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干旱地区耕地利用变化及其驱动力研究——以新疆伊宁市为例

On Change of Cultivated Land Use and Its Driving Forces in Arid Areas:A Case Study of Yining City,Xinjiang
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摘要 农业经济是伊宁市的主体经济,其耕地和草地比例占全区总面积的70.24%。随着城镇化加速和人口增加,大量耕地转为建设用地,而新增耕地则主要来源于草地。开垦草地是一个非常敏感的问题,草地开垦不当会挤占牧民赖以生存的空间,发生农牧矛盾。因此,伊宁市土地利用存在的风险集中在耕地和牧草地。以耕地利用变化为切入点,通过ArcGIS等软件分析2010—2018年期间伊宁市耕地动态变化情况。利用统计数据,结合研究区的实际情况,应用SPSS软件,通过建立多元回归模型,对伊宁市耕地利用变化的驱动因子从自然、社会经济等角度进行定量分析。为伊宁市耕地资源可持续、合理利用提供建议,促进研究区域农牧结合,协调发展。 Agriculture is the main economy of Yining City,whose cultivated land and grassland account for 70.24%of the total area.With the acceleration of urbanization and population growth,a large amount of cultivated land had been converted to construction land,while the new cultivated land was mainly derived from grassland.Reclamation of grassland was a very sensitive issue,as improper reclamation would crowd out the living space of herders,resulting in conflicts between agriculture and animal husbandry.Therefore,the risk of land use in Yining City was concentrated on cultivated land and grassland.Starting with the change of cultivated land use,this paper analyzed the dynamic changes of cultivated land in Yining City from 2010 to 2018 by using ArcGIS and other software.Then,based on statistical data and combined with the actual situation of the research area,this paper established a multiple-regression model through adopting SPSS software and quantitatively analyzed the driving factors of the change in the utilization of cultivated land in Yining City from the perspectives of nature,social economy and others.Suggestions for the sustainable and rational utilization of cultivated land resources in Yining City were provided to promote the integration and harmonious development of agriculture and animal husbandry in the research area.
作者 吾买尔艾力·艾买提卡力 李江风 AIMAITIKALI·Wumaieraili;LI Jiang-feng(School of Public Administration,China University of Geosciences,Wuhan 430074,China)
出处 《国土资源科技管理》 2021年第3期35-44,共10页 Scientific and Technological Management of Land and Resources
关键词 干旱地区 耕地资源 驱动因素 多元回归 主成分分析 arid areas cultivated land resources driving factors multiple regression principal component analysis
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