A magnitude-7.5 earthquake struck western Colombia on Aug. 10, 2026, causing widespread damage across 32 cities. According to figures released by local authorities on Aug. 15, the death toll had risen to 294, with 3,935 people injured.

Researchers from the Aerospace Information Research Institute, Chinese Academy of Sciences; Sichuan University of Science and Engineering; and the Institute of Atmospheric Physics, Chinese Academy of Sciences, reported the study in the Journal of Remote Sensing​ on April 29, 2026. The article presents a new satellite-based method for retrieving global, direct, and diffuse solar radiation from FY-4A. The work targets a key operational problem: how to deliver accurate sunlight estimates at high spatiotemporal resolution without relying heavily on dense ground observations or auxiliary atmospheric datasets.

Researchers from 16 Chinese institutions, including the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS), Beijing Normal University, Peking University, Sun Yat-sen University, and Tsinghua University, published the editorial in the Journal of Remote Sensing​. The article addresses the limitations of fragmented, static, and largely offline observation systems by defining scientific and technical priorities for real-time, cross-platform, and intelligent remote sensing services in climate monitoring, ecological assessment, emergency management, and planetary exploration worldwide today.

Researchers from the Aerospace Information Research Institute, Chinese Academy of Sciences, have developed a new radiative transfer model named CARE-RTM that simulates the propagation of sunlight through the atmosphere and ocean with improved precision and computational speed. CARE stands for Cloud Remote Sensing, Atmospheric Radiation and Renewable Energy Application, reflecting the model's broad coverage of key research areas in Earth observation. The model provides a physical tool for extracting climate and environmental information from satellite data. The findings are published in Advances in Atmospheric Sciences​.

A new machine-learning algorithm could help meteorologists detect heavy rainfall more accurately and in near real time using China's Fengyun-4B geostationary meteorological satellite. Developed by a research team led by Associate Professor JI Dabin from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS), in collaboration with Associate Professor BAO Shanhu from Inner Mongolia Normal University and XIE Yanhui from the Institute of Urban Meteorology, China Meteorological Administration, the algorithm addresses two persistent challenges in satellite-based precipitation monitoring: limited information beneath cloud tops and a severe imbalance between rainy and non-rainy samples.

Hyperspectral LiDAR can recover soil spectral information from beneath vegetation canopies and help estimate key soil properties, according to a study published in Remote Sensing of Environment. The findings offer a new approach to monitoring soils in vegetated areas, where exposed ground is often limited or unavailable.