基于DBSCAN算法的郑洛地区史前聚落遗址聚类分析
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摘要
为了解决判别聚落群过于依赖考古专家人工划分的问题,以郑洛地区新石器时代聚落遗址为例,采用基于密度的DBSCAN(density-based spatial clustering of applications with noise)算法对聚落遗址进行空间聚类研究。通过对郑洛地区四个文化时期聚落遗址的分布分析,发现郑洛地区的主体聚落群从研究区东部的嵩山以南地区,转移到郑洛地区中部的伊洛河流域,并且在伊洛河流域长期定居下来,不断发展扩大;大型聚落遗址主要分布在主体聚落群里,除了裴李岗文化时期部分大型聚落较孤立;从仰韶文化后期到龙山文化时期,聚落遗址分布呈主从式环状分布格局;大多数聚落群的走向都和河流分布一致。研究表明,利用DBSCAN算法进行聚落遗址聚类是可行的,通过聚类得到郑洛地区新石器时代四个文化时期聚落遗址的分布特征。
To solve the problem that the classes are manually divided. The method of DBSCAN which is a spatial clustering algorithm based on density is used to analyze the sites in Zhengzhou-Luoyang area. It is found out that the main part of settlement in Zhengzhou-Luoyang area moved from the southern part of Songshan Mountain to Yiluohe basin,where the ancient people settled down and kept developing. Most of the large settlement sites distributed together,except the large settlement sites during Peiligang culture period,which are more isolated. The main classes distributed as a pattern of the master-slave ring from late Yangshao culture to Longshan culture. Besides,the trend of most classes is the same as the distribution of the river. The results of the clustering analysis suggested that using DBSCAN algorithm to divide the settlement sites into classes is feasible,and the clustering results revealed the spatial distribution pattern of the Neolithic settlement sites in Zhengzhou-Luoyang area.
To solve the problem that the classes are manually divided. The method of DBSCAN which is a spatial clustering algorithm based on density is used to analyze the sites in Zhengzhou-Luoyang area. It is found out that the main part of settlement in Zhengzhou-Luoyang area moved from the southern part of Songshan Mountain to Yiluohe basin,where the ancient people settled down and kept developing. Most of the large settlement sites distributed together,except the large settlement sites during Peiligang culture period,which are more isolated. The main classes distributed as a pattern of the master-slave ring from late Yangshao culture to Longshan culture. Besides,the trend of most classes is the same as the distribution of the river. The results of the clustering analysis suggested that using DBSCAN algorithm to divide the settlement sites into classes is feasible,and the clustering results revealed the spatial distribution pattern of the Neolithic settlement sites in Zhengzhou-Luoyang area.
引文
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7 乔文文,毕硕本,王启富,等.基于逻辑回归的郑洛地区龙山文化遗址预测模型研究.测绘科学,2013;38(06):172—181Qiao W W,Bi S B,Wang Q F,et al.Predictive model of archaeology sites of Longshan Culture in Zhengzhou-Luoyang area.Science of Surveying and Mapping,2013;38(06):172—181
8 Qiao W W,Bi S B.Analysis of spatial distribution of the Neolithic settlements in Zhengzhou-Luoyang area by using GIS.Applied Mathematics and Mechanics,2013;10(01):1518—1522
9 Bi S B,Qiao W W.Modeling the Neolithic settlements of ZhengzhouLuoyang area by weights of evidence.Journal of Convergence Information Technology,2013;8(01):1546—1552
10 于智航.改进的密度聚类算法研究.大连:大连理工大学,2007Yu Z H.Research on improved clustering algorithm based on density.Dalian:Dalian University of Technology,2007
11 杨瑞超.DBSCAN算法在地震相划分中的应用.西安:西安科技大学,2011Yang R C.Application of DBSCAN algorithm in seismicfacies classification.Xi'an:Xi'an University of Science and Technology,2011
12 陈济民.基于连续文化序列的史前聚落演变中的空间数据挖掘研究.南京:南京师范大学,2006Chen J M.The research of spatiak data mining for the evolvement of prehistoric settlements based on continuous culture sequence.Nanjing:Nanjing Normal University,2006
13 李新延,李德仁.DBSCAN空间聚类算法及其在城市规划中的应用.测绘科学,2005;30(3):51—53Li X Y,Li D R.DBSCAN spatial clustering algorithm and its application in urban planning.Science of Surveying and Mapping,2005;30 (3):51—53
14 孙凌燕.基于密度的聚类算法研究.太原:中北大学,2009Sun Lingyan.Research of clustering algorithm based on density.Taiyuan:North University of China,2009
2 许顺湛.河南仰韶文化聚落群研究.中原文物,2001;(05):19—28 Xu S Z.Research into the settlement clusters of Yangshao culture in Henan province.Cultural Relics of Central China,2001;(05):19—28
3 巩文.天水至郑州间仰韶文化晚期聚落群与中心聚落的初步考察.中原文物,2003;(04),28—38Gong W.Preliminary investigation into the settlement clusters and the central settlements distributing from Tianshui to Zhengzhou in the late Yangshao culture.Cultural Relics of Central China,2003;(04):28 —38
4 许顺湛.陕西仰韶文化聚落群的启示.中原文物,2002;(04):7 —13Xu S Z.Revelation from the settlement clusters of Yangshao culture in Shanxi province.Cultural Relics of Central China,2002;(04):7—13
5 黄以柱.略论豫西地区环境的变迁与对策.河南大学学报(自然科学版),1985;(1):51—58Huang Y Z.Argument on the change and countermeasures on the environment in western Henan province.Journal of Henan University(Natural Science),1995;(1):51—58
6 赵春青.郑洛地区新石器时代聚落的演变.北京:北京大学出版社,2001:42—46Zhao C Q.The evolvement of settlements during the Neolithic time in Zhengzhou-Luoyang area.Beijing:Beijing University Press,2001:42 —46
7 乔文文,毕硕本,王启富,等.基于逻辑回归的郑洛地区龙山文化遗址预测模型研究.测绘科学,2013;38(06):172—181Qiao W W,Bi S B,Wang Q F,et al.Predictive model of archaeology sites of Longshan Culture in Zhengzhou-Luoyang area.Science of Surveying and Mapping,2013;38(06):172—181
8 Qiao W W,Bi S B.Analysis of spatial distribution of the Neolithic settlements in Zhengzhou-Luoyang area by using GIS.Applied Mathematics and Mechanics,2013;10(01):1518—1522
9 Bi S B,Qiao W W.Modeling the Neolithic settlements of ZhengzhouLuoyang area by weights of evidence.Journal of Convergence Information Technology,2013;8(01):1546—1552
10 于智航.改进的密度聚类算法研究.大连:大连理工大学,2007Yu Z H.Research on improved clustering algorithm based on density.Dalian:Dalian University of Technology,2007
11 杨瑞超.DBSCAN算法在地震相划分中的应用.西安:西安科技大学,2011Yang R C.Application of DBSCAN algorithm in seismicfacies classification.Xi'an:Xi'an University of Science and Technology,2011
12 陈济民.基于连续文化序列的史前聚落演变中的空间数据挖掘研究.南京:南京师范大学,2006Chen J M.The research of spatiak data mining for the evolvement of prehistoric settlements based on continuous culture sequence.Nanjing:Nanjing Normal University,2006
13 李新延,李德仁.DBSCAN空间聚类算法及其在城市规划中的应用.测绘科学,2005;30(3):51—53Li X Y,Li D R.DBSCAN spatial clustering algorithm and its application in urban planning.Science of Surveying and Mapping,2005;30 (3):51—53
14 孙凌燕.基于密度的聚类算法研究.太原:中北大学,2009Sun Lingyan.Research of clustering algorithm based on density.Taiyuan:North University of China,2009
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