How To Do a Buildout Analysis
by G. Peterson
September 16, 2008
Figuring out how a given area of land is going to change in the future is what a good buildout analysis does. There are a lot of different ways to accomplish this, though, and many measurements that can be used. The first thing you have to ask is what is it about a potential change in landuse that concerns you? Is it the increase in population? Is it the increase in paved areas? Is it a decrease in forest? Overall degree of urbanization? While these are all related, answering this can further refine your approach because it will help you select the right proxy statistic to measure. Simply identifying the change in land uses can also be useful but not necessarily quantifiable.
There are some algorithms that use population predictions, which many municipalities routinely forcast, to determine future degree of urbanization, for example. These are not usually very precise but can give a general directional trend and somewhat of an idea of how things will look at a precise point in the future (typically 20, 50, or 100 years out).
The method I'll focus on here is modeling future impervious surface percentages based on current landuse, zoning regulations, and current impervious surface. This article is a very simplified version of what it takes to conduct such an analysis. For a much more thorough discussion of the topic and an actual implementation scenario, please see the Projects page.
Steps to conduct an impervious surface buildout:
- Obtain parcel level GIS data - these data must have some sort of current landuse identification. Usually the tax assessor department keeps track of landuse via codes, but sometimes you may have to make due with a field containing information on number of houses in the parcel. Then at least you can determine whether or not it is a residential, vacant, or commercial parcel.
- Develop a grouping schema. Group the landuses into logical categories. You'll want several residential categories that have set lot sizes. One dwelling unit on a quarter-acre lot can be one category while one dwelling unit on a 10 acre lot can be in another category, etc. Break out commercial lots into different kinds of commerce if you think that different impervious surface percentages would be associated with each. Industrial categories can vary widely in impervious surfaces so break those out (usually, light, medium, and heavy or some such).
- Obtain a current impervious surface dataset at the largest possible scale. You can do this yourself using open source software and free NAIP imagery or hire it out.
- Overlay the impervious surface data with the parcels that have been grouped into landuses. 5) Figure out the average impervious surface within each unique landuse.
- Use zoning rules to determine which landuse groups the parcels will be in in the future. For example, a low-density residential parcel might buildout to a commercial parcel if it is in a commercial zone. Be consistent. Always use the most aggressive potential buildout scenario if you want to know for sure what the highest level of buildout could be. Don't forget that a large parcel with one house on it could be subdivided if it is in a high-density residential zone. You have to do a series of calculations in the GIS to assign the new buildout landuse groups to those kinds of parcels (depending on the current number of houses, current parcel size, etc.)
- Use the average impervious surface statistics from step 5 to assign buildout impervious surfaces to each parcel depending on the buildout landuse group you've assigned them to in step 6.
- Quantify changes from current to buildout using some sort of logical grouping mechanism such as watershed, riparian corridor, estuary, or municipality.
And that's it — easy as pie, right?!