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hector_slam performs localization only in 2D, but if you combine that information with IMU data (for roll and pitch) and additional data about the z position (from prior knowledge, odometry or other sensors), it can be used for 3D mapping. This approach is used for building a 3D octomap-based map via mapping with known poses using a RGB-D sensor with our autonomous USAR robots as visible in this video.
Depending on your accuracy requirements, sensor motion and scale of environment other solutions might be worth a look. See for instance this recent video made using a Velodyne HDL-64e. ethzasl_icp_mapping also uses libpointmatcher and you could try that.
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