Abstract: In the method of 3D spatial data capturing based on the image sequences, people want to extract 3D data for each pixel, but the data extracted from this way need to be greatly simplified if used for 3D modeling in 3D Geographical Information System (3DGIS). On the other hand, if sparse texture areas exist in the images, it’s difficult to overcome the error matches. This paper presents a vector based matching algorithm. The algorithm takes one image as a continuous 3D surface, and mainly matches feature areas by computing vectors in each normal vector on the surface and matching corresponding vectors. The summary of cosine values of corresponding vectors and feature description value of the corresponding areas in two match windows are adopted as the cost factors. The changes of vectors reflect the image texture information, which can be used to evaluate image feature areas, filter sparse texture areas to avoid mismatch and save computer time. The results from experiment in the last part of the paper indicate that the proposed algorithm is effective for sparse depth map producing and can satisfy 3D modeling in 3DGIS.