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使用引力模型和辐射模型测量可达性。

Measuring accessibility using gravity and radiation models.

作者信息

Piovani Duccio, Arcaute Elsa, Uchoa Gabriela, Wilson Alan, Batty Michael

机构信息

Centre for Advanced Spatial Analysis, University College London, 90 Tottenham Court Road, London W1T 4TJ, UK.

Nam.R, 4 rue Foucault, Paris 75116, France.

出版信息

R Soc Open Sci. 2018 Sep 12;5(9):171668. doi: 10.1098/rsos.171668. eCollection 2018 Sep.

DOI:10.1098/rsos.171668
PMID:30839729
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6170557/
Abstract

Since the presentation of the radiation model, much work has been done to compare its findings with those obtained from gravitational models. These comparisons always aim at measuring the accuracy with which the models reproduce the mobility described by origin-destination matrices. This has been done at different spatial scales using different datasets, and several versions of the models have been proposed to adjust to various spatial systems. However, the models, to our knowledge, have never been compared with respect to policy testing scenarios. For this reason, here we use the models to analyse the impact of the introduction of a new transportation network, a bus rapid transport system, in the city of Teresina in Brazil. We do this by measuring the estimated variation in the trip distribution, and formulate an accessibility to employment indicator for the different zones of the city. By comparing the results obtained with the two approaches, we are able to not only better assess the goodness of fit and the impact of this intervention, but also understand reasons for the systematic similarities and differences in their predictions.

摘要

自从辐射模型提出以来,已经开展了大量工作,将其结果与引力模型的结果进行比较。这些比较始终旨在衡量模型再现由起讫点矩阵描述的出行情况的准确性。这在不同空间尺度上使用不同数据集进行过,并且已经提出了模型的几个版本以适应各种空间系统。然而,据我们所知,这些模型从未在政策测试情景方面进行过比较。因此,我们在此使用这些模型来分析巴西特雷西纳市引入新交通网络——快速公交系统的影响。我们通过测量出行分布的估计变化来做到这一点,并为城市的不同区域制定就业可达性指标。通过比较两种方法获得的结果,我们不仅能够更好地评估拟合优度和这种干预的影响,还能理解它们预测中系统相似性和差异的原因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/4877567a69fb/rsos171668-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/51a5fc19ca1f/rsos171668-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/d724d52cd09a/rsos171668-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/312d65ca2ff8/rsos171668-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/4877567a69fb/rsos171668-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/51a5fc19ca1f/rsos171668-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/d724d52cd09a/rsos171668-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/312d65ca2ff8/rsos171668-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd4/6170557/4877567a69fb/rsos171668-g4.jpg

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