Hyperspectral Analysis of Pigment Identification and Abundance Inversion in the Dome of China’s Yungang Grotto 7

Abstract. Most of the grotto temples have undergone long-term weathering and multiple repainting campaigns, so accurate identification of the composition and spatial abundance of surface pigments is an important foundation for pigment characterization and conservation research. This study focuses on the dome of Yungang Grotto 7. Data were acquired using a three-dimensional (3D) hyperspectral multimodal digital acquisition system and the Analytical Spectral Devices (ASD) field spectroradiometer. The workflow consisted of two stages: pigment identification and abundance inversion. In the pigment identification stage, a normalized weighted identification method integrating Spectral Angle Mapper (SAM) and the Normalized Difference Spectral Index (NDSI) was proposed based on mineral pigment reflectance curves measured by the ASD field spectroradiometer. In the abundance inversion stage, Fully Constrained Least Squares (FCLS) was applied to estimate pigment proportions in mixed pixels under non-negativity and sum-to-one constraints. The results show that the green pigments are most likely malachite and Paris green, the red pigments are most likely hematite and laterite, and the black pigment is most likely carbon black. The interwoven distribution of Paris green and traditional mineral pigments provides material-science evidence for modern repainting and restoration in this area. Nonlinear mixing may occur on rough and weathered grotto surfaces. However, under the current data conditions, its influence on abundance inversion remains unclear. Therefore, Kernel Fully Constrained Least Squares (K-FCLS) was additionally introduced as a reference nonlinear model for qualitative comparison with FCLS.