China Unveils Lunar Radar Project to Map Geology, Aid Moon Missions

On March 5, 2025, Beijing hosted the kick-off meeting for the National Natural Science Foundation of China's major project, "Microwave Imaging Radar for Lunar Exploration and Geological Process Inversion". Led by Prof. WANG Yu from the Aerospace Information Research Institute under the Chinese Academy of Sciences (AIRCAS), this project is a pivotal initiative in China's deep space exploration efforts with the aim to advance lunar exploration through cutting-edge microwave imaging technology and geological analysis.

Mar 25, 2025

---

Scientists Develop GLOSTFM: A Breakthrough Model for High-Resolution Global Land Surface Temperature Monitoring

A research team led by Professor MENG Qingyan from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS), in collaboration with domestic and international institutions, has successfully developed GLOSTFM, a high-efficiency spatiotemporal fusion model based on multi-source satellite data. By integrating thermal infrared and microwave observations from the Fengyun-3D satellite, GLOSTFM significantly enhances the spatiotemporal resolution of land surface temperature (LST) data, providing a powerful tool for global climate change studies and urban heat island monitoring. The research findings have been published in the Remote Sensing of Environment.

Mar 21, 2025

---

Photonic Clock Chip Paves the Way for Next-Generation Ultra-Fast Computing and Communications

A research team from Peking University and the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS) has developed a new photonic clock chip that offers a key advancement for future ultra-fast computing for AI development, 6G networks, autonomous vehicles, and remote sensing.

Mar 12, 2025

---

Scientists Develop Novel Method to Detect Polluted Water in Rural Areas, Tackling Algal Blooms

Chinese scientists have developed a novel method to detect and monitor polluted water in rural areas—a critical step toward tackling harmful algal blooms and contaminated ponds. By combining high-resolution satellite imagery with deep learning methods, researchers from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS) can now pinpoint ponds overrun by duckweed or algae with remarkable accuracy.

Feb 28, 2025

---

Research Identifies Limitations of SIF Algorithms in Monitoring Photosynthetic Dynamics

A study published in the Journal of Remote Sensing by a research team from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS) evaluates three algorithms—Band Shape Fitting (BSF), Three-band Fraunhofer Line Discrimination (3FLD), and Singular Vector Decomposition (SVD)—designed to measure solar-induced chlorophyll fluorescence (SIF) in plants. These algorithms aim to improve the accuracy of SIF data, which is essential for monitoring photosynthesis in both ecological and agricultural research.

Feb 28, 2025

---