Eichhornia crassipes biomass monitoring platform

Abstract

The invention discloses an eichhornia crassipes biomass monitoring platform, and belongs to the technical field of aquatic biomass. An image sensor is installed on the unmanned aerial vehicle, and then the image sensor is in data connection with a data analysis system; after the image sensor shoots a picture, picture data are transmitted to the data analysis system. A machine learning module, a feature recognition module and a risk assessment module are arranged in the data analysis system. The machine learning module is used for classifying and identifying eichhornia crassipes; the feature recognition module is used for recognizing color features of eichhornia crassipes; and the risk assessment module is used for establishing alien plant invasive risk assessment adaptive to the region. The biomass of the eichhornia crassipes is estimated through the three different modules, and manual observation or manual counting is not needed. The invention is high in efficiency, and powerful reference data can be conveniently provided for follow-up eichhornia crassipes cleaning work.

Description

technical field [0001] The invention relates to the technical field of aquatic organism monitoring, in particular to a biomass monitoring platform of water hyacinth. Background technique [0002] Water hyacinth was listed in the first batch of invasive alien species list by the state in 2003. In the 1930s, it was introduced to various provinces in the mainland of China as livestock feed and planted, and then escaped to become a wild plant. Due to the extremely fast reproduction speed of water hyacinth, it has been widely distributed in 19 provinces and cities in North China, East China, Central China, South China and Southwest China, especially in Yunnan, Jiangsu, Zhejiang, Fujian and other provinces, which have brought serious damage to the local environment. Great threat. Experts and scholars at home and abroad have done a lot of research on the invasion of water hyacinth. The existing control methods of water hyacinth include mechanical methods, chemical methods and biol...

AI Technical Summary

Problems solved by technology

[0003] At present, the existing technology uses the traditional image processing method to extract the characteristics of water hyacinth to achieve the purpose of identifying the biomass of water hyacinth, but the lack of image recognition of water hyacinth based on multi-target detection leads to inaccurate recognition and cannot Meet the monitoring requirements for the biomass of water hyacinth

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