LATEST NEWS

SpectralX: Parameter-efficient domain generalization for spectral Remote Sensing Foundation Models Congratulations to Yuxiang Zhang, Prof. Shunlin Liang, and the research team on publishing a new article in the ISPRS Journal of Photogrammetry and Remote Sensing (Vol. 239, pp. 774-792). The article is titled “SpectralX: Parameter-efficient domain generalization for spectral Remote Sensing Foundation Models” and is available at https://doi.org/10.1016/j.isprsjprs.2026.06.008.

Fine-grained hierarchical crop type classification from integrated hyperspectral EnMAP data and multispectral Sentinel-2 time series: A large-scale dataset and dual-stream transformer method Congratulations to Dr. Wenyuan Li, Professor Shunlin Liang, and the research team on publishing a new article in Remote Sensing of Environment (Vol. 344, 115525). The paper is titled “Fine-grained hierarchical crop type classification from integrated hyperspectral EnMAP data and multispec

The JC STEM Lab of Quantitative Remote Sensing is proud to announce the recent publication of the Handbook of Satellite Land Products, co-edited by Lab Director Prof. Shunlin Liang and Prof. Han Ma. This monumental academic reference work provides a systematic, global guide to the satellite-derived information products essential for observing, understanding, and managing the Earth system. The book, published by Elsevier, is available at https://shop.elsevier.com/books/handboo