Bursaphelenchus xylophilus disease occurrence area intelligent identification method

Abstract

The invention discloses a pine wood nematode disease occurrence area intelligent identification method. Remote sensing image data and a deep learning technology are applied to the field of pine wood nematode disease monitoring. A pine wood nematode disease occurrence area semantic segmentation sample data set is constructed based on a remote sensing image, a UNet semantic segmentation model is constructed, the model is trained and optimized, and intelligent recognition of a pine wood nematode disease occurrence area is achieved. The method is simple in process and high in practicability, a new method is provided for intelligent monitoring of pine wood nematode diseases, and the method is suitable for the fields of forest pest and disease damage monitoring, deep learning image recognition and the like.

Description

1. Technical field [0001] The invention relates to the field of remote sensing image analysis and deep learning of forest diseases and insect pests, in particular to an intelligent identification method for pine wood nematode occurrence areas. 2. Background technology [0002] Pine wood nematode (Bursaphelenchus xylophilus) is one of the most dangerous forest biological disasters in China, and it is a devastating disease to pine tree species. Because of its strong infectivity and high fatality rate, pine wood nematode is also known as the "cancer" of pine trees. Pine wood nematode disease has caused great losses to China's forestry ecology and economy. In the 35 years from 1982 to 2017, the disease caused more than 50 million dead pine trees, and the economic loss reached hundreds of billions of yuan. It caused great harm to China's forest resources and ecological environment. Huge destruction. [0003] The traditional monitoring of pine wood nematode disease mainly involv...

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Problems solved by technology

[0003] The traditional monitoring of pine wood nematode disease mainly involves regular inspections by monitors, or general surveys of pine wood nematode disease. Due to the failure to establish relevant monitoring stations and assign corresponding monitoring personnel in some forest areas, the monitoring of pine wood nematode disease is not enough. Comprehensive, accelerated the spread of the epidemic

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