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The 3rd Conference on Remote Sensing of Vegetation Pests and Diseases concluded successfully

Time: 2022-08-28
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The 3rd Conference on Remote Sensing of Vegetation Pests and Diseases was held online from 27 to 28 August. With the theme of 'Protecting Plants, Guarding Security', the conference provided an excellent exchange platform for experts, scholars, managers and students engaged in scientific research, teaching and application. The conference was broadcast live online through a number of web platforms, including Bilibili, Xiaokang Live, Journal of Remote Sensing, China Biodiversity Conservation and Green Development Foundation (CBCGDF) Media, Innovation China, CNKI, Koushare, and MDPI. The purpose of the conference was to promote the in-depth application of remote sensing technology in smart plant protection, disaster forecasting and ecological security by exchanging the latest research results such as the theory, method and technical application. By discussing the integration of disciplines and technological innovation methods in the field of vegetation pests and diseases monitoring, forecasting, prevention and control, the conference promotes theoretical innovation and industrial application, builds ecological civilization, promotes the harmonious coexistence of human and nature, and builds a community of life on earth. 

The conference is co-sponsored by the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Anhui University, Manchester Metropolitan University, Alliance of International Science Organizations (ANSO), the Chinese Society of Agricultural Engineering (CSAE), CBCGDF, the China Agricultural Risk Management Society, Hangzhou Dianzi University, etc.

The opening ceremony was presided over by Wenjiang Huang, a researcher of AIR-CAS and the chairman of the conference. Experts and scholars from 35 institutions delivered speeches and academic presentations on topics such as monitoring methods for vegetation habitats, remote sensing monitoring and forecasting techniques for vegetation pests and diseases, and the ways in which the products are used in agricultural production. More than 400,000 people attended the conference, including government leaders, experts, scholars and business representatives from various fields. The conference also launched a special issue 'Monitoring, Early Warning, and Scientific Management of Vegetation Pests and Diseases' in cooperation with the journal 'Remote Sensing' (IF: 5.349). The conference also hosted an award ceremony for the Beyond Visible Spectrum: AI for Agricultural Challenges-series 1: Automated Crop Disease Diagnosis from Hyperspectral Imagery, a global crop disease diagnosis challenge co-organized by the AIR and Manchester Metropolitan University, where the top five teams in the competition were awarded by the conference chair, Huang Wenjiang, and Professor Han Liangxiu from Manchester Metropolitan University.

The conference is oriented to the monitoring, early warning and prevention and control needs of pests and diseases in crop, forest and grassland, covering many fields such as remote sensing, agriculture, forestry, grassland, plant pathology, entomology, ecology, environment, computer, big data analysis and so on. The conference focused on the application of spatial information technology in the monitoring, early warning, and prevention and control of vegetation pests and diseases, and deeply discussed the latest research results and future development trends in related theories, methods, models, systems, and applications. The conference provides scientific and technological platforms for research, teaching, and industrial integration exchanges in the fields of remote sensing, agriculture, forestry and grassland plant protection. It is hoped that through in-depth discussion and extensive communication, the conference will accelerate the fundamental reform of diseases and pests control mode, to ensure national food security and human ecological well-being.

The 3rd Conference on Remote Sensing of Vegetation Pests and Diseases concluded successfully

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