Produced by DAMO Academy, the industry's first large-scale remote sensing AI model is here! A single model can identify everything on the surface such as farmland, crops, and buildings, which can greatly improve the analysis efficiency of remote sensing applications such as disaster prevention, natural resource management, and agricultural yield estimation. The model is now available on the AIEarth Earth Science Cloud Platform.
For example, if you enter "Extract farmland from images", the selected target will be automatically recognized.
The Remote Sensing AI Interpretation Universal Segmentation Model (AIE-SEG) proposed by DAMO Academy is the first to achieve unified image segmentation tasks in the field of remote sensing.
One model can quickly extract "zero samples of everything" and can identify nearly a hundred types of remote sensing land objects such as farmland, water, and buildings. It can still maintain high-precision recognition under multi-task processing, and can also automatically tune the recognition results based on the user's interactive feedback.
In some specific scenarios, compared with traditional remote sensing models, the accuracy of instance extraction can be increased by 25%, and the accuracy of change detection can be increased by 30%.
Based on the above basic capabilities, the remote sensing AI large model provides "out-of-the-box" API calling services. Users can customize different remote sensing AI interpretation functions according to different needs, such as water extraction, farmland change monitoring, photovoltaic identification, etc.
The Shandong Provincial Institute of Land Surveying and Mapping has cooperated with DAMO Institute in the fields of natural resource survey and cultivated land protection since 2022, using large remote sensing AI models to conduct winter wheat growth monitoring research in Shandong Province. The recognition accuracy reached more than 90%, effectively improving the efficiency of winter wheat remote sensing interpretation, helping agricultural managers better predict grain yields and improve agricultural production efficiency.
The National Institute of Natural Disaster Prevention and Control uses large remote sensing AI models to identify landslides and collapsed buildings. In the test of remote sensing images of historical natural disaster areas, it only takes more than ten minutes to extract this disaster information, which is dozens of times more efficient than manual identification methods, providing efficient and accurate remote sensing analysis support for scientific disaster relief.
Luo Hao, head of AIEarth algorithm at DAMO Academy's visual technology laboratory, said that multi-modal remote sensing is the only way to advance human beings to better understand the earth. DAMO Academy will continue to promote the research of remote sensing AI large models and use AI to assist the exploration and application of earth science.
AIEarth is a one-stop earth science cloud platform released by DAMO Academy in 2022. Based on the accumulation of technologies such as deep learning, computer vision, and geospatial analysis, it provides cloud computing analysis services for multi-source observation data. It currently cooperates with 50+ universities in China, and related technologies have been applied to institutions such as the Ministry of Water Resources, the National Meteorological Center, and the Ministry of Ecology and Environment.