Image maps are raster maps based on grid files. These maps represent Z values (e.g.
elevations) with user specified colors. Blanked regions on image maps are
normally shown as a
The mapping from the Z value to the color is normally defined interactively
and can be set by the user. A novel and effective method is to assign
specific colors to specified Z values using color anchor points within a
pop-up dialog box, as is the case with . You can add
color anchor points at any Z level. Each anchor point can be assigned a unique color, and
automatically blends colors between adjacent anchor points to produce a smooth
color gradation over the map.
It's handy if the color schemes for image maps can be saved for re-use
later. If this is possible (as it is in )
then the colors defined for one image map can be used with any other image map.
In , since the
color anchor points are stored as a percentage of the grid data range, a single color
spectrum file can be used for multiple maps, even if the associated grid files cover
significantly different data ranges. This is a wonderful feature to find
in reasonably priced, off-the-shelf software!
Another important feature to have in visualization software is the ability
to combine image maps with other maps
in "map overlays". Image maps can normally be scaled, clipped, or moved in the same way as
other types of maps.
When a coarse grid (a grid with relatively few rows and columns) is used to generate an
image map, all pixels within a single grid square are assigned the same color. This
can result in an image map with a very blocky appearance. The software
uses a pixel interpolation routine with coarse grids to create a smoother appearance.
When a dense grid (a grid with relatively large numbers of rows and columns) is used,
little difference is seen between the final image maps whether a pixel interpolation
algorithm is employed or not. For dense grids, therefore, on-screen drawing time can often
be reduced by turning off any pixel interpolation.