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.

Researchers at the Chinese Academy of Sciences' Aerospace Information Research Institute (AIR) have unveiled a groundbreaking Multi-Dimensional Data (MDD) format and MARS software that unifies time, space, and spectral dimensions of satellite data for the first time. Published in The Innovation and led by Professor ZHANG Lifu, this innovation processes Earth observation data 482% faster than industry-standard ENVI software while using 97% less storage—solving decades of fragmentation in environmental monitoring.

A study published in Environmental Science & Technology introduces a satellite-based method that significantly improves the accuracy of carbon dioxide (CO₂) emission estimates from coal-fired power plants. Developed by researchers at the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences, the approach enhances our ability to track greenhouse gas emissions in near real-time—crucial for global efforts to combat climate change and achieve national climate goals.

A recent study published in Nature Communications unveils that 17.31% of tropical tree cover—equivalent to 395.9 million hectares (Mha)—has been consistently overlooked by global forest monitoring systems. Using high-resolution satellite imagery (<5m) and an advanced automated algorithm, an international research team mapped previously undetected tree cover (PUTC) across pan-tropical regions from 2015–2022. Their findings highlight significant net losses and critical blind spots in current forest conservation efforts.

A team of Chinese researchers has developed a powerful new method to create highly detailed 3D models of cities using radar data, helping overcome long-standing challenges in urban mapping. By combining artificial intelligence (AI) with building geometry, the new technique—called Geo-SETRA—can produce clearer, more complete images of urban landscapes, potentially transforming how cities are monitored, planned, and protected.