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山东省城市土地集约利用现状评价及其空间差异研究 被引量:5

Evaluation on the Present Situation of the Intensive Urban Land Use of Shandong Province and Its Special Difference
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摘要 为了促进山东省城市土地利用向集约化方向发展,以2010年山东省17个地级城市为研究对象,在借鉴国内外相关研究的基础上,建立土地集约利用评价指标体系,并运用主成分分析和聚类分析相结合的方法,探讨了山东省各城市土地集约利用现状及其空间差异。结果表明:山东省各城市土地集约利用度均不高,且区域差异明显。从空间角度来看,山东半岛的青岛、烟台、威海3市和济南的分值最高,而德州、聊城、菏泽、枣庄等远离山东省中心城市核心竞争群的城市得分较低。其格局大致形成由东北向西南穿插全省逐级递减,形成一个"N"字型的空间布局。进一步将上述17个城市可划分为4种不同的土地集约利用类型。最后结合山东省实际情况,提出了提高土地集约利用的建议和措施。 In order to promote the land use of Shandong Province into intensification, the author put 17 prefecture-lever cities of 2010' s Shandong Province as the study objects, on the basis of relevant researches at home and abroad. By building evaluation index system of intensive urban land use and exerting the methods of principal component analysis and cluster analysis, the author discussed the present situation and the special differences in intensive urban land use of cities in Shandong Province. The results showed that: the intensive use of land in Shandong Province was in a low degree, and it had distinct regional difference. From the perspective of space, Qingdao, Yantai and Weihai located in Shandong peninsula, and Ji' nan which located in the middle of Shandong, were in a high degree, while some cities which were far away from the central cities and core competitive groups, such as Dezhou, Liaocheng, Heze, Zaozhuang, and so on were in a low degree. The special pattern had formed approximately from northeast to southwest which crossed the whole Shandong Province and decreased step by step, taking shape of an ‘N' structure from the view of space. Then, the 17 cities above could be divided into 4 different types of intensive land use. Finally, combined with the actual situation in Shandong Province, the author put forward suggestions and measures to improve the intensive land use.
出处 《中国农学通报》 CSCD 2013年第32期136-143,共8页 Chinese Agricultural Science Bulletin
基金 鲁东大学2013年大学生科技创新基金项目与鲁东大学校专项基金项目"中国种植业区域优势测度及其优势区域识别"(LY2012001)
关键词 土地集约利用 主成分分析 聚类分析 山东省 intensive land use the principal component analysis cluster analysis Shandong Province
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