Global Vegetation Pest and Disease Dynamic Remote Sensing Monitoring and Forecasting

Global climate change intensifies biological crises, with vegetation pests and diseases posing severe threats. These outbreaks reduce biodiversity, disrupt ecosystems, and compromise agricultural productivity and regional stability. Current approaches lack precision and timeliness, hindering effective responses. A global, high-resolution monitoring and forecasting framework is urgently needed to mitigate impacts, reduce pesticide dependence, and protect biodiversity. Such efforts align with UN Sustainable Development Goals 2 and 13, support the Sendai Framework, and enhance international collaboration, ensuring food security and fostering resilient ecosystems.

To meet these critical challenges, a globally scalable technological framework for vegetation pests and diseases monitoring and forecasting is paramount. This framework necessitates a multi-scale approach, integrating sophisticated spectral analysis, AI-driven algorithms, and dynamic monitoring and forecasting tools to ensure rapid and precise detection and early warning of outbreaks. Essential iterative feedback mechanisms enable continuous data refinement, while the sharing and application of critical data, alongside the publication of functional modules, and specialized software, enhances utility and accessibility. Collectively, these components advance comprehensive habitat surveillance and proactive disaster forecasting, providing vital insights and decision-support capabilities to stakeholders across multiple levels.

This solution enables coordinated, multi-institutional monitoring and forecasting of vegetation pests and diseases at continental and regional scales, strengthening disaster mitigation, regional stability, and food security through improved yields, reduced hunger, and reduced loss of life. Early warning capabilities support precise, cost-effective control strategies, mitigating economic losses, raising household incomes, and delivering significant financial savings. Accurate monitoring and warnings guide integrated physical, chemical, and ecological control methods, reducing pesticide dependence, protecting ecosystems, and conserving biodiversity. 

Building on the foundational achievements of previous GEO projects, in 2025–2030, the project will focus on developing efficient technologies for dynamic monitoring, risk analysis, invasion forecasting, and damage assessment of major epidemic and migratory vegetation pests and diseases. By integrating innovative models with advanced technologies, such as artificial intelligence, the project aims to enhance vegetation pest and disease monitoring and forecasting capacities, particularly in developing regions. Through the development and optimization of pest and disease information service infrastructure, the project seeks to provide comprehensive support for effective pest and disease management, contributing to sustainable development and global food security. 

The project plans to produce three types of products tailored to diverse user needs. First, metadata is designed for integration with sectoral data systems to enable further analysis and applications. Second, user-oriented tools—such as maps, mobile applications (apps), and low-cost devices—are developed, specifically targeting end-users, particularly farmers in developing regions. Third, APIs and software are provided for integration with internationally recognized platforms, supporting localized applications in key regions and enhancing global scalability. 

By leveraging these products and technological innovations, the project seeks to deliver comprehensive solutions that proactively address biological threats. Specifically, it aims to achieve over 85% precision in habitat monitoring and forecasting, providing early warnings at least 10 days before anticipated incursions. These outcomes will significantly enhance disaster preparedness, reduce pest impacts, and promote sustainable pest and disease management practices globally. 

The project will establish a collaborative framework integrating the core team, governance bodies, and an international network. The core team will define strategic directions, while governance bodies will oversee management and quality assurance. Leveraging its international partnerships, the project will conduct joint data acquisition, establish joint laboratories, co-develop pest and disease monitoring products, apply for international projects, and deploy global platforms. Regular scientific exchanges and joint training sessions will be organized to foster multidisciplinary integration and innovation. This framework ensures high-quality execution and effective application of outcomes.