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基于空间自相关模型的农村居民点时空演变格局与特征研究
引用本文:任平,洪步庭,周介铭.基于空间自相关模型的农村居民点时空演变格局与特征研究[J].长江流域资源与环境,2015,24(12):1993-2002.
作者姓名:任平  洪步庭  周介铭
作者单位:1. 四川师范大学西南土地资源评价与监测教育部重点实验室, 四川 成都 610066;2. 四川师范大学国土资源开发与保护协同创新中心, 四川 成都 610066
基金项目:国家自然科学基金项目(41301196),国家973项目(2009CB421105)
摘    要:农村居民点作为农村人口重要空间聚集区,其空间布局、演变特征受历史、自然、社会、经济、传统文化等多重因素的影响。科学识别农村居民点的时空分布形态,并揭示其内在的变化规律和驱动因素,对促进农村居民点科学规划、提高农村土地资源空间布局优化均具有重要意义。利用都江堰市2005和2012年两期遥感影像提取农村居民点、城镇、道路、河流等矢量数据,借助RS、GIS空间分析技术,定量研究都江堰市农村居民点时空变化过程、格局和特征,并引入空间自回归模型深入分析不同环境因素对农村居民点空间布局的影响程度。研究结果表明:(1)都江堰市农村居民点的空间分布密度存在显著的空间正相关性,即密度值较高或较低的地区在空间上呈现显著的聚集状态,但局部的空间异质性在增强;(2)密度的高值集群主要集中分布在都江堰市东南部沙西线沿线以及南部成青快速通道一线,并且有进一步沿道路延线纵深扩张的趋势,而密度的低值集群由于受地形的影响,在空间分布上变化不大,主要位于龙门山沿线的乡镇;(3)2005~2012年,地形位指数每增加1%,农村居民点的空间密度减少0.505%,而距城镇、河流和道路的距离每增加1%,农村居民点的空间密度分别增加0.124%、0.144%、0.006%;(4)不同环境因素对农村居民点空间分布的影响程度大小为:地形影响城镇辐射影响河流影响道路影响,并且随着时间的推移,各环境因素的影响程度都在不断地增强。该研究以期为今后同类研究提供一定的方法借鉴,为农村居民点动态变化监测、农村土地节约集约利用、新农村规划等提供理论方法和技术应用支撑。

关 键 词:农村居民点  空间自相关  核密度  影响因素  

RESEARCH OF SPATIO-TEMPORAL PATTERN AND CHARACTERISTICS FOR THE EVOLUTION OF RURAL SETTLEMENTS BASED ON SPATIAL AUTOCORRELATION MODEL
REN Ping,HONG Bu-ting,ZHOU Jie-ming.RESEARCH OF SPATIO-TEMPORAL PATTERN AND CHARACTERISTICS FOR THE EVOLUTION OF RURAL SETTLEMENTS BASED ON SPATIAL AUTOCORRELATION MODEL[J].Resources and Environment in the Yangtza Basin,2015,24(12):1993-2002.
Authors:REN Ping  HONG Bu-ting  ZHOU Jie-ming
Institution:1. Key Lab of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Sichuan Normal University, Chengdu 610066, China;2. Collaborative Innovation Center for Land Resource Development and Protection, Sichuan Normal University, Chengdu 610066, China
Abstract:The spatial distribution and evolutional characteristics for rural settlements, which is an important form of human habitation in rural area, are driven by various factors, such as history, environment, society, economics, traditional culture, and so on.his paper, spatial analytical techniques in RS and GIS, utilized a series of digitalized vector data, including rural settlements, urban areas, road networks, rivers, and so on that were acquired from remote sensing data for the City of Dujiangyan in Sichuan Province for 2005 and 2012, quantitatively the spatio-temporal processes, patterns, and characteristics for the rural settlements in that studied area.Specifically, the spatial autocorrelation model was applied to deeply analyze the different influences by environmental factors to the form of spatial distribution for the rural settlements.The results indicated that: (1) In general there is a significant effect of spatial autocorrelation for the distribution density of rural settlements in the City of Dujiangyan, regions with higher/lower settlements density are neighboring with those with similar settlements density. the tendency of spatial heterogeneity becomes significant in some local areas.(2) The clusters with highest settlements density are mainly distributed at two regions, one is along Sha-Xi straight regions at Southeast of Dujiangyan, and the other is along Cheng-Qing rapid routeway at the South.Such high density regions are also found to be expanding along roads to inner area.However, the lower settlements density regions are majorly caused by the topographic factors since they are mainly distributed along the villages in Longmen Mountain area.Such lower density regions do not show an expanding tendency.(3) With 1% increasing in topographic index, the settlement density was decreasing by 0.505%.Similarly, with 1% increasing of distance to urban area, to river, and to road network, the settlement density would increase by 0.124%, 0.144% and 0.006%.(4) The rank for the influence by environmental factors to the rural settlements' spatial distribution follows: topography> urban > river > road network.Along with the time, such influences are all continuously increasing.This research is to provide some methodological reference to similar works in future.And it can also offer some theoretical and technical supports for dynamic monitoring for rural settlements, intensive use of rural land, and New Country planning.
Keywords:rural settlements  spatial autocorrelation  kernel density  influence factors
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