One main reason current software has problems handling modern terrain data is that the data is orders-of-magnitudes larger than the underlying software algorithms were designed to handle. Many existing applications assume that their data fit in the main memory of the computing device, however, modern massive terrain data is often much larger than the main memory and must reside on external storage devices such as disks. This results in efficiency problems since disk data access is typically 1,000,000 times slower than main memory access. Since software that does not use the disk efficiently is essentially slowed down by this factor, large datasets are often thinned before processing or broken up into tiles that are processed separately. The first may result in the loss of important terrain features, which can significantly (or even catastrophically) reduce the accuracy of many topological analysis applications, while the latter often results in cumbersome workflows and undesirable artifacts at the tile boundaries.
SCALGO software relies on novel I/O-efficient algorithm research to efficiently handle your massive terrain data that resides on slow disks. Such algorithms take advantage of the fact that large blocks of data can be accessed just as fast as single data items on disk to effectively hide the large difference in access time of main memory and disk. This way your massive terrain data sets can be handled without the need for thinning or tiling.
Efficiency problems with existing software often mean that data is thinned before processing. This can lead to significant (or even catastrophic) inaccuracies as can be illustrated by showing the effect of a sea-level rise of 2 meters on the island Mandø in Denmark. left: using a thinned 90-meter resolution model - right: using a full 2-meter resolution terrain model; In the thinned model important topological features (the small dike around the island) are lost, leading to a useless result. SCALGO software enables processing of full-resolution data, which leads to more reliable analysis.