September 12, 2012
SCALGO has released version 1.2 of the software package SCALGO Hydrology, which can be used to perform basic hydrological modeling on massive raster terrain models (containing tens of billions of cells) on a normal desktop computer.
The new version contains a number of new features that make it easier to perform large-area hydrological analysis. These features include handling of massive collections of polygon data, which e.g. allows for easy and efficient "burning" of a large number of features (such as buildings, bridges and culverts) that are important for hydrological modeling into a large-area terrain model. The release also includes functionality that allows for efficient computation of various measures (height, area, volume) of all depressions (including depressions inside other depressions) in massive raster terrain models, which e.g. allows for easy and efficient identification of the depressions and terrain areas most important for hydrological modeling.
As the previous version, all SCALGO Hydrology 1.2 modules can be run through a standalone graphical user-interface or from within ArcGIS. In SCALGO Hydrology 1.2 the newly released ArcGIS version 10.1 is supported and an ArcGIS viewer has been added that allows for easy visualization of the output of many of the package modules.
The new release also contains updates to the standalone user-interface and to some of the core algorithms, including the utilization of multiple CPU cores. Overall, the most significant updates in SCALGO Hydrology 1.2 include:
Information about SCALGO technology, products and services can be found at http://scalgo.com. Future information about SCALGO products and services can also be received directly through Twitter and Facebook.
Scalable Algorithmics (SCALGO) was founded in 2009 with the mission to bring cutting-edge massive terrain data processing technology to market. The SCALGO technology is based on more than two decades of basic and applied research on I/O-efficient and geometric algorithms at Center for Massive Data Algorithmics (MADALGO) at Aarhus University in Denmark and at Duke University in the US, in collaboration with industry LiDAR and environmental GIS application experts. Software based on the technology can handle much larger terrain data sets on a normal desktop than most current software and thus it eliminates the need for accuracy-decreasing data thinning. The use of novel mathematical and algorithmic techniques also means that the software works provably efficient on all input data sets, delivering a completely specified output without the use of cumbersome workflows such as those introduced by data tiling. SCALGO is involved in multiple research projects and offer special pricing for academic institutions.