Researchers from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences have developed a new method for mapping carbon dioxide (CO₂) emissions across Nanchang, the capital city of Jiangxi province in eastern China, providing a clearer picture of the city's carbon footprint. Their findings were recently published in the International Journal of Digital Earth.

Scientists from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS), in collaboration with Shihezi University, have developed a new method for grading cotton Verticillium wilt (VW). This method correlates with yield loss and is suitable for remote sensing monitoring to assess VW severity. Their research has been recently published in Agricultural and Forest Meteorology.

A research team led by Prof. DI Kaichang from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS) has developed an innovative method to advance the study of lobate scarps—small reverse fault landforms thought to reflect ancient tectonic activity on the Moon.

Current satellite systems underestimate total CO₂ emissions from U.S. thermal power plants by 70% (±12%), according to a study published in the Journal of Remote Sensing. Led by researchers at the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS), the analysis highlights critical gaps in remote sensing technology, including coarse spatial resolution (1.29×2.25 km² for the Orbiting Carbon Observatory-2 satellite, or OCO-2; 1.6×2.2 km² for OCO-3), limited precision (~1 ppm), and infrequent revisit cycles (16 days). However, the study estimates that next-generation satellites—equipped with 0.5 km resolution, a precision of at least 0.7 ppm, and daily monitoring capabilities—could reduce errors to below 20%. This advancement would represent a transformative leap in strengthening global carbon accountability.

An international team of researchers has developed the world's first 30-meter resolution dataset to track changes in land productivity—a critical dataset for fighting global land degradation. Published in Scientific Data (https://www.nature.com/articles/s41597-025-04883-3), this innovation promises to help nations track progress toward Sustainable Development Goal (SDG) 15.3, which aims to achieve a "Land Degradation Neutrality" (LDN) world by 2030.

A research team led by Prof. SHI Chong from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS), in collaboration with Japanese scientists, has made a breakthrough in satellite-based air quality monitoring. The team has developed AIRTrans, an innovative algorithm that dramatically improves the accuracy and efficiency of retrieving key aerosol properties from multispectral satellite observations.