
It is recognized that 80% of data have a spatial component (ex. street address, place name, geographic coordinates, map coordinates). Having the possibilities to display data on maps, to compare maps of different phenomena or epochs, and to combine maps with tables and statistical charts allows one to get more insights into spatial datasets. Furthermore, performing fast spatio-temporal analysis, interactively exploring the data by drilling on maps similarly to drilling on tables and charts, and easily synchronizing such operations among these views is nowadays required by more and more users. This can be done by combining Geographical Information Systems (GIS) with On-Line Analytical Processing (OLAP), paving the way to “SOLAP” (Spatial OLAP). The present chapter focuses on the spatial characteristics of SOLAP from a geomatics engineering point of view: concepts, architectures, tools and remaining challenges.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 28 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
