<p>Least squares matching (LSM) is a well-known area-based method for matching between two perspective images. It uses a 2D geometrical transformation to match distorted regions captured from different perspectives. This idea is used here to find a global transformation, contrary to the traditional LSM with its local matching nature, between 3D LiDAR data and 2D high-resolution satellite imagery (HRSI). The proposed method exploits the whole of the overlapped regions between the LiDAR data and the HRSI to find a 3D transformation to relate LiDAR and HRSI. To do so, the radiometric similarity of the HRSI and LiDAR data has also been enhanced by adding shadows and topographic effects to the LiDAR intensity data to act as a proper entity in matching with the HRSI. The results indicate that accurate 3D registration to one-pixel precision can be obtained, on average, even when parameters from approximate 2D transformations are used as initial values.</p>