GeoAI and the digital transformation of agriculture, water and food systems
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Agriculture, water and food are fundamental to prosperity, peace, and development. “End poverty in all its forms everywhere” (SDG1) and “end hunger, achieve food security and improved nutrition and promote sustainable agriculture” (SDG2) are the cornerstones to UN Sustainable Development Goals. The realization of SDG 1 & 2 heavily relies on sustainable agrifood systems and water management. Global challenges related to climate change and shortage of labor, exacerbate existing uncertainties in agriculture and food production. Now, agriculture is undergoing digital transformation. Agricultural practices are carried out on farms in all regions, countries and continents. Geospatial IT, including remote sensing and GIS, plays important roles in modern agriculture and digital transformation of traditional agriculture. The integration of Artificial intelligence (AI) and geospatial IT with agriculture shines light on the future agriculture with higher productivity, profitability, and sustainability.
Agricultural information technology (Agro-informatics) has evolved from precision agriculture to smart agriculture with integration of digital technologies into agricultural management and related processes. AI, represented by machine/deep learning, has been significantly developed and applied in the last ten years. In agriculture various machine/deep learning algorithms and models with explainable abilities have been increasingly developed and applied and reinforcement learning shows great potential for crop growth optimal control and generative adversarial networks for agricultural image augmentation. Agricultural remote sensing can integrate multiple source data from satellites, manned aircrafts, unmanned aerial vehicles and ground-based systems with environmental measurements. The formation and management of agricultural remote sensing big data are the foundation of standardized data storage, processing, analysis and interpretation, and result visualization for intelligent agricultural decision support.
In this AI for Good session, learn about GEOAI research and applications in the agrifood system and water management projects in different scales and regions. Discuss the technical challenges of AI and GEOAI applications in the agrifood system and the benefits these technologies bring to sustainable development.
This live event includes a 30-minute networking event hosted on the AI for Good Neural Network. This is your opportunity to ask questions, interact with the panelists and participants and build connections with the AI for Good community.