A connectivity index is a simple way to measure the connectivity of a street network. The index defines two aspects of a network: nodes and links. Nodes are intersections, dead ends or cul-de-sac heads. Links are the streets that link the nodes together. You divide the number of links by the number of nodes to get the connectivity index. An example is shown here, from the Kentucky model ordinance. A disconnected network with a lot of dead ends and cul-de-sacs has fewer links than a grid network. A grid network doesn’t have to have streets that are straight, by the way; they can be curvy, it just matters that they link up with each other. The goal is to have an index of 1.4 or greater. Some cities actually require new subdivisions to achieve this measure.
Notice that in the second diagram, one internal connection has been made and two links have been added to connect the subdivision to adjacent land. That improves walkability by allowing more direct routes; it also improves safety by creating more than one entrance and exit to the neighborhood.
Obviously you need more than connected streets to make a place walkable. You need to be close to destinations like stores, restaurants, schools, parks, and transit stops. You need good sidewalks or paths, a feeling of safety, and so on.
That leads to more ways to measure walkability.
The Walkability Checklist is sponsored by several different organizations. It gets down into the weeds about the condition of a particular walk, but it doesn’t address the network issues at all. This checklist is good for bringing up problems to your city or town: problems such as dangerous crosswalks or speeding cars. But it focuses on the negative. In the multiple choice questions, there are a lot of reasons you can pick for why the walk was not good (including scary dogs and scary people), but no reasons for why it was good (friendly dogs, friendly people, pretty gardens, …).
There’s a very complete survey called the Neighborhood Environment Walkability Survey or NEWS, developed by a professor in San Diego. According to its description, “NEWS is a 98-question instrument that assesses the perception of neighborhood design features related to physical activity, including residential density, land use mix (including both indices of proximity and accessibility), street connectivity, infrastructure for walking/cycling, neighborhood aesthetics, traffic and crime safety, and neighborhood satisfaction.” It can be used to correlate these various characteristics of neighborhoods with the amount of walking people do.
In contrast to this time-consuming survey, Walk Score is an on-line tool that you can use simply by putting in an address. It attempts to quantify some of the important criteria remotely, using public sources like maps and census data. It looks at the distance to amenities and gives maximum points to something that is a five minute walk or less, but no points to something that’s more than 30 minutes away. It also considers intersection density and block length, which are measures of connectivity. Walk Score is bound to be less accurate than on-the-ground assessments, but it gives a rough idea and is especially popular with realtors. It’s easy to use and fun to compare different neighborhoods. It also breaks down the score into components. You might do well on proximity to destinations but badly on quality of the sidewalks, for example. It allows users to make corrections to it as well.
The lengths of blocks is an important element of walkability that is considered in Walk Score. Most experts say blocks should be no more than 400 feet long in order to make walking attractive. If blocks are too long, people are discouraged from walking or else they will take short cuts.
Those short cuts can tell you a lot about the pedestrian friendliness of an area. Some towns provide paths to make connections that are not available on the streets. But when those are not available, people frequently create their own paths. Called “desire lines,” these worn paths are an indication of inadequate pedestrian infrastructure.
The following maps show the town of Middlebury, VT (pop. about 8,600). The first map shows the street system, and the second includes the pedestrian paths. Some of those paths are maintained by the town or by private property owners (called “official” on the map) and some are unofficial desire lines. The very dense network of paths on the college campus is not included. Note the shortcuts across the railroad tracks, and the ones connecting the college campus to nearby neighborhoods where many employees live. One 860-foot long block in the center of town has two paths across it, effectively breaking it up into segments about 300 ft. long, just as one would predict.
Now we will take a neighborhood near the elementary school and shopping district, and see if the pedestrian paths bring the connectivity index up to the desired 1.4.
Connectivity Index: Middlebury Example
The following maps show a neighborhood of Middlebury VT called Buttolph Acres. It contains single family homes and a few condo complexes, an elementary school, a courthouse, a church, a social service agency, and businesses along the major roads to the west and northwest. There’s a large park to the east.
The first map shows the streets only. The second map shows the streets and the paths.
In the street system: 44 links/35 nodes = a connectivity index of 1.26.
In the system of streets plus paths: 63 links/44 nodes = a connectivity index of 1.43.
Yes! The paths, both official and unofficial, bring the connectivity index up above 1.4.
These two small examples in Middlebury support the connectivity index and block length metrics, based on where people actually walk. Wouldn’t it be nice to build these characteristics into new developments in the first place?