Rapid Delivery of Massive Geospatial Data Over Internet2

We study the feasibility of the on-demand delivery of a massive geospatial dataset over Internet2 for educational use. The dataset (20TB uncompressed, 2.5TB compressed), generously made available for this study by AirphotoUSA, provides a seamless, one-meter resolution aerial orthophotograph covering over three million square miles of the continental United States. We identify factors that limit the scalability, availability and user-perceived performance of serving such a dataset. To do this, we conduct experiments that measure response times for various levels of network congestion, bandwidth, and load. We also provide a proof-of-concept experiment by serving the dataset over Internet2 to students at Oklahoma State University. Given this information, we determine the server-side architecture and resource requirements sufficient to serve this dataset from Cal Poly. We discuss the funding for wide distribution of high-resolution datasets to universities and the student response to use of this data for education

EFFECTIVE DIFFUSIVITY FOR TRANSIENT GASEOUS DIFFUSION IN POROUS MEDIA

Abstract not availabl

Forest Roads Mapped Using LiDAR in Steep Forested Terrain

LiDAR-derived digital elevation models can reveal road networks located beneath dense forest canopy. This study tests the accuracy of forest road characteristics mapped using LiDAR in the Santa Cruz Mountains, CA. The position, gradient, and total length of a forest haul road were accurately extracted using a 1 m DEM. In comparison to a field-surveyed centerline, the LiDAR-derived road exhibited a positional accuracy of 1.5 m, road grade measurements within 0.53% mean absolute difference, and total road length within 0.2% of the field-surveyed length. Airborne LiDAR can provide thorough and accurate road inventory data to support forest management and watershed assessment activities