Making sense of terrain data through access and visualization
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terrain visualization↗
Engineering topics
Plesea, L.
Publications and source records attributed to Plesea, L..
Access and visualization using clusters and other parallel computers
JPL's Parallel Applications Technologies Group has been exploring the issues of data access and visualization of very large data sets over the past 10 years. this work has used a number of types of parallel computers, and today includes the use of commodity clusters. This talk will highlight some of the applications and tools we have developed, including how they use parallel computing resources, and specifically how we are using modern clusters.
parallel computers clusters↗
Large area remote sensed imagery: data, tools, tricks, and tips
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remote imagery↗
Ter(r)ascale ter(r)acomputing framework : a high performance information technology framework for global scale high resolution remote sensed data
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terascale computing↗
A framework for run time fusion, visualization and analysis of large, distributed data sets
In this paper a framework is presented for extracting information content from modern sky surveys, which have archived multiple terabytes of data in various wavelengths and at various resolutions.
virtual observatory visualization supercomputing↗
Building large scale mosaics from Landsat data
This paper describes the process and tools used for creating a full resolution seamless Landsat mosaic of the continental U.S. at 30 meters per pixel.
Mosaic Landsat supercomputing↗