In Part 1 of this two-part post, I outlined how I would create a heat map of the county showing areas of high inundation risk, low prior investments, and high vulnerability.

This month, in Part 2 of this two-part post, I will describe how we might build the composite heat map and how it could be used to identify areas for future flood resilience investments.

Building the Composite Heat Map

Last month I described three input variables that I would use to create a composite heat map of flood risk reduction needs. The three layers included:

— The Flood Risk (annual chance of inundation);

— The Flood Mitigation Benefit Index (FMBI); and,

— The Social Vulnerability Index (SVI).

These are useful data, but they are not integrated or combined yet. Each variable can be used to create a separate heat map. How can we combine these three maps into one composite map?

Overhead Transparency Projectors

I attended high school in the 1980s. At that time many teachers used an overhead transparency projector to present information to the class. They would place transparent sheets of plastic on a light box, light would shine up through the sheet, hit a mirror, shine through a lens, and get projected onto a screen for the class to see. The sheets would sometimes have pre-printed information or the teacher might actually write with a marker on the sheet as they presented the information. Here’s a photograph of one of these old devices.

Transparencies for Planning

We can create a transparent sheet for each of the layers we’d like to consider when creating the composite heat map. Today we can do this with Geographic Information System (GIS) mapping software, but I thought it would be helpful to illustrate the idea using clear sheet transparencies.

I created a hypothetical area of the county with nine U.S. Census Blocks. I also created three hypothetical transparencies for consideration; one for flood risk, one for FMBI, and one for SVI. In each map, the red color indicates a greater need for future resilience investments and the green color indicates a lower need for future resilience investments. The numbered rectangular shapes are hypothetical U.S. Census Blocks.

The flood risk map shows that Blocks 1, 2, 3, 7, and 8 have very high risks, while 5 has a very low risk.

Here’s the Flood Mitigation Benefit Index (FMBI) map:

The FMBI map shows a wide range of index values within the very high flood risk areas on the left side of the image.

Here’s the SVI map:

The SVI map shows very highly vulnerable people in Block 8 with high to moderate vulnerability in Blocks 2 and 7.

Equal Weight Example

If we place all three transparencies on the overhead transparency projector at the same time and without any adjustment, we see an equal weight composite. This means that all three variables – flood risk, FMBI, and SVI are considered equally. Take a look:

The equal weight composite heat map shows that additional resilience investments are needed in U.S. Census Blocks 7 and 8 (and perhaps 2 if we have sufficient funding). The legend colors don’t exactly match up anymore because of the way the layered colors blend.

Variable Weight Example

Let’s say we decide the current flood risk is the most important factor we should consider, followed by SVI, and then followed by FMBI. Let’s also say we think that flood risk should be six times more important than the FMBI and three times more important than the SVI. This logic would yield the following weight factors and transparency levels. Note that the transparency level goes down with a high weight to allow that layer to influence the composite more strongly. Also, note that the assignment of the weights is a policy choice – not an engineering choice.

	Weight Factor	Transparency Level
Flood Risk	60	40
Flood Mitigation Benefit Index	10	90
Social Vulnerability Index	20	80

Here are the new transparencies with the weight factors and transparency levels applied:

Here is the new composite heat map we see after we place all three of the weighted transparencies on the overhead projector:

The weighted composite heat map shows that future resilience investments are needed in U.S. Census Blocks 1, 2, 3, 7, and 8 (and perhaps 6 and 9 if we have sufficient funding). The legend colors don’t exactly match up anymore because of the way the layered colors blend.

Discussion of Results

Compare the weighted result to the equal weight result.

The equal-weighted composite heat map showed that future resilience investments are needed in U.S. Census Blocks 7 and 8 (and perhaps 2 if we have sufficient funding). The weighted composite heat map showed that future resilience investments are needed in U.S. Census Blocks 1, 2, 3, 7, and 8 (and perhaps 6 and 9 if we have sufficient funding). What accounts for this difference?

In the first example, all three input variables were considered equally. In the second example, flood risk was considered to be six times more important than FMBI and three times more important than SVI.

Implications for Planning

This article shows how policy decisions regarding the relative importance of various factors will lead to different decisions and different outcomes. It shows why elected officials and the public should stay engaged in planning efforts to let planners know what factors and weights they should be considering.