DGGS provide a uniform discrete environment to integrate, visualize, and transform Earth data. The structure of the DGGS provide opportunities to simplify most spatial operations. Efficiency is gained as operations and algorithms can be created on the grid structure independent of data sources. Spatial queries are primarily simple set theory operations. Multi resolution characteristics of the DGGS allow for progressive refinement of spatial queries. Topological relationships between two regions can be described within an efficient binary matrix (Dimensionally Extended 9 Intersection Model). As each cell of a DGGS is equal area, spatial statistics on aggregated cells are uniformly generated independent of location. Predictive modelling techniques like finite element, agent based and cellular automaton can use the DGGS multiresolution grid structure.
PYXIS DGGS SDK allows developers to build custom DGGS solutions in comprehensive C++ and C# Libraries. A hosted 3D DGGS visualization and geoprocessing application is ready to exploit using a REST API with C# or JS. Boolean, relational, image processing, image algebra, mathematical morphology, frequency transforms, and other functions are exposed within: Expressions and processes are classified by efficient MapReduce operations:
These basic operations are used to build expressions that generate:
Processes are easy to use and, when connected together, provide a simple geoanalytic workflow within the PYXIS pipe and filter architecture (PIPE) and the PYXIS DGGS Language.
