The research team at the Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), has conducted a comprehensive remote sensing forecast for wheat pests and diseases across Asia, Europe, and North America.

A recent study has unveiled the first comprehensive, long-term dataset of global industrial heat sources (GIHS) from 2012 to 2021. This dataset, published in the Scientific Data, was developed by a team of researchers from the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences (CAS, offering insights into the spatio-temporal distribution of industrial heat sources worldwide.

Researchers from the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences (CAS) have developed a spatiotemporal migration method to accurately map China's soybean cropland. Leveraging Sentinel-1/2, the innovative technique has yielded 10-m maps of China's soybean cropland spanning from 2019 to 2022. The study was published in Scientific Data.

Researchers at the Aerospace Information Research Institute (AIR) with the Chinese Academy of Sciences (CAS) proposed a novel approach to assess dynamics in photoprotective pigments （carotenoids, anthocyanins, and betalains）at the canopy level. This advancement reveals the climatic conditions under which these adjustments typically occur across various global land ecosystems, providing insights into plant adaptation to detrimental environments.

A study published in the Remote Sensing of Environment conducted a bibliometric analysis spanning from 1992 to 2022, which reviewed and described the transformative influence of a century of advancements in RSA.

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.