Global Vegetation Pest and Disease Dynamic Remote Sensing Monitoring and Forecasting

Global pests and diseases caused more than 40% yield loss and ecological degradation under the global climate change. There is an urgent need to enhance global cooperation in spatial information technology, specifically to advance scientific and technological capabilities in P&D monitoring and forecasting to ensure the food security and ecological development.

Digital precision monitoring and early warning systems were developed for crop, forest, and grassland pests and diseases, focusing on major global vegetation pests and diseases such as desert locusts, fall armyworms, wheat rust, and pine wilt disease. It addresses the current lack of large-scale and rapid monitoring and early warning methods for pest and disease outbreaks. P&D monitoring and forecasting models and algorithms are established for 18 major crop, forest and grass P&D. Multi-scale P&D monitoring and forecasting products, reports are normally released by self-developed system to meet the requirements of multi-level users via metadata, API, map and software.

Our work have been affirmatively approved or reviewed by the Standing Committee of the Political Bureau of the CPC Central Committee, adopted by the General Office of the CPC Central Committee and the General Office of the State Council 10 times, and adopted by national ministries and industry organizations more than 220 times, reducing the amount of pesticide application by about 30% and improving species Richness of about 10%: Adopted by the Food and Agriculture Organization of the United Nations (FAO), United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER), Global Biodiversity Information Facility (GBIF), Pakistani Ambassador to China, Agricultural Extension Department (AED), Eritrea, etc., supporting scientific prevention and control of an area of more than 500 million mu. GEO promotes this achievement as a typical case to the world.

Our work have been affirmatively approved or reviewed by governments and international organizations around the world through four forms: metadata, API, Map, and Software. For example,

1. FAO used metadata to issue warnings to high-risk countries such as Somalia, Ethiopia, Kenya et al to guide global crop protection and found the pest in our forecast areas, valuable for decision making, guiding for early stage pest management;
2. GBIF used APIs further to reveal environmental disturb factors and protect biodiversity, which is the first ‘Remote Sensing Dataset’ in GBIF for global circulation to support ecology sustainable development;
3. Technicians and prevention staffs used pests and diseases map to conduct precision control, helping more countries enhance the country's food security through sharing data of monitoring and assessment of global vegetation P&D;
4. Software can be used to forecast the risk of pests and diseases in specific areas and time to maximize biopesticide promotion. International branches reduced chemical pesticide usage and achieved cost saving using our results.

Global climate change has led to an increase in the severity of vegetation pests and diseases. To achieve international food security and maintain ecological sustainability at a large scale, there is an urgent need to develop timely and accurate remote sensing-based monitoring and early forecasting products and services. We build a community of stakeholders to improve our capacity to support the SDG2 & SDG13 of UN’s 2030 Agenda, and disaster prevention and reduction objects of Sendai Framework. Ultimately promoting global cooperation in vegetation pests and diseases control to help ensure global food security and sustainable development of ecosystem.

We focused on globally migratory and epidemic vegetation pests and diseases, and conducts habitat monitoring, hotspot analysis, migration and spread risk prediction modeling in breeding and diffusion areas, to provide scientific support for food and ecological security at global and regional scales. The main steps are as follows:

1. We established a remote sensing-based monitoring and forecasting technology for vegetation pests and diseases: We identified the characteristic and sensitive spectral bands in response to various crop diseases and pests using remote sensing-based monitoring techniques. In this part, in situ data of crop pests and diseases in China are provided by the National Agro-Tech Extension and Service Center of China, in situ data of forestry and grassland pests and diseases in China are provided by Center for Biological Disaster Prevention and Control, and in situ data of global vegetation pests and diseases are provided by FAO.
2. Development of a remote sensing-based monitoring and forecasting system for vegetation pests and diseases: We used key technologies (such as a satellite-earth coordinated observation network) and conducted rapid quantitative processing of spatio-temporal remote sensing data at multiple scales. In this part, biodiversity assessment model and biological interaction model were developed by GBIF, cutting-edge deep learning algorithm was developed by MMU, remote sensing monitoring and forecasting model of pests and diseases was developed by AIR-CAS, CABI provided the biological model, and IMMA constructed the inversion model of vegetation physical and chemical parameters.
3. Promotion and application of vegetation pest and disease products: Based on the remote sensing-based monitoring and forecasting system for crop diseases and pests, we produced and released thematic maps and scientific reports on acute diseases and pests in major crops worldwide, nationwide, and in key regions. Agriculture applications are promoted by FAO, ANSO and National Agro-Tech Extension and Service Center of China; ecology applications are promoted by GBIF, CABI and Center for Biological Disaster Prevention and Control; Forestry and grassland pest and disease control strategies, including time, height, spraying method, concentration of agent.