A recent study has unveiled an innovative data-driven model that disentangles human-induced and natural water consumption in croplands, shedding new light on the sustainability of arid lake ecosystems. By harnessing the power of remote sensing and machine learning, the research quantifies the impact of agricultural expansion on water resources, offering a crucial blueprint for balancing irrigation demands with environmental conservation. This innovation provides policymakers and conservationists with a powerful tool to mitigate water scarcity and prevent the disappearance of critical freshwater lakes.

A research team from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS) has released a long-term and high-resolution dataset that tracks global cropland water-use efficiency (WUE) from 2001 to 2020. Published in Scientific Data, the dataset offers annual WUE estimates for croplands worldwide at a 1-km spatial resolution. It is expected to become a valuable resource for promoting sustainable agricultural water management.

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.