Monitoring Forest Damage Caused by Pine Wilt Disease with Remote Sensing Technologies: A review

Pine wilt disease (PWD), often referred to as the “cancer of pine forests,” is notorious for its rapid spread and devastating impact. Remote sensing technologies (RSTs) are crucial for monitoring PWD; however, challenges remain in accurately detecting early-stage infections and scattered outbreaks. This review adopts a remote sensing perspective to systematically summarize the biological characteristics and spectral features of PWD. It analyzes the advantages and limitations of ground-based unmanned aerial systems (UASs), and satellite remote sensing platforms in PWD monitoring. Existing studies suggest that multimodal and multiplatform collaborative observations may help mitigate background interference. Additionally, the review evaluates the performance of statistical methods, shallow machine learning, and deep learning algorithms in feature extraction and monitoring model development. Results indicate that integrating remote sensing spatiotemporal-spectral analysis with artificial intelligence (AI) and developing models driven by both data and biological mechanisms offer promising solutions to key monitoring challenges. This review aims to improve and optimize the selection of monitoring methods, contributing to global efforts to control this destructive forest disease.