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In this study, a new approach for the matching and reconstruction of line features from multispectral stereo aerial images is presented. The advantages of the existing multispectral information in aerial images are fully taken into account all over the steps of pre-processing and edge detection. To accurately describe the straight line segments, a principal component analysis technique is adapted. The initial correspondences between the stereo images are generated using a new pair-wise stereo matching approach which involves a total of seven relational constraints. The final line to line correspondences between the stereo images are established in a precise matching stage in which the final line matches are assigned by means of three novel measures and a final similarity voting scheme. Once the line matches are established, the stereo reconstruction of those matches is performed by an innovative reconstruction approach that manipulates the redundancy inherent in line pair-relations. By this way, the reconstruction of the stereo matches that are observed in a nearly-parallel geometry with the epipolar lines can also be performed accurately. The proposed approach is tested over two different urban test sites with various built-up characteristics, and as a result, very successful and promising stereo line matching and reconstruction performances are reached. Besides, the comparison of the results of the proposed approach with the results of one of the state-of-the-art stereo matching approaches proves the superiority and the potential of proposed approach.