In the process of landslide deformation monitoring, the indicators of monitoring system based on surface displacement cannot accurately reflect the deformation evolution law of deep geotechnical body. Although the joint time curve of deep displacement monitoring of borehole and related monitoring data can reflect the deformation characteristics inside the slope body, it cannot spatially describe and explain the overall deformation process of geotechnical body completely due to the limitation of technical conditions such as borehole. In this paper, using the characteristics of resistivity imaging technology with fast and accurate collection of electrical information of subsurface medium and multi-dimensional imaging, we take resistivity imaging data as complete modal data and fuse deep displacement and groundwater level and other modal data. Through joint depth matrix decomposition and optimization, layer-by-layer modal semantic matching and updating, the distribution and representation differences of modal data are compensated, and the analysis tasks such as classification and clustering of incomplete multimodal data are completed, and the inversion results of resistivity data are updated according to the output modal shared eigenvalues to realize effective multidimensional imaging monitoring of the internal deformation process of landslide geological bodies.