9. What are indicators, and why are we using them?
Indicators are a tool. They are a way to measure the potential impact each scenario has on things like average wage, housing affordability, and access to frequent transit.
The indicators help us better understand the link between how a community develops and average wages, or how a community develops and how many people can access transit, etc. In turn, they help us evaluate and more fully compare the scenarios to each other.
10. How accurate are the indicator results?
On a high-level, pretty accurate. On a detailed level, less so.
The indicator results come from a model. The results are not meant to be exact numbers or percentages that reflect what will happen in the future. That is not their purpose. Instead, the indicator results show us how the scenarios compare to each other on a high level.
Here's an example. The indicator "Complete Neighborhood" shows the percentages of households that meet certain criteria such as ½ mile to a neighborhood park, ½ mile to grocery store, and 1 mile to a public elementary school. The model measures those distances using a straight line radius, not walking distance along an actual street route. That means, the results – percentages of complete neighborhoods – may seem high, but the comparison between the scenarios is more accurate. More new households will likely live near a grocery store, neighborhood park, and elementary school in Scenarios C and D than in Scenario A.
It's also worth noting a difference between the model and scenario maps. The scenario maps illustrate high-level ideas. They do this by showing swaths of land being developed or redeveloped into certain types of land uses (e.g., different colors on the maps). The model, however, does not assume that every property that is colored in the scenarios will be developed or redeveloped. That would not be practical. The indicator results, therefore, are based on some of the properties being developed as shown in the scenarios.
11. Why are some of the indicators different from Phase 1?
In Phase 1, the community chose 20 indicators. Since then, people have had a lot of questions about how future growth is going to impact transportation, particularly congestion. In response, we asked the Mid-Willamette Valley Council of Governments (MWVCOG) to use their transportation model to help answer the questions. Their model produced several results, including the new indicators on mode split (e.g., breakdown of how people travel), vehicle miles traveled, and vehicle hours of delay. Because we used the MWVCOG's transportation model, we did not run our consultant's separate transportation model that we used in Phase 1.
We did not carry forward a few of the indicators from the first phase for various data reasons. For example, in Phase 1, we measured bicycle and pedestrian use. Specifically, we looked at the percentage of people who were projected to bike and walk to work. In this visioning phase (phase 2), we used the MWVCOG's transportation model, which provides data on travel mode split. It provided trips by bicycle and walking – as well as by bus and vehicle – and it included all trips, not just trips to work like the model we used in Phase 1. We did not want to cause any confusion by having different results for biking and walking from different models, so we just stuck with mode split as an indicator.
Another example is annual traffic crashes. In phase 1, we used our consultant's transportation model, which produced crash data. That was largely based on historic data for per capita crashes. During this visioning phase (phase 2), we used the MWVCOG's transportation model, which cannot produce crash data.