Today, I would like to share with you the report "Exploration of Artificial Intelligence" made by Liu Xiaoding, Secretary of the Party Committee and President of the Guangdong Provincial Institute of Land and Resources Surveying and Mapping, in the sub-forum theme of the 2024 China Surveying and Mapping Geographic Information Science and Technology Annual Conference: "Remote Sensing Large Models and Intelligent Remote Sensing Applications" and Applications".
Guest introduction
Secretary of the Party Committee and President of the Guangdong Provincial Institute of Land and Resources Surveying and Mapping, Director of the Key Laboratory of Natural Resources Monitoring for Tropical and Subtropical South China of the Ministry of Natural Resources, and professor-level senior engineer. Graduated from Wuhan University of Science and Technology of Surveying and Mapping, majoring in engineering surveying.
He has long been committed to the application of surveying and mapping geographical information, spatiotemporal big data, artificial intelligence and spatial optimization decision support technology in the exploration and practice of natural resource management. The projects he has presided over have won many surveying and mapping science and technology awards and surveying and mapping outstanding engineering awards, and he has authorized multiple invention patents. He has won honors such as the National "Advanced Individual in Surveying and Mapping Emergency Support" and the Guangdong Province "May 1st Labor Medal".
Report topic
Exploration and Application of Artificial Intelligence
Report summary
Artificial intelligence is an important engine for developing new productivity. With the rapid development of large AI models, natural resource management is ushering in a leap from computational intelligence to perceptual intelligence and then to cognitive intelligence. The report deeply discusses the supporting role of intelligent surveying and mapping in promoting high-quality development of natural resources. Specific applications include intelligent generation of three-dimensional scenes, intelligent interpretation of remote sensing of natural resources, fine monitoring of cultivated land planting attributes, intelligent and accurate identification of marine aquaculture, early intelligent identification of disasters, and AI knowledge services, etc. Finally, it was concluded that to provide full-chain natural resource management services, government, industry, academia, and research still need to work together to achieve comprehensive intelligence in natural resource management and support the high-quality development of thousands of industries.
PPT sharing
