DEVELOPER TOOLS

AmberCore Software, the leading global provider of high performance spatial decision support systems, announced today advanced data processing capabilities targeted specifically at solving management of very large data sets. "The use of large data sets in GIS is on the increase," said Martin Sendyk, President and CEO of AmberCore. "But using these large data sets with most of today's GIS systems is cumbersome, slow and expensive for the end user. AmberCore's Amber iQ 2.0 series of spatial analysis software has now solved this issue for large data power-users." AmberCore unveiled its three stage solution for large data: (1) Minimize data pre-processing - Unlike other systems, Amber iQ places no limits on raster file sizes. Extremely large raster files can be incorporated into a GIS analysis as a single file. To the GIS user this means no extensive pre-processing of data, such as the division of large data sets into smaller, more manageable sub-sets. (2) Advanced memory management - For the processing of large point files, Amber iQ 2.5 (available later this month) buffers the data into memory, indexes the files intelligently according to the interpolation method being used, and access appropriately-sized pieces of data for processing. This enables linear processing and allows Amber iQ to manage extremely large data sets without overwhelming memory resources. The GIS user experiences extremely fast processing of large data files. (3) Optimized dynamic display technology - Amber iQ also effectively addresses the need for efficient viewing of large data sets. Viewing these files is extremely fast as Amber iQ employs an optimized dynamic display technology, which brings into memory only the portion of the data being viewed. Speed is then further increased by the pyramid data structure that Amber iQ employs for raster data sets. Viewing and analysis can be done in 2D or 3D. "The current Release 2.0 series of Amber iQ has been especially designed as a power-tool for large data power-users," said Boris Vorobiov, CTO and VP R&D. "For example, the response from LiDAR users has been excellent. LiDAR data points are typically collected at sub meter accuracy, resulting in data sets that can represent terabytes of information."