Next Article in Journal
Ensemble Estimation of Information Divergence
Next Article in Special Issue
Intrinsic Computation of a Monod-Wyman-Changeux Molecule
Previous Article in Journal
Quantum Dynamics and Non-Local Effects Behind Ion Transition States during Permeation in Membrane Channel Proteins
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Entropy 2018, 20(8), 559; https://doi.org/10.3390/e20080559

A Novel Index Based on Binary Entropy to Confirm the Spatial Expansion Degree of Urban Sprawl

School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210046, China
*
Authors to whom correspondence should be addressed.
Received: 18 May 2018 / Revised: 25 June 2018 / Accepted: 25 July 2018 / Published: 27 July 2018
(This article belongs to the Special Issue Information Theory in Complex Systems)
Full-Text   |   PDF [3927 KB, uploaded 27 July 2018]   |  

Abstract

The phenomenon of urban sprawl has received much attention. Accurately confirming the spatial expansion degree of urban sprawl (SEDUS) is a prerequisite to controlling urban sprawl. However, there is no reliable metric to accurately measure SEDUS. In this paper, based on binary entropy, we propose a new index named the spatial expansion degree index (SEDI), to overcome this difficulty. The study shows that the new index can accurately determine SEDUS and, compared with other commonly used measures, the new index has an obvious advantage in measuring SEDUS. The new index belongs to the second-order metrics of point pattern analysis, and greatly extends the concept of entropy. The new index can also be applied to other spatial differentiation research from a broader perspective. Although the new index is influenced by the scaling problem, because of small differences between different scales, given that the partition scheme in the research process is the same, the new index is a quite robust method for measuring SEDUS. View Full-Text
Keywords: urban sprawl; point pattern analysis; binary entropy; index urban sprawl; point pattern analysis; binary entropy; index
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Chen, Z.; Zhou, Y.; Jin, X. A Novel Index Based on Binary Entropy to Confirm the Spatial Expansion Degree of Urban Sprawl. Entropy 2018, 20, 559.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top