Scientists at the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS), in collaboration with their international collogues, have proposed a state-of-the-art deep-learning network, named EOLO, aiming to improve the detection of ocean eddies observed in C-band spaceborne synthetic aperture radar (SAR) imagery. This work has been published in Remote Sensing of Environment , which combines advanced AI algorithms with high-resolution spaceborne SAR data, providing a methodological basis for further studies of sub-mesoscale eddies.

A study published in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing sheds light on how plants respond to stress, specifically in the case of cotton plants affected by verticillium wilt (VW). This disease can wreak havoc on cotton crops but understanding how it affects the plants at the photosynthetic physiological level has been a challenge.

In a recent effort, researchers from the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences (CAS) have unveiled an unprecedentedly detailed dataset illuminating the complex network of water bodies sprawled across the Tibetan Plateau. Unlike previous studies, which primarily zoomed in on larger water bodies, this dataset paints a holistic picture by furnishing a high-resolution map of water bodies, pinpointing details down to a remarkable 2-meter precision for the year 2020.

A significant advancement in the field of remote sensing of China has emerged, as researchers from the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), unveiled their latest product – the "AIR·RingSee" integrated machine for remote sensing intelligence training and inference on October 26, 2023.

In the arid regions where desertification threatens dryland ecosystems, scientists from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS) have taken a closer look at the intricate relationship between natural factors and human activities on non-vascular plants, particularly biological soil crusts (BSCs) in China.

A research team led by Prof. WANG Junbo from the State Key Laboratory of Transducer Technology with the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS) introduced a novel simulation-based evolutionary method for the design of parameter-free MEMS (Micro-Electro-Mechanical Systems) structures. This innovative approach aims to maximize the degrees of freedom in MEMS design, opening the door to more efficient and adaptable microscale structures.