基于扩展生态位理论的居住空间分异研究——以兰州市为例

doi:10.12118/j.issn.1000-6060.2022.486

摘要/Abstract

摘要：

为了从生态位角度系统研究居住空间的分异状况，基于扩展生态位理论构建了居住生态位评价模型，实证分析了西北内陆中心城市兰州市主城区的居住空间分异。结果表明：（1）居住空间生态位呈现出以中心繁华城区为核心的高生态位，向外围圈层或扇形逐次递减的分布趋势；居住势既反映了区位的集聚和扩散功能，也体现了区位的过滤和排斥功能；居住态的空间分异一定程度上可以反映居住空间的分异状况，也能体现不同社会经济属性群体在空间上形成的相对地位和空间格局。（2）居住势、居住态和居住生态位较好的街道往往占据城市的优势区位且历史文化悠久、基础设施完善、公共服务健全、自然人文环境等都较好，特别是有高等学府、科研院所等单位坐落其中，居民的文化程度和收入水平都相对较高；而居住势、居住态和居住生态位较差的街道往往位于城区边缘，区位条件较差、基础设施落后、公共服务薄弱、地形起伏较大且交通不便、自然人文环境等相对较差，居民大都以农转非、棚改户、低保户等低收入群体为主且文化程度普遍较低。最后，提出了调控城市居住空间分异的政策建议。研究结果在丰富居住空间分异理论和研究案例的同时，对西北内陆中心城市的高质量发展具有重要的参考价值。

关键词: 扩展生态位理论, 居住空间分异, 生态位模型, 兰州市

Abstract:

In order to systematically study the differentiation of residential space from the perspective of the ecological niche theory, this paper constructs a residential niche evaluation model based on the extended ecological niche theory, and empirically analyzes the differentiation of residential space in the main urban area of Lanzhou City, a central inland city in northwest China. The results show the following key points: (1) The residential space niche shows a high ecological niche in the core downtown area, which gradually decreases toward the outer circle or fan. Residential potential not only reflects the agglomeration and diffusion function of location, but also reflects its filtering and exclusion function. To some extent, the spatial differentiation of residential state can reflect the differentiation of residential space, and it can also reflect the relative positions and spatial patterns of groups with different socio-economic attributes. (2) The streets with better potential, living state and living ecological niche tend to occupy the advantage of urban location, has a long history and culture, improved infrastructure, public services and good natural humanities environment, especially with universities, research institutes and other units located among them, the residents’ cultural level and the income level is relatively high. And the streets of poor potential, living state and living ecological niche are often located in the city edges, where the geographical condition is poor, with poor infrastructure, weak public services, uneven terrain, and inconvenient transportation, the natural humanities environment is relatively poor, the residents mostly in urbanized, shed tranform project households and low-income residents and the low-income groups are generally with low cultural level. Finally, some policy suggestions are put forward to regulate the differentiation of urban residential space. The research results not only enrich residential space differentiation theory and the associated corpus of case studies, but also provide important reference value for the high-quality development of inland central cities in northwest China.

Key words: extended niche theory, residential spatial differentiation, niche model, Lanzhou City

张文斌, 张志斌. 基于扩展生态位理论的居住空间分异研究——以兰州市为例[J]. 干旱区地理, 2023, 46(8): 1376-1386.

ZHANG Wenbin, ZHANG Zhibin. Residential spatial differentiation based on extended niche theory: A case of Lanzhou City[J]. Arid Land Geography, 2023, 46(8): 1376-1386.

图/表 6

图1

表1

表2

兰州市主城区各街道居住生态位单项和综合评价结果"

主城区	街道	L_i	N_i	C_i	D_i	S_i	I_i	A_i	P_i	EN_i
城关区	酒泉路街道	0.30	0.13	0.54	0.49	1.45	0.45	0.58	1.03	0.0248
	张掖路街道	0.33	0.14	0.55	0.39	1.40	0.54	0.57	1.11	0.0251
	雁南街道	0.29	0.09	0.25	0.47	1.11	0.51	0.53	1.04	0.0215
	临夏路街道	0.33	0.13	0.48	0.38	1.31	0.45	0.54	0.99	0.0231
	雁北街道	0.23	0.08	0.20	0.46	0.98	0.53	0.40	0.93	0.0191
	五泉街道	0.26	0.12	0.22	0.43	1.03	0.47	0.54	1.01	0.0204
	白银路街道	0.28	0.14	0.35	0.45	1.22	0.41	0.72	1.14	0.0236
	皋兰路街道	0.29	0.13	0.45	0.46	1.34	0.46	0.48	0.95	0.0228
	广武门街道	0.30	0.15	0.54	0.49	1.48	0.45	0.60	1.05	0.0253
	伏龙坪街道	0.09	0.02	0.07	0.27	0.45	0.49	0.20	0.70	0.0114
	靖远路街道	0.26	0.11	0.23	0.41	1.08	0.49	0.41	0.90	0.0191
	草场街街道	0.23	0.11	0.31	0.45	1.10	0.51	0.35	0.86	0.0196
	火车站街道	0.23	0.09	0.23	0.38	0.93	0.48	0.38	0.86	0.0180
	拱星墩街道	0.28	0.12	0.21	0.47	1.09	0.47	0.57	1.04	0.0213
	东岗街道	0.21	0.09	0.20	0.49	0.98	0.49	0.29	0.78	0.0176
	团结新村街道	0.28	0.14	0.24	0.43	1.09	0.48	0.39	0.87	0.0196
	东岗西路街道	0.30	0.16	0.35	0.46	1.38	0.45	0.56	1.69	0.0226
	铁路东村街道	0.24	0.15	0.33	0.44	1.16	0.45	0.54	1.00	0.0216
	铁路西村街道	0.25	0.15	0.25	0.50	1.15	0.46	0.42	0.88	0.0203
	渭源路街道	0.29	0.21	0.42	0.44	1.38	0.44	0.82	1.69	0.0264
	盐场路街道	0.15	0.07	0.20	0.43	0.84	0.57	0.50	1.07	0.0191
	嘉峪关路街道	0.31	0.11	0.18	0.45	1.06	0.47	0.54	1.01	0.0207
	焦家湾街道	0.25	0.15	0.34	0.35	1.09	0.49	0.42	0.91	0.0200
	青白石街道	0.02	0.03	0.07	0.22	0.33	0.66	0.21	0.87	0.0121
	高新区街道	0.16	0.04	0.09	0.41	0.71	0.53	0.51	1.24	0.0175
七里河区	西园街道	0.27	0.09	0.29	0.48	1.12	0.48	0.44	0.92	0.0205
	西湖街道	0.24	0.17	0.37	0.42	1.19	0.62	0.92	1.54	0.0273
	建兰路街道	0.22	0.16	0.32	0.37	1.07	0.46	0.48	0.94	0.0201
	敦煌路街道	0.18	0.12	0.31	0.38	0.99	0.48	0.43	0.91	0.0190
	西站街道	0.20	0.10	0.32	0.48	1.10	0.47	0.43	0.90	0.0200
	晏家坪街道	0.14	0.07	0.22	0.45	0.88	0.56	0.14	0.70	0.0158
	龚家湾街道	0.15	0.13	0.26	0.35	0.90	0.62	0.53	1.16	0.0205
	土门墩街道	0.21	0.06	0.24	0.48	0.99	0.52	0.33	0.85	0.0184
	秀川街道	0.14	0.06	0.18	0.35	0.72	0.48	0.38	0.86	0.0159
	彭家坪街道	0.22	0.04	0.15	0.32	0.73	0.52	0.36	0.88	0.0162
西固区	陈坪街道	0.14	0.07	0.14	0.37	0.72	0.55	0.41	0.97	0.0169
	先锋路街道	0.08	0.16	0.17	0.37	0.78	0.48	0.35	0.83	0.0161
	福利路街道	0.11	0.13	0.27	0.38	0.88	0.48	0.46	0.93	0.0182
	西固城街道	0.12	0.12	0.20	0.39	0.83	0.49	0.54	1.03	0.0186
	四季青街道	0.17	0.05	0.10	0.33	0.64	0.52	0.33	0.86	0.0150
	临洮街街道	0.14	0.10	0.25	0.40	0.89	0.50	0.36	0.85	0.0175
	西柳沟街道	0.12	0.05	0.21	0.37	0.75	0.52	0.39	0.92	0.0166
安宁区	培黎街道	0.23	0.19	0.39	0.42	1.24	0.38	0.97	1.67	0.0259
	西路街道	0.11	0.15	0.35	0.37	1.08	0.61	0.99	1.67	0.0258
	沙井驿街道	0.09	0.08	0.13	0.31	0.61	0.53	0.37	0.90	0.0151
	十里店街道	0.24	0.12	0.26	0.39	1.09	0.49	0.55	1.04	0.0204
	孔家崖街道	0.24	0.15	0.29	0.38	1.06	0.47	0.60	1.08	0.0213
	银滩路街道	0.25	0.14	0.30	0.44	1.13	0.61	1.07	1.58	0.0281
	刘家堡街道	0.20	0.08	0.32	0.53	1.13	0.39	1.02	0.72	0.0255
	安宁堡街道	0.13	0.05	0.17	0.36	0.71	0.51	0.06	0.58	0.0129

表2

图2

图3

图4

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指标	数据来源	数据获取说明
家庭月收入	问卷调查	各街道被调查居民的平均家庭月收入
户主学历	问卷调查	各街道被调查居民户主学历的众数
生活环境	POI数据	通过街道内标准化的商业休闲娱乐、医院医疗机构、学校教育机构、工业企事业单位的网络爬虫POI数据等计算而得
自然环境	POI数据	通过街道内街道中心点到黄河的距离和标准化的绿地公园面积等计算而得
交通环境	POI数据	通过街道内标准化的道路长度、街道内标准化的公交站点数等计算而得
区位环境	POI数据	通过街道内中心点到市中心距离等计算而得