抄録
Amidst escalating global climate change and environmental degradation, ecological protection of vegetation has emerged as a critical strategy for enhancing ecosystem resilience and safeguarding biodiversity. In parallel, the rapid advancement of artificial intelligence (AI) technologies has opened new frontiers for ecological research and conservation practice. This review systematically examines recent progress in the application of AI to vegetation ecological protection, elucidating its current capabilities and future potential. First, it investigates AI-assisted vegetation monitoring, emphasizing the integration of remote sensing, image recognition, and machine learning algorithms for health assessment, species classification, and spatiotemporal dynamics analysis. Second, it explores AI-driven approaches in ecosystem management, including vegetation restoration, disaster impact assessment, and predictive ecological modeling. Third, the role of AI in biodiversity conservation is analyzed, particularly in optimizing habitat suitability assessments and enhancing decision support for conservation planning. Moreover, the paper highlights the synergies between AI and sustainable development goals, discussing how AI contributes to evidence-based policymaking and participatory ecological governance. Drawing on representative case studies, the review synthesizes the current effectiveness of AI applications and delineates key technological innovations and implementation challenges. Ultimately, it identifies critical research gaps and outlines future directions to promote interdisciplinary collaboration and inform the strategic deployment of AI in ecological protection. The overarching aim is to provide a comprehensive theoretical foundation and actionable insights for researchers, practitioners, and policymakers engaged in promoting sustainable ecological outcomes through intelligent technologies.
