You are here: Home > Maps > Oregon Earthquakes > Data Drop Shadow
Oregon Earthquakes: Creating a drop shadow effect for geographic features
Rate this effect!
Without a drop shadow effect; notice the northern and eastern borders of Oregon.
Without a drop shadow effect; notice the northern and eastern borders of Oregon.
With a drop shadow effect; the map of Oregon appears to elevate one level in the visual hierarchy.
With a drop shadow effect; the map of Oregon appears to elevate one level in the visual hierarchy,

What: Sometimes you want to create a little visual hierarchy on your page layout by arranging maps and other map elements such as legends, titles and text block on top of each other. Why: This creates a more visually pleasing map since the map reader can see variation in the levels of information and there is more distinction between page elements. To learn more about visual hierarchy, see pages 12-14 in Designing Better Maps.

How: One way you can achieve this effect is to copy the data frame for the map you want to add a drop shadow to. Delete all the features in the data frame that will not be used to create the "shadow" and symbolize the remaining features with a gray fill or other symbol for a shadow. Position the "shadow" data frame under the map data frame and adjust its position so that it is slightly offset both vertically and horizontally (in our case, to the north and east).

This solution is better than creating a new data frame, positioning it under the map data frame in the table of contents, adding the feature class that has the area being mapped, changing the symbology to a gray fill, and shifting the data frame. When you copy the data frame, you don't have to worry about making the size and scale of this data frame the same as the data frame you are shadowing - it is done automatically because it is a copy. And you don't have to add the features that will be used to create the shadow -- you only have to delete the features that will not.


To make finely tuned adjustments to the location of the data frame, use the option to set the position by specifying its x,y location on the page as well as the anchor point. To do this, right click the data frame, select Properties, and click the Size and Position tab. Then set the location of the anchor point you want to use, and modify the x and y locations so they position the shadow data frame where you want.

Exporting the results to pdf or other file type posted by Matthew Hogan on Sep 25 2008 5:55AM
I followed the instructions for creating a shadow effect found here, Oregon Earthquakes: Creating a drop shadow effect for geographic features. I copied the dataframe, removed all the layers except buildings, shaded them gray, shifted the frame, and looks great in ArcMap. However, when I export the maps as either a pdf or jpeg (even if I turn the background color off in the export options) the shadows I created do not show up. It seems that even though niether dataframe has a fill asigned that the software assumes the fill for each data fram is white, thus my nice shadowed buildings are covered.

Any thoughts?

That should work posted by Charlie Frye on Sep 25 2008 3:05PM
If you notice, our PDF link on the main page for the Oregon Earthquake Map has this effect working properly. So, the no frills scenario should work well. One possibility is that you've got transparency--in the upper data frame, which, as I remember will force the background of that data frame to white. If that wasn't the problem, definitely contact technical support (through your organization's usual channels) as they have a comprehensive list of things to check.
Further information posted by Aileen Buckley on Sep 25 2008 10:27PM
Here is some further clarification on this issue:

There is a long-standing issue with data frame background "transparency" which is really a limitation of our current display and output pipeline using the Microsoft GDI. This is NIM006938, outlined in Knowledge Base article 17336:

The reason the workflow described here works in this example (the Oregon earthquakes map) is because the data frame contains only vector data, so the content is maintained as vector on output and the background doesn’t show up as white. As the article noted above explains, if any layers in the inserted dataframe are transparent or have other rasterizing symbology, the entire dataframe must be rasterized, resulting in a white background.

The workaround is to remove any rasterizing symbology inside the inset dataframe. One tool you could use to find out whether any of the symbology in that dataframe is rasterizing is the “Detect Complex Output” developer sample: This sample will tell you which layers in the dataframe cause rasterization, so you can remove the cause of the rasterization if desired.

If you would like to post a comment, please login.

Contact Us | Legal | Privacy |