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基于空间自相关的区域农村居民点分布与环境的关系研究 |
宋文1,2, 吴克宁1,2, 刘霈珈1,2, 高星1,2, 李晨曦1,2
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1.中国地质大学(北京)土地科学技术学院,北京 100083;2.国土资源部土地整治重点实验室,北京 100035
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摘要: |
为分析丘陵沟壑区农村居民点分布与自然、社会经济环境的关系,丰富相关研究的方法,为农村居民点整理实践提供科学参考。以甘肃省临夏县北塬地区为研究对象,以行政村为研究单元,将空间自相关分析方法和空间叠加分析方法相结合,并选择较优的分析指标农村居民点分离度对居民点分布与环境的关系进行分析。分析结果显示:临夏县北塬地区的农村居民点分离度指标的全局Moran指数为01637,并且置信度高于95%,农村居民点分布存在显著的空间自相关特征; 地形、河流、水库、公路和建制镇等自然、社会经济环境要素因子对北塬地区农村居民点的局部显著性空间聚集和异常特征的形成影响明显,同时发现北塬地区自然环境要素的影响占据主导地位。2种方法的结合可以有效地揭示环境因素对居民点分布的影响,居民点整理可根据主导影响因子的不同而采取差别化的整理模式和措施。 |
关键词: 农村居民点 分布特征 空间自相关 空间叠加 丘陵沟壑区 |
DOI:10.7621/cjarrp.1005-9121.20161211 |
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SPATIAL AUTOCORRELATION ANALYSIS OF RELATIONSHIP BETWEEN RURAL SETTLEMENTS AND THEIR ENVIRONMENT |
Song Wen1,2, Wu Kening1,2, Liu Peijia1,2, Gao Xing1,2, Li Chenxi1,2
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1.School of land Science and Technology,China University of Geosciences,Beijing 100083,China;2.Key Laboratory of land Consolidation and Rehabilitation,Ministry of land and Resources,Beijing 100035,China
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Abstract: |
This paper analyzed the spatial autocorrelation between rural settlements and their environment in Beiyuan hilly-gully region of Linxia county in central Gansu province. Factors from both natural and social-economic environments were considered.The purpose of this paper was to provide a reference for the rural settlements arrangement. Based on spatial autocorrelation and spatial overlay analysis method,this paper took administrative villages as the research unit and the degree of separation of rural settlements as a better index.The results indicated that the global Moran′s index of therural settlements separation was 0.1637,the confidence level was higher than 95%.The distribution of rural settlements showed significant spatial autocorrelation. The factors such as terrain,river,road,reservoir and town, apparently influenced the formation of local significant spatial aggregation, of which the natural environmental element was dominated.This paper can effectively reveal environmental factors influencing the distribution of rural residential land.The rural residential land arrangement should adopt different modes and measures according to different dominant factors. |
Key words: rural settlements distribution characteristics spatial autocorrelation spatial overlay hilly-gully region |