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.