DGGS Operations

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 multi-resolution grid structure.  

PYXIS DGGS SDK allows developers to build custom DGGS solutions in comprehensive C++ and C# Libraries.  A hosted 3D DGGS visualization and geo-processing application is ready to exploit using a REST API with C# or JSBoolean, relational, image processing, image algebra, mathematical morphology, frequency transforms, and other functions are exposed within:

DGGS Expressions and Processes

 Expressions and processes are classified by efficient MapReduce operations:
  • Iterations (Locate)- Operations that traverse over DGGS cell indices and extend to iterate over the set of all cells in a given geometry:

    Play With Topological Relationships

    • Nearest neighbor;
    • Parent/child; and
    • Feature geometry.
  • Selections (Filter) - Operations that generate a collection of cells (also referred to as a geometry):
    • User Selected;
    • Implied by Indexing;
    • Algebraic on Indexing;
    • Boolean on Values;
    • Algorithm on Values;
    • Buffering;
    • Connectivity Table;
    • Set Theory & Topological Relationships;
    • Point Analysis; and
    • Image Segmentation.
  • Computations (Map) - Operations that modify existing or add a new value to a cell:
    • User Input;
    • Sampling and Quantization; 
    • Arithmetic Calculations on Values;
    • Mathematical Morphology;
    • Convolution Filters; and 
    • Multi-Resolution Spatial Analysis Process.
  • Aggregated Summaries (Reduce) - Operations that characterize a collection of cells:
    • Spatial Statistics;
    • Derivatives;
    • Histogram; and
    • Frequency Transformations.
These basic operations are used to build expressions that generate:
  • Cell Location;
  • Geometries; 
  • Cell Values; and 
  • Aggregated Characteristics, respectively. 
Processes are easy to use and, when connected together, provide a simple geo-analytic workflow within the PYXIS pipe and filter architecture (PIPE) and the PYXIS DGGS Language.
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