基于近邻传播聚类元胞自动机模型的武汉城市扩散和聚合过程同步模拟

doi:10.11821/dlxb202110013

地理学报 ›› 2021, Vol. 76 ›› Issue (10): 2522-2535.doi: 10.11821/dlxb202110013

基于近邻传播聚类元胞自动机模型的武汉城市扩散和聚合过程同步模拟

何青松¹(), 谭荣辉², 杨俊³()

1.华中科技大学公共管理学院,武汉 430074
2.天津大学管理与经济学部公共管理学院,天津 300072
3.东北大学江河建筑学院,沈阳 110004

收稿日期:2020-10-13 修回日期:2021-06-06 出版日期:2021-10-25 发布日期:2021-12-25
通讯作者: 杨俊(1978-), 男, 湖北孝昌人, 教授, 博士生导师, 主要从事城市遥感应用研究。E-mail: yangjun8@mail.neu.edu.cn
作者简介:何青松(1990-), 男, 安徽肥西人, 博士, 副教授, 硕士生导师, 主要从事城市增长模拟、地理过程建模研究。E-mail: baihualin2013@163.com
基金资助:
国家自然科学基金项目(42001334)

Synchronized simulation of urban diffusional and aggregational process based on the affinity propagation cellular automata: A case study of Wuhan city

HE Qingsong¹(), TAN Ronghui², YANG Jun³()

1. College of Public Administration, Huazhong University of Science & Technology, Wuhan 430079, China
2. College of Management and Economics, Tianjin University, Tianjin 300072, China
3. Jangho Architecture, Northeastern University, Shenyang 110004, China

Received:2020-10-13 Revised:2021-06-06 Published:2021-10-25 Online:2021-12-25
Supported by:
National Natural Science Foundation of China(42001334)

摘要/Abstract

摘要：

元胞自动机（CA）作为城市时空动态模拟应用最广泛的模型,可以有效模拟填充式和边缘式城市扩张过程,但是在飞地式扩张模拟方面稍显不足。本文提出一种改进CA模型—APCA,在传统CA基础上利用近邻传播聚类（AP）搜寻城市扩散增长的“种子点”,实现城市增长扩散过程和聚合过程的同步模拟。以武汉市为研究区域,使用APCA模拟其在2005—2025年间城市扩张的时空过程。结果显示：① APCA在设置“种子点”数量为1~8个时模拟总体精度均高于Logistics-CA,当“种子点”数量为6时,模拟新增部分精度最高,达到0.5217;② 2015—2025年武汉市飞地型增长面积约为8.67 km²,占新增城市用地总面积比例为6.30%;③ 武汉市1995—2025年间“先扩散后聚合”的城市扩张过程符合城市增长相位理论。APCA在一定程度上了完善了传统二维平面CA框架,将城市扩张模拟维度由面维扩展到点维,为准确展现城市用地空间扩展规律提供参考。

关键词: 元胞自动机, AP聚类, 扩散增长, 武汉市

Abstract:

Cellular automata (CA) has been widely recognized as an effective approach in the simulation of spatiotemporal dynamics of metropolitan areas, particularly for infilling and edge urban expansion processes. However, the traditional Logistics-CA has its severe drawbacks in simulating outlying expansion, since it evolves primarily according to the status of a set of neighboring cells, failing to identify other potential seeds that could also stimulate urban expansion in a significant way. This paper develops an advanced CA, called APCA, by using Affinity Propagation (AP) to comprehensively search for urban expansion seed points, as well as by realizing a synchronous simulation of diffusional and aggregational processes of urban cell. This paper uses the data of Wuhan, the largest provincial capital in central China, to validate the effectiveness of APCA. By simulating Wuhan's urban expansion dynamics between 1995 and 2025, the APCA (1) identifies that the total areas of outlying expansion amount to 8.67 km², accounting for 6.30% of added urban land of the city; and (2) successfully simulates a process of "first diffusion and then aggregation" in Wuhan, which is in harmony with the Phase Theory of urban expansion. Compared with the traditional Logistics-CA, the overall accuracy of APCA remains higher regardless of the number of seed points as long as they are within 1-8, while the accuracy of APCA reaches its highest (0.5217) when the seed point is set as 6. The APCA contributes to the two-dimensional CA framework by expanding surface-dimension simulation to point-dimension simulation, and thereby facilitates effective and accurate simulations of urban expansion patterns.

Key words: cellular automata, affinity propagation, diffusional urban expansion, Wuhan

何青松, 谭荣辉, 杨俊. 基于近邻传播聚类元胞自动机模型的武汉城市扩散和聚合过程同步模拟[J]. 地理学报, 2021, 76(10): 2522-2535.

HE Qingsong, TAN Ronghui, YANG Jun. Synchronized simulation of urban diffusional and aggregational process based on the affinity propagation cellular automata: A case study of Wuhan city[J]. Acta Geographica Sinica, 2021, 76(10): 2522-2535.

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种子点数量	1	2	3	4	5	6	7	8
整体部分精度	0.8632	0.8648	0.8724	0.8737	0.8748	0.8753	0.8721	0.8719
新增部分精度	0.4818	0.4866	0.5134	0.5136	0.5207	0.5217	0.5132	0.5015

区名	边缘型占比	填充型占比	飞地型占比
洪山区	67.19	32.81	0.00
江夏区	63.44	36.56	0.00
蔡甸区	63.77	5.74	30.49
汉阳区	80.53	19.47	0.00
江岸区	3.42	96.58	0.00
东西湖区	71.09	28.91	0.00
黄陂区	40.12	41.84	18.04
硚口区	98.99	1.01	0.00
汉南区	47.36	52.64	0.00
新洲区	10.04	89.96	0.00
武昌区	55.43	44.57	0.00
青山区	30.22	69.78	0.00
江汉区	0.00	100.00	0.00

基于近邻传播聚类元胞自动机模型的武汉城市扩散和聚合过程同步模拟

Synchronized simulation of urban diffusional and aggregational process based on the affinity propagation cellular automata: A case study of Wuhan city

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