The spatial and topological organization of cities have a great influence on the lives of their inhabitants, including mobility efficiency. Entropy has been largely adopted for the characterization of the most varied natural and human-made systems and structures. In this work, we apply entropy to characterize the uniformity of spatial coverage allowed by the geometry, reflected by the area, of city blocks. It is suggested that this measurement can predict several properties of real cities, such as mobility. We consider several real-world cities, from which the average minimal shortest path length is also calculated and compared with the entropy of the block areas. Several interesting results have been found and are discussed in the article.
Thank you very much for your interesting work.
I have some questions:
1. what do you mean by divisional entropy? In this paper, divisional entropy is used to measure the uniformity of blocks' size in a given city?
2. I am a little confused by Figure 6. Higher value of the entropy means more uniform block areas in a city. In Figure 6, you say "Higher values of the entropy of block areas correspond to higher values of shortest path lengths", which means more uniform block areas in a city has higher values of shortest path lengths. Am I right? However, in Section 3, you say "So, a city with more
uniform block areas will tend to have shortest paths. " So I am really confused. Can you explain it? Thank you!
Best Wishes,
Feiyan Liu
Many thanks for reading and commenting on our conference article. Regarding your two questions, we would like to observe that:
1. The divisional entropy has been defined in section 2.4, Equation (2). The uniformity of the block areas is reflected in this measurement. Actually, we used the exponential of this entropy (which we call evenness), which is also a measurement of block area uniformity.
2. We had used an incorrect figure, and a new version of our manuscript was updated just before your question. As you can verify, the new Figure 6 is now coherent with the interpretation that, for the considered data set (some of cities in California), higher evenness of city blocks area tends to be related to smaller average shortest path length.
Yours sincerely, The authors
