A Digital Management System for Monitoring Epidemics and the Management of Pine Wilt Disease in East China

Abstract

The precise monitoring of forest pest and disease outbreaks is a crucial prerequisite for efficient prevention and control. With the extensive application of remote sensing monitoring technology in the forest, a large amount of data on pest and disease outbreaks has been collected. It is highly necessary to practically apply these data and improve the efficiency of forest pest and disease monitoring and management. In this study, a Digital Forest Protection (DFP) system based on the geographic information system (GIS) was designed and developed for pine wilt disease (PWD) monitoring and management, a devastating forest disease caused by the pine wood nematode, Bursaphelenchus xylophilus. The DFP system consists of a mobile app for data collection and a web-based data analysis platform. Meanwhile, artificial intelligence and deep-learning methods had been conducted to integrate a real-time unmanned aerial vehicle (UAV) remote sensing monitoring with PWD detection. This system was implemented in PWD monitoring and management in Zhejiang Province, China, and has been applied in data collection under certain circumstances, including the manual epidemic survey, the UAV epidemic survey, and eradication monitoring, as well as trunk injection. Based on DFP system, the effective monitoring of PWD outbreaks could be achieved, and corresponding efficient management strategies could be formulated in a timely manner. This allows for the possibility to optimize the integrated management strategy of PWD on a large geographic scale.