The invention discloses an endangered
plant phoebe hainanensis identification and systematic monitoring method based on multi-
source data fusion, and belongs to the technical field of endangered
plant protection. According to the method, a potential distribution area is delineated through a
species distribution model, individual accurate identification and filing are achieved through a multi-
branch feature fusion model, multi-scale growth and microenvironment data are collected through
Internet of Things nodes, and finally a'discovery-identification-monitoring-protection 'whole-process
closed loop is formed through a unified
data management platform. According to the method, phenological
feature extraction, transfer learning modeling, man-
machine collaborative
verification and low-power-consumption
Internet of Things monitoring technologies are adopted, and the problems that a traditional method is low in efficiency, insufficient in recognition precision and fragmented in monitoring are solved. According to the method, efficient discovery, accurate identification and long-term
dynamic monitoring of the wild
population of the phoebe hainanensis are achieved, scientific support is provided for protection
decision making, and the method is convenient to operate and high in practicability and has protection value and application prospects.