Change detection of objects, such as buildings, is essential for map updating. Traditionally, detection is usually performed through spectral analysis of multi-temporal images. This article proposes a method that employs multi-temporal interpolated lidar data. The objective of this study is to perform change detection and change-type determination via geometric analysis. A shape difference map is generated between the digital surface models in two different time periods. The areas with small shape differences are treated as non-changed areas and are excluded from the segmentation. The object's properties are then applied to determine the change types. Experimental results demonstrate that the proposed scheme achieves accuracy as high as 80%. Most of the errors from this study occurred in small or vegetation areas.