Crusta combines 1.) representation of global, high-resolution surface data, 2.) visualization of these data on a real-time virtual globe, and 3.) efficient exploration and annotation using real-time interactive software tools. Using Crusta one can easily import sub-meter resolution DEM or imagery for arbitrary locations on the globe. Dynamic manipulation of the visualization (illumination, vertical exaggeration, iso-lines) support explorative discovery of key surface features and a clear understanding of their three-dimensional embedding. Such features can be directly mapped on the virtual landscape. This capability greatly improves the confidence and localization of mapped features. The majority of movies on this website demonstrate Crusta.


LiDAR Viewer provides an opportunity for the user to view LiDAR point cloud datasets without sub-sampling or reducing the data. The program will load in a point cloud and display each individual point from the survey. LiDAR Viewer allows the user to select points and extract them to a separate file, extract primitives (plane, sphere, cylinder) from selected points, determine distance from a plane, and navigate in real-time through large datasets (>2.7 billion points). It is a powerful tool that can provide unique insight from LiDAR datasets that are difficult to attain using DEMs.

• Map the trace of the Enriquiilo fault and prepare a 3D model of the fault. This will enable us to use the newly available imagery to seek evidence of the most recent earthquake and penultimate events from the 18th century. We plan to use this fault model in forward simulations of fault interaction using Virtual California, GeoFEST, or another appropriate code.

• Rapidly assess the data for ground rupture, liquifaction, landslides, and other structures, and, if needed, pass observations to researchers in the field. Though reports from the field and our own investigations indicate that ground ruptures are minimal from this event, we continue with with the assessment because our analysis tools may able to reveal features in the new data that are difficult to identify using other methods. We also plan to map other active structures in southern Haiti that are broadly part of the Enriquillo fault zone and that will help to understand the structural context of the 2010 and penultimate events.

• Using methods that we have developed for automated feature extraction and surface characterization, analyze LIDAR and other remote sensing data for the extend and scope of damage and the presence of damaged features.

Rates of deformation are important for predicting earthquake frequency. We seek to understand how slip rates vary along the Enriquillo fault in southern Haiti to its termination in the southwestern Dominican Republic, as well as the relationship Enriquillo fault slip to the rate and style of deformation of flanking structures in southern Haiti.