This research work proposes a novel cost calculation method that considers shadow occlusion areas to address the issues of poor disparity estimation in urban areas, termed Matching Cost based on Shadow Properties (MCSP), error estimation of the shadow occlusion area, which not only considers the problem of disparity error estimation in the shadow occlusion areas but also considers the problem of edge integrity and smoothness in the disparity estimation results. Firstly, a shadow detection model is established through the double constraints of spatial angle and distance to detect and mark the shadow areas in complex scenarios self-adaptively. This makes the model robust and overcomes the singleness of the threshold segmentation method. Then, an edge feature term considering both the shadow and non-shadow areas is constructed and introduced into the matching cost calculation to form MCSP that can make the edges of the disparity estimation results as complete and smooth as possible. To verify the optimization ability and transferability of MCSP, the MCSP cost is integrated into three classical disparity estimation algorithms respectively. The experimental results demonstrate that the MCSP is suitable for both aerial images and satellite remote sensing images. The qualitative and quantitative evaluation results show that MCSP is superior to two classical cost calculation methods and shows good transferability and applicability in the popular disparity estimation algorithms, which can significantly enhance the definition of the edges of the ground objects and improve the quality of the disparity estimation in the shadow occlusion areas.