A research team led by Professor LU Shanlong from the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences, has developed a machine learning approach to simulate three-dimensional (3D) underwater topography of lakes. The study, published in Big Earth Data​, introduces a method based on the XGBoost algorithm that requires only a digital elevation model (DEM) as input. This study provides a promising solution for generating lakebed topography in regions where data are limited.

A new study has, for the first time, mapped long-term, large-scale transport pathways of PM2.5 pollution across China from 2000 to 2021. Published in Geoscience Frontiers, the research introduces an innovative data-driven framework based on the Dynamic Times Warping (DTW) method to trace how air pollutants have moved across the country during the two decades. The findings offer critical insights into the evolution of PM2.5 transport and provide scientific support for more effective air quality management.

Researchers at the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences, have developed a novel approach for assessing urban sustainability using data from the SDGSAT-1 satellite. Their study, published in Remote Sensing of Environment, demonstrates that high-resolution (10 m) Glimmer Imager observations can reveal detailed patterns of human activity, population aggregation, and intercity connectivity across China’s three major urban agglomerations: the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Guangdong–Hong Kong–Macao Greater Bay Area.

Published in Scientific Reports, the research is led by Dr. LIANG Dong from the Aerospace Information Research Institute, Chinese Academy of Sciences. By combining high-resolution satellite data from the Sentinel-1 and Sentinel-2 with advanced analytical techniques, the study explores how snow algae growth, temperature changes, and snowmelt interact on two major Antarctic ice shelves—Brunt and Riiser-Larsen ice shelves—between 2019 and 2022.

A recent study published in the International Journal of Digital Earth presents a first city-level assessment of urban sustainability trends across more than 7,000 urban centers in the Belt and Road Initiative (BRI) region. Utilizing multi-temporal Earth observation (EO) data, the research evaluates two SDG 11 indicators—Land Use Efficiency (LUE, SDG 11.3.1) and population-weighted PM₂.₅ concentrations (PPM₂.₅, SDG 11.6.2)—from 2000 to 2020, providing a spatiotemporal analysis of sustainability of urban spatial expansion and environmental exposure.

A research team led by Dr. CHENG Tianhai at the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences has made significant progress in monitoring methane emissions from landfills. By leveraging high-resolution satellite remote sensing, the team developed a method for accurately quantifying methane emissions from landfills. This method was applied to conduct a comprehensive global assessment of landfill emissions. The findings were published in Nature Climate Change​ on July 28, 2025.