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An integrated atmospheric-topographic correction framework for land surface reflectance estimation using a spatial-spectral Attention U-Net model Congratulations to Dr. Yichuan Ma, Professor Shunlin Liang, and the research team for their recent publication in Remote Sensing of Environment  (Vol. 334, 115188). The paper, titled "An integrated atmospheric-topographic correction framework for land surface reflectance estimation using a spatial-spectral Attention U-Net model," is

AgriFM: A multi-source temporal remote sensing foundation model for Agriculture mapping Congratulations to Dr. Wenyuan Li, Professor Shunlin Liang, and the research team for their recent publication in Remote Sensing of Environment  (Vol. 334, 115234). The paper, titled "AgriFM: A multi-source temporal remote sensing foundation model for Agriculture mapping," is available via https://doi.org/10.1016/j.rse.2026.115234 . The codes and models are freely accessible at https://gla

Generating an annual 30 m rice cover product for monsoon Asia (2018–2023) using harmonized Landsat and Sentinel-2 data and the NASA-IBM geospatial foundation model Congratulations to Husheng Fang, Professor Shunlin Liang, and the research team for their recent publication in Remote Sensing of Environment  (Vol. 335, 115256). The paper, titled "Generating an annual 30 m rice cover product for monsoon Asia (2018–2023) using harmonized Landsat and Sentinel-2 data and the NASA-IB