A new study led by Professor LU Shanlong from the Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), has published in Communications Earth & Environment, reveals that since 2019, when the previously isolated Zonag-Yanhu drainage basin became connected to the headwaters of the Yangtze River, both hydrological and ecological processes within the basin have undergone rapid transformation.

A research team led by Prof. NIE Sheng at the Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), has developed a new bathymetric mapping framework that integrates indirect inversion of ICESat-2 satellite LiDAR data with multi-source remote sensing observations. The framework, detailed in Remote Sensing of Environment combines wave-based indirect bathymetry, multi-source feature fusion, and a temporal sample-transfer strategy to achieve high-accuracy, wide-coverage mapping in optically complex shallow waters.

A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS), in collaboration with the Center for Advanced Studies in Earth Sciences and Biodiversity (CADIC-CONICET), Argentina, has revealed major blind spots in current Antarctic vegetation mapping caused by the poor detectability of dark-colored lichens.

A recent study published in Microsystem & Nanoengineering​ introduces an innovative solution to the persisting challenges in Micro-Electro-Mechanical Systems (MEMS) resonant accelerometers: temperature drift and measurement dead zones. By adopting a dual-mode operating scheme that effectively separates the operating frequencies of the differential beams, the researchers achieved notable improvements in the sensor's accuracy and overall performances.

A research team from the State Key Laboratory of Remote Sensing and Digital Earth, in collaboration with the Laboratory of Electromagnetic Radiation and Detection Technology at the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS), has successfully completed field testing of a self-developed unmanned vehicle-mounted glacier penetrating radar on the Bayi Glacier in the central Qilian Mountains. The tests ran from October 10 to 25, 2025.

A new study published in Scientific Reports has evaluated land productivity dynamics (LPD) across the African Great Green Wall (GGW) from 2013 to 2022, offered a decade-long perspective on one of the world’s most ambitious initiatives to combat desertification in the Sahel. It aims to assess progress toward the United Nations’ Sustainable Development Goal (SDG) 15.3 for Land Degradation Neutrality (LDN) and identify the key factors driving land productivity change to guide more effective restoration strategies.