You are here

Geospatial Data Analytics Group presents current work to Office of Naval Research

Accurate and high-quality terrain data is usually generated via expensive data acquisition methods such as aerial imagery or light detection and ranging (LiDAR) flights, where three dimensional representations of an object are created by measuring the reflected pulses of laser light that illuminate the object. These methods are also limiteds to geographical areas the collection team has physical access to.

Prof. Rongjun Qin discusses his research at the ONR Science Fair, September 2018Associate Professor of Geodetic Engineering Rongjun Qin’s research group has been investigating alternative methods of generating accurate, three dimensional content in city-scale, for Virtual Reality/ Augmented Reality (VR/AR) applications on behalf of the United States Office of Naval Research (ONR). The team’s ongoing work integrates free, street-level images from sources such as cell phones and Google street view with satellite stereo images obtained from high-resolution, commercial and civilian satellites to create 3D base models.

 

Xu Hang and Xiaohu Lu display their team's research in Quantico, VA.

In September 2018, Dr. Qin, postdoctoral researcher Dr. Xu Huang and Ph.D. student Xiaohu Lu showcased their research at the ONR Science Fair in Quantico, Virginia. Qin’s team demonstrated a software package that provides a real-time, online computation of topographic generation from satellite images as well as preliminary results from its previous work integrating street-level with satellite-derived imagery.

Qin sees a great benefit in using alternative methods to supply data to support the miltary’s education and combat training applications. “Using low-cost satellite and crowdsourcing data can significantly bring down the acquisition cost,” he stated, which allows military personnel to be trained safely and effectively in these immersive, artificial environments.

Professor Qin's Geospatial Data Analytics Group will continue to support the ONR team in large-area terrain data generation from satellite photogrammetric reconstruction for their research and experimental purposes.