Urban Areas 3 : derivation from OSM using residential blocks

View S from the Cathedral of Learning in Oakland, Pittsburgh,
showing some urban areas used as tests in this post.

The incised valley of the Monogahela in the background contained railways and steel works. The plateau beyond has residential suburbs of Pittsburgh. To the left foreground are the woods and ravines of Schenley Park, with a residential area beyond. Source: Zack Weinberg via Wikimedia Commons CC-BY-SA

One of the obvious features of the highway network for the USA on OpenStreetMap is that road density is much higher in built-up areas. I started looking at how to measure this, when I recalled a method for identifying city blocks introduced to me by a Brazilian user of OpenStreetMap data.

Residential Areas for Butler Co, Pennsylvania, identified with the block method
from OpenStreetMap data. Orange line outlines Butler County.

My idea was simple, a greater road density implies smaller areas for the polygons enclosed by a set of roads. By choosing some maximum polygon size, one should be able to pick out urban areas.

The method itself is also really quite simple:

• Take the main road network for some area and make a union of it (which will be a MULTILINESTRING).
• Polygonize this data, and decompose to individual polygons.

In Lucas' implementation the first step is done by municipal areas. I wanted to try the approach for a whole state without using administrative area data. I therefore once again turned to my trusty standby of using a gridded method.

Persistence in the Urban Environment : 1

Anyone reading this blog should have realised that I am interested in using maps to understand how the environment we live in has changed over time. I know I share this interest with many other OSMers. There have been many proposals, and discussions about how we might use some of the principles and technologies of OSM to create maps representing an area at some historical time point. I am greatly heartened that a new mailing list (http://lists.openstreetmap.org/listinfo/historic) has appeared for interested parties to share ideas on this subject:

Wollaton Park Estate from the E, (June 1928)

One problem which has exercised my mind, and particularly from my exercise at looking at the OSM edit history of Berlin, was how adding a history (or time) dimension to geographical data might impact on data volume. In thinking about this I have been struck that a very large proportion of the urban environment of cities in Europe and North America is remarkably static. This was brought home by the recent availability of historical aerial photographs of Great Britain (at the Britain from Above website).

Wollaton Park Estate on OSM