Floating type seabed data measurement method and device and electronic equipment

Abstract

The embodiment of the invention provides a floating type seabed data measurement method and device and electronic equipment, and relates to the field of image recognition. The floating type seabed data measurement method comprises the steps: firstly obtaining a seabed scanning image on the ocean surface of a to-be-measured region through a floating type image collection device; splicing and preprocessing the seabed scanning images to obtain a seabed planar graph of the to-be-measured area; and finally, based on a pre-trained coral classification model, determining distribution areas of variouscorals in the seabed planar graph. Therefore, according to the technical scheme provided by the embodiment of the invention, measurement can be carried out on the water surface without underwater visual inspection, and the technical problems of low measurement accuracy and long measurement time in the prior art are relieved, and the accuracy of a measurement result can be improved, and the measurement time is shortened, and the measurement efficiency is improved.

Description

technical field [0001] The invention relates to the field of oceanographic measurement, in particular to a floating seabed data measurement method, device and electronic equipment. Background technique [0002] Bio-species richness is an important measure of coral reef health, as healthy reefs are typically home to more species than degraded reefs. Coral reefs are sampled to estimate species richness, or the number of species in a given area. [0003] At present, scientists mainly rely on divers' visual inspection for sampling coral reefs, that is, divers go directly into the water for measurement. Among them, transverse lines and square frames are commonly used tools in the process of sampling coral reefs. Such as figure 1 shown. When launching measurements, divers need to hold a square frame made of PVC pipes to count or quantify the organisms in a small area, and estimate the richness of a larger area based on the results of the small area. Estimating a large area wit...

AI Technical Summary

Problems solved by technology

Estimating a large area with a small area sample will generate many assumptions, resulting in low measurement accuracy; in addition, due to the refraction problem of water, the measurement accuracy of visual measurement is low, and the measurement time required is often relatively long

[0004] To sum up, there are problems of low measurement accuracy and long measurement time in the prior art

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