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多维视角下江西省余江县农村居民点分布特征及其影响因素 被引量:1

Multidimensional perspective study about rural residential distribution characteristics and its influencing factors of Yujiang County in Jiangxi Province
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摘要 以江西省余江县农村居民点为研究对象,引入VCM曲线、核密度估计法、空间自相关分析、Voronoi图和地形位指数等研究方法,从空间分布特征和布局影响因素出发,综合分析了余江县农村居民点的现状及其影响因素。结果表明,余江县农村居民点分布特征呈集聚型,居民点高值区集中在中部平原区域。影响居民点分布格局的主要因素为地形位指数、坡向、地质灾害、水土流失、道路、水系、城镇。农村居民点都向地形位指数优势区、坡向优势区、道路发达便捷区、水系优越区、城镇区集中;地质灾害易发区、地形位指数和坡向劣势区对居民点吸引力不强,分布的居民点较少。对居民点集中的优势区域,可作为重点发展型区域,对农村居民点建设进行合理的规划和引导;对居民点较少的劣势区域,如画桥镇、黄庄乡和塘潮源林场等,在做好防范措施的同时,建议逐步调整搬迁优化农村居民点。 Taking rural residential in Yujiang County as study object,the spatial distribution characteristics and in-fluencing factors were explored by VCM cure, kernel density estimation method, spatial autocorrelation analysis, Voronoi diagram,topographic index and so on. It was shown that the distribution of rural residential in Yujiang County belonged to cluster type. The high value of rural residential concentrated in the central plains area. The main factors influencing the rural residential distribution pattern consisted of topographic index, slope aspect, geological disasters, water loss and soil erosion, road, drainage, town. The rural residential concentrated to the topographic index advantage area, slope aspect advantage area, road developed area, drainage superior area and urban area. The geological-hazard-prone area, topographic index and slope aspect disadvantage area exhibited little appeal to rural residential. For the advantage region with a lot of rural residential,it could be used as the key developmental area, and reasonable planning and guidance should be provided for the construction of such area. While,for the disadvan-tage region with little rural residential,such as Huaqiao Town,Huangzhuang Village,Tangchaoyuan forest farm and so on,preventive measures and relocation work should be done.
出处 《浙江农业学报》 CSCD 北大核心 2016年第8期1428-1437,共10页 Acta Agriculturae Zhejiangensis
基金 国家自然科学基金资助项目(41361049) 江西省自然科学基金项目(20122BAB204012)
关键词 农村居民点 VCM曲线 核密度估计 空间自相关分析 rural residential VCM curve kernel density estimation spatial autocorrelation analysis
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