# How should I aggregate quantitative data from components to mapunits?

Components are each separate individual soils with individual properties and are grouped together for simplicity's sake when characterizing the map unit.

We often want to map data gathered and stored at the component level, but without knowing exactly where the component boundaries are, we must aggregate the data from components to mapunits. When the data we need to aggregate are quantitative such as crop yields, water table depths, or slopes then we can perform various mathematical procedures in addition to the qualitative tools like using the value from the dominant component or finding a limiting value.

Area-weighting is the most common form of quantitative aggregation. We'll examine area-weighted averages:

- Calculating an area-weighted average
- You can also use the qualitative techniques on quantitative data

An area-weighted average is useful when you want an average value for the mapunit but the data is stored by component. Simply averaging the component values gives erroneous results because the components can cover vastly different amounts of the mapunit. Instead, we multiply the data values by the percentage of the area that component covers and then we divide by the total of the area percentages. For example:

In the mapunit shown above, the RED component covers 75% of the area and has a water table depth of 36 inches. The other components, ORANGE and YELLOW, cover 12% and 8% of the area and have water table depths of 42 and 14 inches. The beginning of the area-weighted average calculation looks like this:

(.75*36 + .12*42 + .08*14) = 27 + 5.04 + 1.12 = 33.16

So the water table over these three components is at an average depth of 33.16 inches. However, these three components do not cover the entire area of the mapunit! (Why not? Because there are 'inclusions' which are too small to gather data on individually but collectively they take up a decent percentage of the area.) Therefore we must divide our answer by the sum of the area percentages like this:

33.16 / (.75 + .12 + .08) = 33.16 / .95 = 34.91

So, based on the data we have, the water table over the entire mapunit is at an average depth of 34.91 inches.

Note that you do not have to use the percentages of the area. Instead you could use any measure of area as long as you are consistent about it. That is, you can use acres but you must make sure to multiply each data value by the acres covered by the component AND sum up the acreages to divide by.Ready to try it yourself? Here's a problem for you. The answer is at the bottom of the page...do the calculation and then scroll down to check your method and your answer. The RED component covers 65% of the area and has a slope of 1%. The ORANGE and YELLOW components cover 16% and 12% and have slopes of 5% and 1.75%. What is the average slope for the entire mapunit?

You can, of course, use the dominant component or limiting property techniques when working with quantitative data as well. The limiting property method seems especially likely to be useful so that you can look for components where a value is above or below a set threshold.

Always remember that for different variables and different mapping purposes, different techniques are appropriate. Care is needed to make sure that the best method is being used.

```
```The
average slope for the mapunit in the problem above can be calculated
as follows:

(.65*.01
+ .16*.05 + .12*.0175) / (.65 + .16 + .12) =

(.0065
+ .008 + .0021) / .93 = .01471 / .93 = .0178

So
the average slope is 1.78% over the mapunit.

Right?

Right. Good work!