In a recent editorial published in the Innovation Geoscience, researchers from the Aerospace Information Research Institute (AIR) with the Chinese Academy of Sciences (CAS) highlight the significant advances in multimodal AI foundation models in Earth observation techniques, particularly in unlocking the power of remote sensing big data, and their profound impact on our understanding of the planet's various facets.

A recent breakthrough from researchers at the Chinese Academy of Sciences propels this field forward. As reported in Advanced Photonics Nexus, they achieved a remarkable 60-milliwatt (mW) solid-state DUV laser at 193 nm with a narrow linewidth using a sophisticated two-stage sum frequency generation process employing LBO crystals. The process involves pump lasers at 258 and 1553 nm, derived from a Yb-hybrid laser and an Er-doped fiber laser, respectively. This setup, culminating in a 2mm×2mm×30mm Yb:YAG bulk crystal for power scaling, demonstrates impressive results.

In a recent study published in the Bio-Design and Manufacturing on Feb. 22, a research group led by Prof. WU Yirong from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS) has unveiled a new method for improving deep brain stimulation treatments for PD, focusing on the STN - a critical area for managing the disease's symptoms.

In a bid to understand urban thermal environments better, researchers from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS) have developed a comprehensive dataset on anthropogenic heat (AH) emissions in China.

A recent study published in the Journal of Remote Sensing on March 13 introduced a new method for estimating plant productivity. Researchers from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS) developed a dataset called CMLR GPP (Canopy-scale Mechanistic Light Reaction Gross Primary Production) with an exceptional spatial resolution of 0.05 degree. This dataset offers estimates of gross primary production (GPP) spanning from May 2018 to December 2021 on a global scale.

Understanding how our planet's land cover changes over time is crucial for tackling climate change. However, getting detailed, long-term data has been tough. That's where a land-cover dataset called GLC_FCS30D comes in: the latest released dataset offers an unprecedented glimpse into global land-cover dynamics from 1985 to 2022 at a remarkable 30-meter resolution.