8.7 Chapter Summary

Raster Data Models

  • Raster data are derived from a grid-based system of contiguous cells containing specific attribute information.
  • The spatial resolution of a raster dataset represents a measure of the accuracy or detail of the displayed information.
  • The raster data model is widely used by non-GIS technologies such as digital cameras/pictures and LCD monitors.
  • Care should be taken to determine whether the raster or vector data model best suits your data or analytical needs.

Geoprocessing with Raster Imagery

  • Overlay processes place two or more thematic maps on top of one another to form a new map.
  • Overlay operations using vector data include the point-in-polygon, line-in-polygon, or polygon-in-polygon models.
  • Union, intersection, symmetrical difference, and identity are common operations used to combine information from various overlain datasets.
  • Raster overlay operations can employ powerful mathematical, Boolean, or relational operators to create new output datasets.

Scale of Raster Analysis

  • Local raster operations examine only a single target cell during analysis.
  • Neighborhood raster operations examine the relationship of a target cell’s proximal surrounding cells.
  • Zonal raster operations examine groups of cells that occur within a uniform feature type.
  • Global raster operations examine the entire areal extent of the dataset.

Spatial Interpolation for Spatial Analysis

  • Spatial interpolation estimates those unknown values found between known data points.
  • Spatial autocorrelation is positive when mapped features are clustered and negative when mapped features are uniformly distributed.
  • Thiessen polygons are a valuable tool for converting point arrays into polygon surfaces.

Terrain Mapping for Spatial Analysis

  • Nearest neighborhood functions are frequently used on raster surfaces to create slope, aspect, hillshade, viewshed, and watershed maps.


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