Xinran Li
Papers
1
Total Citations
27
H-Index
1
About
Xinran Li is a leading researcher in environmental remote sensing and atmospheric science, whose work has fundamentally advanced the monitoring of air quality through big Earth data analytics. Her primary research areas include aerosol optical depth (AOD) retrieval, fine particulate matter (PM₂.₅) estimation, and the development of gap-free, high-resolution environmental datasets. Li’s most significant contribution is the creation of the Long-term Gap-free High-resolution Air Pollutants (LGHAP) dataset, with the v2 iteration providing spatially contiguous daily AOD and PM₂.₅ concentrations at a 1 km grid resolution across China since 2000. This breakthrough, detailed in her 2024 paper (27 citations), addresses a critical gap in environmental monitoring by eliminating spatial data voids, enabling more accurate long-term exposure assessments and epidemiological studies. Her work has been instrumental in supporting policy decisions for air pollution control and public health research. By leveraging machine learning and multi-source satellite data, Li has set a new standard for global air quality datasets, making her a pivotal figure in the intersection of big data analytics and environmental science.
Research Focus
Key Achievements
Top Papers
- 1