount is small, an identification accuracy is high, and manpower is saved and so on. The method is suitable for non-Gaussian submarine landform type identification.

Description

technical field [0001] The invention relates to the technical fields of marine surveying and mapping, marine engineering, marine oil and gas resources, etc., in particular to a non-Gaussian seabed landform type identification method based on multi-fractal spectrum features. Background technique [0002] Geomorphology is the general term for various undulating shapes on the earth's surface. The types of submarine topography include paleochannels, scour troughs, submarine canyons, deep water channels, seamounts, carbonate platforms, cliffs, landslides, etc. Geomorphological classification is the basis of seabed geomorphological research and mapping. Geomorphic morphology can reflect the internal relationship between geomorphic genetic types and genetic control forms, and is the key to deep geological knowledge mining. [0003] The multi-beam sounding system can detect the fine features of the seabed topography and topography with wide coverage and high resolution. The system...

AI Technical Summary

Problems solved by technology

This method can make full use of the knowledge of technicians and has good flexibility, but it requires technicians to have rich geological knowledge and experience in observation and judgment, which has great subjectivity, poor timeliness, and high labor intensity.

Especially due to the massive level of seabed data, it is far from being able to undertake the processing tasks of massive data only relying on the artificial ability of technicians

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