Plants’ morphology changes in their growing process. The 3D reconstruction of plant is of great significance for studying the impacts of plant morphology on biomass estimation, illness and insect infestation, genetic expression, etc. At present, the 3D point cloud reconstructed through 3D reconstruction mainly includes the morphology, color and other features of the plant, but cannot reflect the change in spatial 3D distribution of organic matters caused by the nutritional status (e.g. chlorophyll content), as well as illness and insect infestation of the plant. Multispectral photography can reflect the distribution of organic content and other chemical values, and has been extensively applied in such fields as near-ground remote sensing and non-destructive test of quality of agricultural products. In this paper, 31 pieces of multispectral images of 4-leaf rapes are collected for spatial 3D reconstruction through the structure from motion (SFM) method to obtain the 3D point clouds of the rape and filter noise points therein. The maximum length deviation is found to be 0.1023cm and the RMSE is 0.052599 after the model obtained is evaluated with the control point and length, indicating that this method is of good spatial uniformity and accuracy in reconstructing the model obtained. NDVI exponential spatial distribution is then calculated. It is finally proved that the model obtained is of great significance for studying the spatial distribution of plant nutrition, illness and insect infestation in the future.