We are requesting an startup allocation on the XSEDE Comet supercomputer resource in order to manage and process high resolution topography data (including lidar based point cloud data) for the NSF funded OpenTopography project. Over the past decade, there has been dramatic growth in the acquisition of publicly funded high-resolution topographic and bathymetric data for scientific, environmental, engineering and planning purposes. Because of the richness of these data sets, they are often extremely valuable beyond the application that drove their acquisition and thus are of interest to a large and varied user community. However, because of the large volumes of data produced by high-resolution mapping technologies such as lidar, it is often difficult to distribute these datasets. Furthermore, the data can be technically challenging to work with, requiring software and computing resources not readily available to many users. Some of these complex algorithms require high performance computing resources to run efficiently, especially in an on-demand processing and analysis environment. With the steady growth in the number of users, complex and resource intensive algorithms to generate derived products from these invaluable datasets, HPC resources are becoming more necessary to meet the increasing demand. By utilizing the comet XSEDE resource, OpenTopography aims to democratize access and processing of these high-resolution topographic data.