Cross-Validation of Surface Reflectance Between GF5-02 AHSI and EnMAP Across Diverse Land Cover Types

Multi-source hyperspectral data are increasingly applied in environmental monitoring, precision agriculture, and geological exploration, yet differences in sensor characteristics hinder interoperability. This study presents a systematic cross-validation of surface reflectance between the German EnMAP mission and the Chinese GF5-02 Advanced Hyperspectral Imager (AHSI) across four representative land cover types: minerals in the East Tianshan Mountains, tropical grasslands in Hainan Danzhou, desert in Dunhuang, and inland salt lakes in Qinghai. Using EnMAP Level-2A products as reference, we evaluated GF5-02 reflectance with spectral angle (SA), root mean squared error (RMSE), relative RMSE (RRMSE), and correlation coefficient (R). Results show strong consistency for high- and medium-reflectance surfaces (R > 0.96, SA < 0.08 rad), while water bodies exhibit larger discrepancies (R = 0.82, SA = 0.34 rad), likely due to atmospheric correction and sensor response differences. Additional ground validation in the East Tianshan region confirmed the reliability and stability of GF5-02 data. Overall, GF5-02 demonstrates high consistency with EnMAP across most land cover types, supporting quantitative applications, though further improvements are needed for low-reflectance environments.